<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Archiving and Interchange DTD v2.3 20070202//EN" "archivearticle.dtd">
<article article-type="systematic-review" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xml:lang="EN">
<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Pediatr.</journal-id>
<journal-title>Frontiers in Pediatrics</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Pediatr.</abbrev-journal-title>
<issn pub-type="epub">2296-2360</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fped.2024.1368583</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pediatrics</subject>
<subj-group>
<subject>Systematic Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Evaluation of diagnostic accuracy of urine neutrophil gelatinase-associated lipocalin in patients with symptoms of urinary tract infections: a meta-analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Zhang</surname><given-names>Yin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn001"><sup>&#x2020;</sup></xref><uri xlink:href="https://loop.frontiersin.org/people/2666434/overview"/><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/resources/"/><role content-type="https://credit.niso.org/contributor-roles/software/"/><role content-type="https://credit.niso.org/contributor-roles/supervision/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/visualization/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author"><name><surname>Chen</surname><given-names>Chen</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref><uri xlink:href="https://loop.frontiersin.org/people/2089022/overview" /><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/resources/"/><role content-type="https://credit.niso.org/contributor-roles/software/"/><role content-type="https://credit.niso.org/contributor-roles/supervision/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/visualization/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author"><name><surname>Mitsnefes</surname><given-names>Mark</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref><uri xlink:href="https://loop.frontiersin.org/people/1001513/overview" /><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author"><name><surname>Huang</surname><given-names>Bin</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="author-notes" rid="fn001"><sup>&#x2020;</sup></xref><uri xlink:href="https://loop.frontiersin.org/people/1921892/overview" /><role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/project-administration/"/><role content-type="https://credit.niso.org/contributor-roles/resources/"/><role content-type="https://credit.niso.org/contributor-roles/software/"/><role content-type="https://credit.niso.org/contributor-roles/supervision/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
<contrib contrib-type="author" corresp="yes"><name><surname>Devarajan</surname><given-names>Prasad</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="corresp" rid="cor1">&#x002A;</xref>
<xref ref-type="author-notes" rid="fn001"><sup>&#x2020;</sup></xref><uri xlink:href="https://loop.frontiersin.org/people/422127/overview" /><role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/><role content-type="https://credit.niso.org/contributor-roles/data-curation/"/><role content-type="https://credit.niso.org/contributor-roles/formal-analysis/"/><role content-type="https://credit.niso.org/contributor-roles/funding-acquisition/"/><role content-type="https://credit.niso.org/contributor-roles/investigation/"/><role content-type="https://credit.niso.org/contributor-roles/methodology/"/><role content-type="https://credit.niso.org/contributor-roles/project-administration/"/><role content-type="https://credit.niso.org/contributor-roles/resources/"/><role content-type="https://credit.niso.org/contributor-roles/supervision/"/><role content-type="https://credit.niso.org/contributor-roles/validation/"/><role content-type="https://credit.niso.org/contributor-roles/visualization/"/><role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/><role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/></contrib>
</contrib-group>
<aff id="aff1"><label><sup>1</sup></label><institution>Division of Biostatistics and Epidemiology, Cincinnati Children&#x2019;s Hospital Medical Center</institution>, <addr-line>Cincinnati, OH</addr-line>, <country>United States</country></aff>
<aff id="aff2"><label><sup>2</sup></label><institution>Division of Nephrology and Hypertension, Cincinnati Children&#x2019;s Hospital Medical Center</institution>, <addr-line>Cincinnati, OH</addr-line>, <country>United States</country></aff>
<aff id="aff3"><label><sup>3</sup></label><institution>Department of Pediatrics, University of Cincinnati College of Medicine</institution>, <addr-line>Cincinnati, OH</addr-line>, <country>United States</country></aff>
<author-notes>
<fn fn-type="edited-by"><p><bold>Edited by:</bold> Robert P. Woroniecki, Stony Brook Children&#x0027;s Hospital, United States</p></fn>
<fn fn-type="edited-by"><p><bold>Reviewed by:</bold> O. P. Mishra, Heritage Institute of Medical Sciences, India</p>
<p>Nader Shaikh, University of Pittsburgh, United States</p></fn>
<corresp id="cor1"><label>&#x002A;</label><bold>Correspondence:</bold> Prasad Devarajan <email>prasad.devarajan@cchmc.org</email></corresp>
<fn fn-type="other" id="fn001"><label><sup>&#x2020;</sup></label><p>ORCID Yin Zhang <ext-link ext-link-type="uri" xlink:href="http://orcid.org/0000-0002-6127-7535">orcid.org/0000-0002-6127-7535</ext-link> Bin Huang <ext-link ext-link-type="uri" xlink:href="http://orcid.org/0000-0001-9724-675X">orcid.org/0000-0001-9724-675X</ext-link> Prasad Devarajan <ext-link ext-link-type="uri" xlink:href="http://orcid.org/0000-0002-7847-8552">orcid.org/0000-0002-7847-8552</ext-link></p></fn>
</author-notes>
<pub-date pub-type="epub"><day>22</day><month>05</month><year>2024</year></pub-date>
<pub-date pub-type="collection"><year>2024</year></pub-date>
<volume>12</volume><elocation-id>1368583</elocation-id>
<history>
<date date-type="received"><day>10</day><month>01</month><year>2024</year></date>
<date date-type="accepted"><day>23</day><month>04</month><year>2024</year></date>
</history>
<permissions>
<copyright-statement>&#x00A9; 2024 Zhang, Chen, Mitsnefes, Huang and Devarajan.</copyright-statement>
<copyright-year>2024</copyright-year><copyright-holder>Zhang, Chen, Mitsnefes, Huang and Devarajan</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p></license>
</permissions>
<abstract><sec><title>Introduction</title>
<p>Early and accurate diagnosis of urinary tract infection (UTI) can prevent serious sequelae including chronic kidney disease. Multiple individual studies have identified urine neutrophil gelatinase-associated lipocalin (uNGAL) as a promising biomarker for early diagnosis of UTI. We sought to understand the distribution and diagnostic accuracy of uNGAL values in patients presenting with UTI symptoms.</p>
</sec><sec><title>Methods</title>
<p>Our systematic literature reviews in PubMed, Embase, and Cochrane Reviews up to March 2024, identified 25 studies reporting mean/median, standard deviation/quartiles, and detection limits of uNGAL in symptomatic patients with and without culture-confirmed UTI. Seventeen studies were in children. Meta-analyses were performed using the quantile estimation (QE) method estimating the distributions of uNGAL, which were then compared between the UTI and non-UTI groups for identifying the best cut-off points maximizing the Youden index. Sensitivity analyses were performed on all 25 studies including adult patients.</p>
</sec><sec><title>Results</title>
<p>We found that uNGAL levels were significantly higher in samples with confirmed UTI compared to those without. In pediatric studies, median and 95&#x0025; confidence interval (CI) of uNGAL values were 22.41 (95&#x0025; CI of 9.94, 50.54) ng/mL in non-UTI group vs. 118.85 (95&#x0025; CI of 43.07, 327.97) ng/mL in UTI group. We estimated the cut-off point of 48.43 ng/mL with highest sensitivity (96&#x0025;) and specificity (97&#x0025;) in children. Sensitivity analysis including both pediatric and adult studies yielded similar results.</p>
</sec><sec><title>Discussion</title>
<p>The level of uNGAL in symptomatic patients with confirmed UTI is much higher than that reported in patients without UTI. It may be used as a diagnostic tool to identify UTI early among symptomatic patients. The range of uNGAL concentrations and cut-off points reported in subjects with UTI is much lower than that reported in patients with acute intrinsic kidney injury.</p>
</sec><sec><title>Systematic Review Registration</title>
<p><ext-link ext-link-type="uri" xlink:href="https://www.crd.york.ac.uk/">https://www.crd.york.ac.uk/</ext-link>, PROSPERO (CRD42023370451).</p>
</sec>
</abstract>
<kwd-group>
<kwd>neutrophil gelatinase-associated lipocalin</kwd>
<kwd>urinary tract infection</kwd>
<kwd>acute kidney injury</kwd>
<kwd>acute renal failure</kwd>
<kwd>meta-analysis</kwd>
</kwd-group><contract-num rid="cn001">P50DK096418</contract-num><contract-num rid="cn002">&#x00A0;</contract-num><contract-num rid="cn003">5UL1TR001425-03</contract-num><contract-sponsor id="cn001">NIH/NIDDK Center of Excellence in Nephrology</contract-sponsor><contract-sponsor id="cn002">Center for Clinical and Translational Science and Training</contract-sponsor><contract-sponsor id="cn003">NIH National Center for Advancing Translational Sciences</contract-sponsor><counts>
<fig-count count="7"/>
<table-count count="1"/><equation-count count="0"/><ref-count count="66"/><page-count count="0"/><word-count count="0"/></counts><custom-meta-wrap><custom-meta><meta-name>section-at-acceptance</meta-name><meta-value>Pediatric Nephrology</meta-value></custom-meta></custom-meta-wrap>
</article-meta>
</front>
<body><sec id="s1" sec-type="intro"><title>Introduction</title>
<p>A urinary tract infection (UTI) is commonly encountered in humans of all ages. Early and accurate diagnosis can prevent serious sequelae such as sepsis, renal scars, chronic kidney disease, and hypertension (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). However, the current gold standard for the diagnosis is a urine culture, the results of which are typically delayed by at least 48&#x2005;h. Furthermore, urine culture results may be confounded by sample contamination. The presence of classical UTI symptoms may aid in the initial suspicion; however, UTI symptoms can be nonspecific and misleading, especially in infants and children (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Currently available point-of-care screening tests lack sufficient accuracy. For example, the leukocyte esterase (LE) test has a reported sensitivity and specificity of 79&#x0025; and 87&#x0025; for the diagnosis of culture-positive UTI (<xref ref-type="bibr" rid="B3">3</xref>). This implies that by using the LE test, 21&#x0025; of true UTIs will be missed, leading to delayed treatment, and 13&#x0025; of subjects will receive a false-positive UTI diagnosis with resultant inappropriate antibiotic prescriptions. Indeed, more than 50&#x0025; of children who are empirically prescribed antibiotics in the emergency department setting for a suspected UTI were subsequently shown to not have a true UTI (<xref ref-type="bibr" rid="B4">4</xref>). The performance of urine WBC count and urinary nitrite is even poorer, with a sensitivity of 74&#x0025; and 45&#x0025; respectively (<xref ref-type="bibr" rid="B3">3</xref>). Thus, there is an unmet clinical need for a sensitive and specific urinary biomarker that can provide a rapid diagnosis in subjects with UTI symptoms.</p>
<p>In recent years, several urinary biomarkers have been investigated for their diagnostic accuracy for UTI, based on their established role in the host response to inflammatory urinary pathogens (<xref ref-type="bibr" rid="B5">5</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>). A contemporary unbiased approach used machine learning algorithms to explore 42 different immunological predictors for a positive urine culture among adult women with UTI symptoms (<xref ref-type="bibr" rid="B5">5</xref>). The most promising biomarkers identified were neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase 9 (MMP9), CXCL8 and interleukin-1&#x03B2; (IL-1&#x03B2;). While other targeted approaches over the years have additionally identified interleukin-8, tumor necrosis factor-&#x03B1;, and urine antimicrobial peptides (<xref ref-type="bibr" rid="B5">5</xref>&#x2013;<xref ref-type="bibr" rid="B7">7</xref>) as putative predictors of UTI, the most promising and widely studied UTI biomarker is NGAL (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B12">12</xref>). Pre-clinical studies have established the biological, teleological, and functional roles of NGAL (<xref ref-type="bibr" rid="B13">13</xref>&#x2013;<xref ref-type="bibr" rid="B18">18</xref>). There is now a strong rationale for the use of kidney-derived uNGAL as a UTI biomarker, independent of neutrophil presence or activation, in contrast to the LE and pyuria tests (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>).</p>
<p>Despite ample biologic plausibility, accumulating human evidence has revealed significant variations in the test characteristics and diagnostic accuracy of uNGAL for the diagnosis of UTI (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B12">12</xref>). In addition, uNGAL has also been widely investigated and advanced as a clinical diagnostic biomarker in other kidney diseases, especially in acute kidney injury (AKI) (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B28">28</xref>). Standard analytical laboratory platforms for the rapid measurement of uNGAL are already available and used globally for the early diagnosis and risk stratification of AKI in some centers. Thus, it is particularly important to understand the distribution of uNGAL values in patients with a possible UTI, to further clarify the use of uNGAL as a clinical diagnostic tool in other kidney conditions. Therefore, in this meta-analysis of all published studies to date, we aimed to determine and compare the distribution of uNGAL in subjects presenting with UTI symptoms. We also sought to determine the overall diagnostic accuracy of uNGAL, by determining the area under the receiver operating characteristic (ROC) curve and the optimal cut-off points for the prediction of UTI.</p>
</sec>
<sec id="s2" sec-type="methods"><title>Methods</title>
<sec id="s2a"><title>Study design</title>
<p>The meta-analysis of observational studies in epidemiology (MOOSE, <xref ref-type="bibr" rid="B29">29</xref>) guideline was used to summarize the evidence on value of uNGAL for the diagnosis of UTI. The PRISMA checklist for the reporting of this meta-analysis is shown in <xref ref-type="sec" rid="s9">Supplementary Table S1</xref>.</p>
</sec>
<sec id="s2b"><title>Search strategy</title>
<p>This review is registered with PROSPERO (registration number: CRD42023370451). The literature search was performed multiple times and finalized on 03/02/2024, using the electronic bibliographic databases: PubMed, Embase, and Cochrane Reviews. The search keywords were neutrophil gelatinase-associated lipocalin, NGAL, lipocalin, urinary tract infection, UTI, and urine culture. Articles written in English language and published from initiation of the database to March 2024 were retrieved. Studies were included in the analysis if they contained data on the combination of UTI symptoms, urine culture, and uNGAL. Studies reporting on plasma NGAL in UTI were not included in this analysis. Both pediatric and adult populations were included based on the current knowledge that uNGAL levels are similar in all ages beyond the immediate neonatal period. Conference abstracts were excluded. If the same data were reported in multiple studies, only the most comprehensive one was considered. Reference lists were also reviewed and identified for additional articles that may not be searchable in the databases.</p>
</sec>
<sec id="s2c"><title>Data extraction</title>
<p>The full text of these studies was screened, and the data were independently summarized by two researchers. A third researcher was involved in discussion to resolve uncertainty about eligibility of study. The primary outcome was the distribution of urine NGAL values in the UTI and non-UTI samples in subjects presenting with UTI symptoms. UTI was identified based on a positive urine culture. Summary statistics of the mean, standard deviation (SD), median, 25&#x0025;-tile (Q1), 75&#x0025;-tile (Q3), minimum, maximum, and sample size (n) were extracted from the identified studies separately for the groups with and without UTI. Study types (prospective cross-sectional study, retrospective cross-sectional study, and case-control study), sample characteristics including population, UTI diagnosis, assay type, and publication information (journal, author, year of publication) were also summarized and documented. Missing data and data inquiry were communicated directly with study authors.</p>
</sec>
<sec id="s2d"><title>Risk of bias and applicability concerns assessment</title>
<p>The risk of bias and applicability concerns among included studies were assessed based on quality assessment of diagnostic accuracy studies (QUADAS-2) recommendations (<xref ref-type="bibr" rid="B30">30</xref>). Two researchers conducted assessments in each study. The characteristics considered were patient selection, index test, reference standard, and flow and timing. Any disagreement was resolved through discussion between researchers.</p>
</sec>
<sec id="s2e"><title>Statistical analysis</title>
<p>The uNGAL is not normally distributed and may be subject to detection limits. Studies have therefore often reported median or mean of log transformed NGAL. Studies reported as median and quartiles are often not included in traditional meta-analysis studies utilizing reported means and standard deviations (SD) only. To include studies reporting median and quartiles as well as studies reporting mean and standard deviation, we applied Quantile Estimation (QE) method (<xref ref-type="bibr" rid="B31">31</xref>). This approach has gained popularity in meta-analyses of biomarker studies, allowing for the inclusion of a broader range of eligible studies by accommodating different statistical summaries (<xref ref-type="bibr" rid="B32">32</xref>&#x2013;<xref ref-type="bibr" rid="B34">34</xref>).</p>
<p>Our primary analysis focused on estimating distributions of uNGAL in pediatric populations with and without symptomatic UTI. We first applied the QE method implemented in the R package estmeansd, to convert all study reports into corresponding mean and standard deviation for both UTI and non-UTI samples. Then, random effect meta-analyses models were applied to estimate averaged mean and SD of log-transformed uNGAL, assuming log-normal distribution. Heterogeneities were reported using Cochran Q statistic and I&#x00B2;. Forest plot and funnel plots were generated for the UTI and non-UTI samples. Studies that included more than one non-UTI control samples were treated as two individual control samples. Finally, we estimated the optimal cut off point for uNGAL, and its corresponding sensitivity and specificity, by maximizing the Youden index (<xref ref-type="bibr" rid="B35">35</xref>). We conducted several sensitivity analyses by: (1) including both pediatric and adult populations, (2) excluding small UTI studies with sample size <italic>N</italic>&#x2009;&#x003C;&#x2009;50, (3) including healthy controls, and (4) excluding high/unclear risk of bias studies. A <italic>p</italic>-value &#x003C;0.05 was considered statistically significant. All analyses were performed in R version 4.2.2 (package: estmeansd and meta-analysis).</p>
</sec>
</sec>
<sec id="s3" sec-type="results"><title>Results</title>
<sec id="s3a"><title>Description of studies</title>
<p>In total, we identified 102 papers of which 35 full-text manuscripts were reviewed and 25 articles were included in our analyses (<xref ref-type="fig" rid="F1">Figure&#x00A0;1</xref>). There were 17 studies in children and 8 studies in adults. Overall, the study involved 2,985 patients, who had reported acute UTI symptoms with positive urine culture, acute pyelonephritis with positive culture, or recurrent UTIs. None of the patients were reported to have AKI, chronic kidney disease (CKD), or known congenital anatomic anomalies of the kidney or urinary tract. Urine samples were collected by catheter, sterile bag, midstream catch, or suprapubic aspirate. The detailed summary of eligible studies is shown in <xref ref-type="table" rid="T1">Table&#x00A0;1</xref>.</p>
<fig id="F1" position="float"><label>Figure 1</label>
<caption><p>Flow diagram of search strategy.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g001.tif"/>
</fig>
<table-wrap id="T1" position="float"><label>Table 1</label>
<caption><p>Summary of eligible studies.</p></caption>
<table frame="hsides" rules="groups">
<colgroup>
<col align="left"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
<col align="center"/>
</colgroup>
<thead>
<tr>
<th valign="top" align="left" colspan="5"/>
<th valign="top" align="center">Sub group</th>
<th valign="top" align="center" colspan="2">UTI group</th>
<th valign="top" align="center" colspan="2">Control group</th>
<th valign="top" align="center" colspan="2">Healthy control</th>
<th valign="top" align="center" colspan="5"/>
</tr>
<tr>
<th valign="top" align="center">Ref</th>
<th valign="top" align="center">Publication</th>
<th valign="top" align="center">Population</th>
<th valign="top" align="center">Sample</th>
<th valign="top" align="center">Assay</th>
<th valign="top" align="center"/>
<th valign="top" align="center"><italic>N</italic></th>
<th valign="top" align="center">Statistics</th>
<th valign="top" align="center"><italic>N</italic></th>
<th valign="top" align="center">Statistics</th>
<th valign="top" align="center"><italic>N</italic></th>
<th valign="top" align="center">Statistics</th>
<th valign="top" align="center">AUC</th>
<th valign="top" align="center">Cutoff</th>
<th valign="top" align="center">Sensitivity</th>
<th valign="top" align="center">Specificity</th>
<th valign="top" align="center">Method of define Cut off</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B36">36</xref></td>
<td valign="top" align="left" rowspan="2">Petrovic 2013</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Sterile bag</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">50</td>
<td valign="top" align="left">Mean 155</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">SD 92.39</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B37">37</xref></td>
<td valign="top" align="left" rowspan="2">Kim 2014</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">284</td>
<td valign="top" align="left">Mean 19</td>
<td valign="top" align="center" rowspan="2">528</td>
<td valign="top" align="left">Mean 14.3</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.58</td>
<td valign="top" align="center" rowspan="2">5.75</td>
<td valign="top" align="center" rowspan="2">70&#x0025;</td>
<td valign="top" align="center" rowspan="2">42&#x0025;</td>
<td valign="top" align="left" rowspan="2">ROC analysis</td>
</tr>
<tr>
<td valign="top" align="left">SD 44.5</td>
<td valign="top" align="left">SD 34.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="3"><xref ref-type="bibr" rid="B38">38</xref></td>
<td valign="top" align="left" rowspan="3">Urbschat 2014</td>
<td valign="top" align="left" rowspan="3">Adults</td>
<td valign="top" align="left" rowspan="3">Midstream catch</td>
<td valign="top" align="left" rowspan="3">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="3">Upper UTI</td>
<td valign="top" align="center" rowspan="3">30</td>
<td valign="top" align="left" rowspan="2">Mean 111.07</td>
<td valign="top" align="left" rowspan="3" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="3">38</td>
<td valign="top" align="left">Mean 49.78</td>
<td valign="top" align="left" rowspan="3">&#x2013;</td>
<td valign="top" align="left" rowspan="3">&#x2013;</td>
<td valign="top" align="left" rowspan="3">&#x2013;</td>
<td valign="top" align="left" rowspan="3">&#x2013;</td>
<td valign="top" align="left" rowspan="3">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2">SD 58.6</td>
</tr>
<tr>
<td valign="top" align="left">SD 114.29</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B38">38</xref></td>
<td valign="top" align="left" rowspan="2">Urbschat 2014</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">Lower UTI</td>
<td valign="top" align="center" rowspan="2">29</td>
<td valign="top" align="left">Mean 100.61</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">SD 95.38</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B39">39</xref></td>
<td valign="top" align="left" rowspan="2">Lee 2015</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">33</td>
<td valign="top" align="left">Median 380</td>
<td valign="top" align="center">3</td>
<td valign="top" align="left">Median 16</td>
<td valign="top" align="center" rowspan="2">33</td>
<td valign="top" align="left">Median 10</td>
<td valign="top" align="left" rowspan="2" colspan="4">Prediction metrics for NGAL/Creatinine ratio only</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 250, 725</td>
<td valign="top" align="center">3</td>
<td valign="top" align="left">IQR 6, 39</td>
<td valign="top" align="left">IQR 1, 28</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B40">40</xref></td>
<td valign="top" align="left" rowspan="2">Nickavar 2016</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Various</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">37</td>
<td valign="top" align="left">Median 0.48</td>
<td valign="top" align="center" rowspan="2">26</td>
<td valign="top" align="left">Median 0.065</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.75</td>
<td valign="top" align="center" rowspan="2">0.2</td>
<td valign="top" align="center" rowspan="2">76&#x0025;</td>
<td valign="top" align="center" rowspan="2">77&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.15, 0.72</td>
<td valign="top" align="left">IQR 0.01, 0.24</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B41">41</xref></td>
<td valign="top" align="left" rowspan="2">Price 2017</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">50</td>
<td valign="top" align="left">Median 88.9</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">50</td>
<td valign="top" align="left">Median 3.6</td>
<td valign="top" align="center" rowspan="2">0.99</td>
<td valign="top" align="center" rowspan="2">23.9</td>
<td valign="top" align="center" rowspan="2">89&#x0025;</td>
<td valign="top" align="center" rowspan="2">100&#x0025;</td>
<td valign="top" align="left" rowspan="2">ROC analysis</td>
</tr>
<tr>
<td valign="top" align="left">IQR 40.7, 193.4</td>
<td valign="top" align="left">IQR 2.5, 8.1</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B42">42</xref></td>
<td valign="top" align="left" rowspan="2">Lubell2017</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">35</td>
<td valign="top" align="left">Median 215.1</td>
<td valign="top" align="center" rowspan="2">225</td>
<td valign="top" align="left">Median 4.4</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.98</td>
<td valign="top" align="center" rowspan="2">39.1</td>
<td valign="top" align="center" rowspan="2">97&#x0025;</td>
<td valign="top" align="center" rowspan="2">96&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 100.3, 917.8</td>
<td valign="top" align="left">IQR 1.6, 11.8</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B43">43</xref></td>
<td valign="top" align="left" rowspan="2">Valdimarsson 2017</td>
<td valign="top" align="left" rowspan="2">Infants</td>
<td valign="top" align="left" rowspan="2">Suprapubic aspirate</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">108</td>
<td valign="top" align="left">Median 192</td>
<td valign="top" align="center" rowspan="2">64</td>
<td valign="top" align="left">Median LOD</td>
<td valign="top" align="center" rowspan="2">13</td>
<td valign="top" align="left">Median LOD</td>
<td valign="top" align="center" rowspan="2">0.97</td>
<td valign="top" align="center" rowspan="2">38</td>
<td valign="top" align="center" rowspan="2">93&#x0025;</td>
<td valign="top" align="center" rowspan="2">95&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 100, 364</td>
<td valign="top" align="left">IQR LOD, 16.5</td>
<td valign="top" align="left">IQR LOD, LOD</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B44">44</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2018</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">UTC</td>
<td valign="top" align="center" rowspan="2">24</td>
<td valign="top" align="left">Median 434</td>
<td valign="top" align="center" rowspan="2">100</td>
<td valign="top" align="left">Median 135</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.88</td>
<td valign="top" align="center" rowspan="2">229</td>
<td valign="top" align="center" rowspan="2">83&#x0025;</td>
<td valign="top" align="center" rowspan="2">86&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 309, 969</td>
<td valign="top" align="left">IQR 54, 224</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B44">44</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2018</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">No growth</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">77</td>
<td valign="top" align="left">Median 18</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 5, 78</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B45">45</xref></td>
<td valign="top" align="left" rowspan="2">Jung 2018</td>
<td valign="top" align="left" rowspan="2">Infants</td>
<td valign="top" align="left" rowspan="2">Bag</td>
<td valign="top" align="left" rowspan="2">Immunoassay (Architect)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">102</td>
<td valign="top" align="left">Median 366.6</td>
<td valign="top" align="center" rowspan="2">320</td>
<td valign="top" align="left">Median 26.9</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.94</td>
<td valign="top" align="center" rowspan="2">46.2</td>
<td valign="top" align="center" rowspan="2">90&#x0025;</td>
<td valign="top" align="center" rowspan="2">93&#x0025;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Range 4.5&#x2013;742.3</td>
<td valign="top" align="left">Range 0.7&#x2013;304.4</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B46">46</xref></td>
<td valign="top" align="left" rowspan="2">Krzemien 2018</td>
<td valign="top" align="left" rowspan="2">Infants</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioVendor)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">42</td>
<td valign="top" align="left">Mean 67.5</td>
<td valign="top" align="center" rowspan="2">24</td>
<td valign="top" align="left">Mean 48</td>
<td valign="top" align="center" rowspan="2">18</td>
<td valign="top" align="left">Mean 38</td>
<td valign="top" align="center" rowspan="2">0.76</td>
<td valign="top" align="center" rowspan="2">42.2</td>
<td valign="top" align="center" rowspan="2">74&#x0025;</td>
<td valign="top" align="center" rowspan="2">72&#x0025;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">SD 34.8</td>
<td valign="top" align="left">SD 41.1</td>
<td valign="top" align="left">SD 32.3</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B5">5</xref></td>
<td valign="top" align="left" rowspan="2">Gadalla 2019</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (Mologic)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">79</td>
<td valign="top" align="left">Median 45.25</td>
<td valign="top" align="center" rowspan="2">104</td>
<td valign="top" align="left">Median 22.63</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">Range 1&#x2013;59.7</td>
<td valign="top" align="left">Range 1&#x2013;59.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B47">47</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2020</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">Single UTI</td>
<td valign="top" align="center" rowspan="2">44</td>
<td valign="top" align="left">Median 456</td>
<td valign="top" align="center" rowspan="2">6</td>
<td valign="top" align="left">Median 37</td>
<td valign="top" align="center" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.96</td>
<td valign="top" align="left" rowspan="2" colspan="3">For Creatinine standardized NGAL only</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 214, 779</td>
<td valign="top" align="left">IQR 19, 52</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B47">47</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2020</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">Recurrent UTI</td>
<td valign="top" align="center" rowspan="2">20</td>
<td valign="top" align="left">Median 395</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 144, 463</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B48">48</xref></td>
<td valign="top" align="left" rowspan="2">Shaikh 2020</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (Thermofisher)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">111</td>
<td valign="top" align="left">Mean 620.49</td>
<td valign="top" align="center" rowspan="2">89</td>
<td valign="top" align="left">Mean 140.02</td>
<td valign="top" align="center" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.89</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">79&#x0025;</td>
<td valign="top" align="center" rowspan="2">90&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">SD 554.54</td>
<td valign="top" align="left">SD 337.84</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B49">49</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2021</td>
<td valign="top" align="left" rowspan="2">Adults with NLUTD</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">Unlikely UTI</td>
<td valign="top" align="center" rowspan="2">8</td>
<td valign="top" align="left">Median 187</td>
<td valign="top" align="center" rowspan="2">67</td>
<td valign="top" align="left">Median 95</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 146, 224</td>
<td valign="top" align="left">IQR 37, 161</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B49">49</xref></td>
<td valign="top" align="left" rowspan="2">Forster 2021</td>
<td valign="top" align="left" rowspan="2">Adults with NLUTD</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">No UTI</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">29</td>
<td valign="top" align="left">Median 37</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 15, 71</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B50">50</xref></td>
<td valign="top" align="left" rowspan="2">Lubell 2022</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">Possible Positive UTI</td>
<td valign="top" align="center" rowspan="2">21</td>
<td valign="top" align="left">Median 210.1</td>
<td valign="top" align="center" rowspan="2">7</td>
<td valign="top" align="left">Median 16.5</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.96</td>
<td valign="top" align="center" rowspan="2">39.1</td>
<td valign="top" align="center" rowspan="2">91&#x0025;</td>
<td valign="top" align="center" rowspan="2">94&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">IQR 95.8, 1000</td>
<td valign="top" align="left">IQR 12, 162.1</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B50">50</xref></td>
<td valign="top" align="left" rowspan="2">Lubell 2022</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">Culture Negative</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">183</td>
<td valign="top" align="left">Median 0.01</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.01, 11.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B51">51</xref></td>
<td valign="top" align="left" rowspan="2">Moon 2021</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">Immunoassay (Architect)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">157</td>
<td valign="top" align="left">Mean 240.9</td>
<td valign="top" align="center" rowspan="2">164</td>
<td valign="top" align="left">Mean 31.6</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">0.86</td>
<td valign="top" align="center" rowspan="2">36.5</td>
<td valign="top" align="center" rowspan="2">82&#x0025;</td>
<td valign="top" align="center" rowspan="2">79&#x0025;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">SD 292.4</td>
<td valign="top" align="left">SD 63.1</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B52">52</xref></td>
<td valign="top" align="left" rowspan="2">Pamuk 2022</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioVendor)</td>
<td valign="top" align="left" rowspan="2">Lower UTI</td>
<td valign="top" align="center" rowspan="2">30</td>
<td valign="top" align="left">Median 30.3</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x2013;</td>
<td valign="top" align="center" rowspan="2">28</td>
<td valign="top" align="left">Median 4.16</td>
<td valign="top" align="center" rowspan="2">0.95</td>
<td valign="top" align="center" rowspan="2">15.6</td>
<td valign="top" align="center" rowspan="2">92&#x0025;</td>
<td valign="top" align="center" rowspan="2">86&#x0025;</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 22.57, 61.73</td>
<td valign="top" align="left">IQR 1.71, 11.74</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B52">52</xref></td>
<td valign="top" align="left" rowspan="2">Pamuk 2022</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioVendor)</td>
<td valign="top" align="left" rowspan="2">Pyelonephritis</td>
<td valign="top" align="center" rowspan="2">29</td>
<td valign="top" align="left">Median 66.15</td>
<td valign="top" align="left" rowspan="2" colspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 25.66, 87.61</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B53">53</xref></td>
<td valign="top" align="left" rowspan="2">Shaikh 2022</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (Thermofisher)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">75</td>
<td valign="top" align="left">Mean 419.99</td>
<td valign="top" align="left">69</td>
<td valign="top" align="left">Mean 8</td>
<td valign="top" align="left">48</td>
<td valign="top" align="left">Mean 4.3775</td>
<td valign="top" align="center" rowspan="2">1</td>
<td valign="top" align="center" rowspan="2">39.1</td>
<td valign="top" align="center" rowspan="2">100&#x0025;</td>
<td valign="top" align="center" rowspan="2">97&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">SD 134.2</td>
<td valign="top" align="left"/>
<td valign="top" align="left">SD 40.7</td>
<td valign="top" align="left"/>
<td valign="top" align="left">SD 21.4</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B54">54</xref></td>
<td valign="top" align="left" rowspan="2">Haley 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">M-PCR&#x002B;/SUC- 10K</td>
<td valign="top" align="center" rowspan="2">86</td>
<td valign="top" align="left">Median 117.4</td>
<td valign="top" align="center" rowspan="2">120</td>
<td valign="top" align="left">Median 14.47</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="6" colspan="5">The optimal cut-off point was determined using thresholds presented previously in the literature (38.0)</td>
</tr>
<tr>
<td valign="top" align="left">IQR 13.9, 299.2</td>
<td valign="top" align="left">IQR 0.2, 40.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B54">54</xref></td>
<td valign="top" align="left" rowspan="2">Haley 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">M-PCR-/SUC&#x2009;&#x002B;&#x2009;10K</td>
<td valign="top" align="center" rowspan="2">26</td>
<td valign="top" align="left">Median 12.79</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 1.02, 89.51</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B54">54</xref></td>
<td valign="top" align="left" rowspan="2">Haley 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">&#x2013;</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">Both positive 10K</td>
<td valign="top" align="center" rowspan="2">351</td>
<td valign="top" align="left">Median 201.75</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 57.46, 489.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="3"><xref ref-type="bibr" rid="B55">55</xref></td>
<td valign="top" align="left" rowspan="3">Kim 2023</td>
<td valign="top" align="left" rowspan="3">Children</td>
<td valign="top" align="left" rowspan="3">Catheter</td>
<td valign="top" align="left" rowspan="3">Immunoassay (Architect)</td>
<td valign="top" align="left" rowspan="3">&#x00A0;</td>
<td valign="top" align="center" rowspan="3">218</td>
<td valign="top" align="left" rowspan="2">Median 204.5</td>
<td valign="top" align="center" rowspan="3">238</td>
<td valign="top" align="left">Median 33</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="center" rowspan="3">0.74</td>
<td valign="top" align="center" rowspan="3">68.4</td>
<td valign="top" align="left" rowspan="3" colspan="2">Subgroups only</td>
<td valign="top" align="left" rowspan="3">AUC after dichotomize</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2">IQR 8.7, 104</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 87.9, 461.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B56">56</xref></td>
<td valign="top" align="left" rowspan="2">Parnell 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">No Microbes Detected</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">117</td>
<td valign="top" align="left">Median 16.05</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="8" colspan="5">Previously published thresholds for biomarker positivity were used as cut-off point (38.0)</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.2, 50.4</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B56">56</xref></td>
<td valign="top" align="left" rowspan="2">Parnell 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">&#x003C;10,000 cells/ml</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">23</td>
<td valign="top" align="left">Median 34.55</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">IQR 8.75, 114.25</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B56">56</xref></td>
<td valign="top" align="left" rowspan="2">Parnell 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="center" rowspan="2">10,000&#x2013;99,999 cells/ml</td>
<td valign="top" align="center" rowspan="2">79</td>
<td valign="top" align="left">Median 53.8</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">IQR 12.8, 231</td>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B56">56</xref></td>
<td valign="top" align="left" rowspan="2">Parnell 2023</td>
<td valign="top" align="left" rowspan="2">Adults</td>
<td valign="top" align="left" rowspan="2">Midstream catch</td>
<td valign="top" align="left" rowspan="2">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="2">&#x2265;100,000 cells/ml</td>
<td valign="top" align="center" rowspan="2">364</td>
<td valign="top" align="left">Median 228.9</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
</tr>
<tr>
<td valign="top" align="left">IQR 75.2, 494.6</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2"><xref ref-type="bibr" rid="B57">57</xref></td>
<td valign="top" align="left" rowspan="2">Shaikh 2023</td>
<td valign="top" align="left" rowspan="2">Children</td>
<td valign="top" align="left" rowspan="2">Catheter</td>
<td valign="top" align="left" rowspan="2">ELISA (BioPorto)</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">50</td>
<td valign="top" align="left">Mean 326.5</td>
<td valign="top" align="center" rowspan="2">324</td>
<td valign="top" align="left">Mean 16.7</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="left" rowspan="2">&#x00A0;</td>
<td valign="top" align="center" rowspan="2">0.96</td>
<td valign="top" align="center" rowspan="2">39.93</td>
<td valign="top" align="center" rowspan="2">90&#x0025;</td>
<td valign="top" align="center" rowspan="2">96&#x0025;</td>
<td valign="top" align="left" rowspan="2">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left">SD 258.6</td>
<td valign="top" align="left">SD 67.9</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="4"><xref ref-type="bibr" rid="B58">58</xref></td>
<td valign="top" align="left" rowspan="4">Akhlaghpour 2024</td>
<td valign="top" align="left" rowspan="4">Adults</td>
<td valign="top" align="left" rowspan="4">Midstream catch</td>
<td valign="top" align="left" rowspan="4">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="4">Symptomatic, SUC and M-PCR &#x002B;</td>
<td valign="top" align="center" rowspan="4">351</td>
<td valign="top" align="left">Mean 251.8</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="16" colspan="5">Previously published thresholds for biomarker positivity were used as cut-off point (38.0)</td>
</tr>
<tr>
<td valign="top" align="left">SD 193.9</td>
</tr>
<tr>
<td valign="top" align="left">Median 211</td>
</tr>
<tr>
<td valign="top" align="left">IQR 64.6, 500</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="4"><xref ref-type="bibr" rid="B58">58</xref></td>
<td valign="top" align="left" rowspan="4">Akhlaghpour 2024</td>
<td valign="top" align="left" rowspan="4">Adults</td>
<td valign="top" align="left" rowspan="4">Midstream catch</td>
<td valign="top" align="left" rowspan="4">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="4">Asymptomatic, No Microbes</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="center" rowspan="4">110</td>
<td valign="top" align="left">Mean 4.2</td>
</tr>
<tr>
<td valign="top" align="left">SD 11.3</td>
</tr>
<tr>
<td valign="top" align="left">Median 0.16</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.16, 0.16</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="4"><xref ref-type="bibr" rid="B58">58</xref></td>
<td valign="top" align="left" rowspan="4">Akhlaghpour 2024</td>
<td valign="top" align="left" rowspan="4">Adults</td>
<td valign="top" align="left" rowspan="4">Midstream catch</td>
<td valign="top" align="left" rowspan="4">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="4">Asymptomatic, SUC or M-PCR &#x002B;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="center" rowspan="4">118</td>
<td valign="top" align="left">Mean 24.4</td>
</tr>
<tr>
<td valign="top" align="left">SD 56.8</td>
</tr>
<tr>
<td valign="top" align="left">Median 0.16</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.16, 17.7</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="4"><xref ref-type="bibr" rid="B58">58</xref></td>
<td valign="top" align="left" rowspan="4">Akhlaghpour 2024</td>
<td valign="top" align="left" rowspan="4">Adults</td>
<td valign="top" align="left" rowspan="4">Midstream catch</td>
<td valign="top" align="left" rowspan="4">ELISA (R&#x0026;D Systems)</td>
<td valign="top" align="left" rowspan="4">Asymptomatic, SUC and M-PCR &#x002B;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="left" rowspan="4">&#x00A0;</td>
<td valign="top" align="center" rowspan="4">51</td>
<td valign="top" align="left">Mean 36.5</td>
</tr>
<tr>
<td valign="top" align="left">SD 70.2</td>
</tr>
<tr>
<td valign="top" align="left">Median 9.5</td>
</tr>
<tr>
<td valign="top" align="left">IQR 0.16, 27</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="3"><xref ref-type="bibr" rid="B59">59</xref></td>
<td valign="top" align="left" rowspan="3">Bilsen 2024</td>
<td valign="top" align="left" rowspan="3">Adults</td>
<td valign="top" align="left" rowspan="3">Midstream catch</td>
<td valign="top" align="left" rowspan="3">LC-MS</td>
<td valign="top" align="left" rowspan="3">&#x00A0;</td>
<td valign="top" align="center" rowspan="3">62</td>
<td valign="top" align="left">Median 594</td>
<td valign="top" align="left" rowspan="3">&#x00A0;</td>
<td valign="top" align="left" rowspan="3">&#x00A0;</td>
<td valign="top" align="center" rowspan="3">100</td>
<td valign="top" align="left" rowspan="2">Median 59</td>
<td valign="top" align="center" rowspan="3">0.86</td>
<td valign="top" align="center" rowspan="3">201</td>
<td valign="top" align="center" rowspan="3">87&#x0025;</td>
<td valign="top" align="center" rowspan="3">72&#x0025;</td>
<td valign="top" align="left" rowspan="3">Youden Index</td>
</tr>
<tr>
<td valign="top" align="left" rowspan="2">IQR 289, 1772</td>
</tr>
<tr>
<td valign="top" align="left">IQR 20, 234</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3b"><title>Risk of bias and applicability concerns</title>
<p>The risk of bias assessment of 25 included studies (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B36">36</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>) was performed according to the guidance of QUADAS-2. Twelve studies were rated as having low risk of all four domains of bias and were classified as low risk of bias (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B46">46</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>, <xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B57">57</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>). Six studies were classified as having high risk of bias (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B38">38</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B49">49</xref>). Seven remaining studies had unclear risk of bias (<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B52">52</xref>, <xref ref-type="bibr" rid="B54">54</xref>&#x2013;<xref ref-type="bibr" rid="B56">56</xref>). Details on the rating of each risk of bias are shown in <xref ref-type="fig" rid="F2">Figure&#x00A0;2</xref>.</p>
<fig id="F2" position="float"><label>Figure 2</label>
<caption><p>Rating of risk of biases and applicability concerns.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g002.tif"/>
</fig>
<p>The risk of applicability concerns assessment of the same 25 included studies (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B36">36</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>) was also performed according to the guidance of QUADAS-2. Sixteen studies were rated as having low risk of all three domain of applicability concerns (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B57">57</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>). Seven studies were classified as having high risk of applicability concerns (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B38">38</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B54">54</xref>). Two studies had unclear risk of applicability concern (<xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B56">56</xref>). Details on the rating of each applicability concern domain are shown in <xref ref-type="fig" rid="F2">Figure&#x00A0;2</xref>.</p>
</sec>
<sec id="s3c"><title>Quantitative analysis: non-UTI samples in pediatric studies</title>
<p>The forest plot shown in <xref ref-type="fig" rid="F3">Figure&#x00A0;3A</xref> summarizes the log transformed uNGAL value in each study for the non-UTI samples reported in the pediatric studies. 16 non-UTI groups from 14 studies were included (<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>, <xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B57">57</xref>). Summarized mean and standard deviation were reported. The results suggested that the median uNGAL value in the non-UTI children population is 22.41 (95&#x0025; CI of 9.94, 50.54) ng/ml. No potential heterogeneous issue was detected, with Cochran Q statistic 11.98 (15 DF), <italic>P</italic>&#x2009;&#x003D;&#x2009;0.68. The <italic>I</italic><sup>2</sup> of 0&#x0025; was also statistically insignificant. Details are shown in funnel plots (<xref ref-type="fig" rid="F3">Figure&#x00A0;3B</xref>).</p>
<fig id="F3" position="float"><label>Figure 3</label>
<caption><p>(<bold>A</bold>) forest plot of log<sub>e</sub>-transformed NGAL values for non-UTI samples in pediatric studies. Each row corresponds to a non-UTI group, displaying the standardized mean on a logarithmic scale along with its 95&#x0025; confidence intervals (CIs). The diamond symbol represents the mean average of log<sub>e</sub>-transformed NGAL values. Upon applying anti-log transformation to revert NGAL values to their original scale in ng/ml, the calculated mean average (95&#x0025; CI) is 22.42 (9.97, 50.40) ng/ml. (<bold>B</bold>) Funnel plot of publication bias for non-UTI samples in pediatric studies. The horizontal axis is standardized log-NGAL and the vertical axis is standard error of log-NGAL. The diagonal lines represent the 95&#x0025; confidence limits of estimation.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g003.tif"/>
</fig>
</sec>
<sec id="s3d"><title>Quantitative analysis: UTI samples in pediatric studies</title>
<p>The forest plot shown in <xref ref-type="fig" rid="F4">Figure&#x00A0;4A</xref> summarizes the log transformed uNGAL value in each study for the UTI samples reported in the pediatric studies. 17 pediatric studies contributed 19 UTI groups of patients (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B42">42</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B57">57</xref>). Summarized mean and standard deviation were reported. The results suggested that the median uNGAL value is 118.85 (95&#x0025; CI of 43.07, 327.97) ng/ml in the UTI patient population. We did find statistically significant Cochran Q statistic 37.17 (18 DF), <italic>P</italic>&#x2009;&#x003D;&#x2009;0.005 and large <italic>I</italic><sup>2</sup> (59.3&#x0025;) indicating heterogeneous results reported from different studies. Details are shown in funnel plots (<xref ref-type="fig" rid="F4">Figure&#x00A0;4B</xref>).</p>
<fig id="F4" position="float"><label>Figure 4</label>
<caption><p>(<bold>A</bold>) forest plot of log<sub>e</sub>-transformed NGAL values for UTI samples in pediatric studies. Each row corresponds to a UTI group, displaying the standardized mean on a logarithmic scale along with its 95&#x0025; confidence intervals (CIs). The diamond symbol represents the mean average of log<sub>e</sub>-transformed NGAL values. Upon applying anti-log transformation to revert NGAL values to their original scale in ng/ml, the calculated mean average (95&#x0025; CI) is 119.10 (42.95, 327.01) ng/ml. (<bold>B</bold>) Funnel plot of publication bias for UTI samples in pediatric studies. The horizontal axis is standardized log-NGAL and the vertical axis is standard error of NGAL. The diagonal lines represent the 95&#x0025; confidence limits of estimation.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g004.tif"/>
</fig>
</sec>
<sec id="s3e"><title>Optimal cut-off point</title>
<p>The estimated area under the curve (AUC) is 0.99. We estimated that the cut-off point of 48.43&#x2005;ng/ml would optimize Youden Index with sensitivity of 96&#x0025; and specificity of 97&#x0025; (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B42">42</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>&#x2013;<xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B55">55</xref>, <xref ref-type="bibr" rid="B57">57</xref>).</p>
</sec>
<sec id="s3f"><title>Sensitivity analysis 1: inclusion of both pediatric and adult studies</title>
<p>8 adult studies (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B49">49</xref>, <xref ref-type="bibr" rid="B54">54</xref>, <xref ref-type="bibr" rid="B56">56</xref>, <xref ref-type="bibr" rid="B58">58</xref>, <xref ref-type="bibr" rid="B59">59</xref>) were added in the sensitivity analysis (<xref ref-type="fig" rid="F5">Figures&#x00A0;5A,B</xref>, <xref ref-type="fig" rid="F6">6A</xref>,<xref ref-type="fig" rid="F6">B</xref>). The median uNGAL value in the non-UTI patient population is 23.56 (95&#x0025; CI of 12.35, 44.93) ng/ml. The median uNGAL value in the UTI patient population is 113.73 (95&#x0025; CI of 56.13, 230.45) ng/ml. We estimated that the cut-off point of 50.31&#x2005;ng/ml would optimize Youden Index with sensitivity of 99&#x0025; and specificity of 99&#x0025; when both pediatric and adult studies were included.</p>
<fig id="F5" position="float"><label>Figure 5</label>
<caption><p>(<bold>A</bold>) forest plot of log<sub>e</sub>-transformed NGAL values for non-UTI samples in sensitivity analysis including both pediatric and adult studies. Each row corresponds to a non-UTI group, displaying the standardized mean on a logarithmic scale along with its 95&#x0025; confidence intervals (CIs). The diamond symbol represents the mean average of log<sub>e</sub>-transformed NGAL values. Upon applying anti-log transformation to revert NGAL values to their original scale in ng/ml, the calculated mean average (95&#x0025; CI) is 23.57 (12.30, 45.15) ng/ml. (<bold>B</bold>) Funnel plot of publication bias for non-UTI samples in sensitivity analysis including both pediatric and adult studies. The horizontal axis is standardized log-NGAL and the vertical axis is standard error of NGAL. The diagonal lines represent the 95&#x0025; confidence limits of estimation.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g005.tif"/>
</fig>
<fig id="F6" position="float"><label>Figure 6</label>
<caption><p>(<bold>A</bold>) forest plot of loge-transformed NGAL values for UTI samples in sensitivity analysis including both pediatric and adult studies. Each row corresponds to a UTI group, displaying the standardized mean on a logarithmic scale along with its 95&#x0025; confidence intervals (CIs). The diamond symbol represents the mean average of log<sub>e</sub>-transformed NGAL values. Upon applying anti-log transformation to revert NGAL values to their original scale in ng/ml, the calculated mean average (95&#x0025; CI) is 113.30 (56.26, 230.44) ng/ml. (<bold>B</bold>) Funnel plot of publication bias for UTI samples in sensitivity analysis including both pediatric and adult studies. The horizontal axis is standardized log-NGAL and the vertical axis is standard error of NGAL. The diagonal lines represent the 95&#x0025; confidence limits of estimation.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g006.tif"/>
</fig>
</sec>
<sec id="s3g"><title>Sensitivity analysis 2: excluding small UTI studies</title>
<p>Fifteen studies (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B45">45</xref>, <xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B51">51</xref>, <xref ref-type="bibr" rid="B53">53</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>) were included in the sensitivity analysis after excluding small UTI studies with sample size <italic>N</italic>&#x2009;&#x003C;&#x2009;50 (<xref ref-type="fig" rid="F7">Figures&#x00A0;7A,B</xref>). The Cochran Q statistic 8.5 (16 DF), <italic>P</italic>&#x2009;&#x003D;&#x2009;0.93 and <italic>I</italic><sup>2</sup>&#x2009;&#x003D;&#x2009;7.76&#x0025; indicating small heterogeneity. The median estimated uNGAL is 111.77 (95&#x0025; CI of 49.4, 252.7) ng/ml.</p>
<fig id="F7" position="float"><label>Figure 7</label>
<caption><p>(<bold>A</bold>) forest plot of log<sub>e</sub>-transformed NGAL values for UTI samples in sensitivity analysis excluding small UTI groups. Each row corresponds to a UTI group, displaying the standardized mean on a logarithmic scale along with its 95&#x0025; confidence intervals (CIs). The diamond symbol represents the mean average of log<sub>e</sub>-transformed NGAL values. Upon applying anti-log transformation to revert NGAL values to their original scale in ng/ml, the calculated mean average (95&#x0025; CI) is 112.17 (49.40, 252.14) ng/ml. (<bold>B</bold>) Funnel plot of publication bias for UTI samples in sensitivity analysis excluding small UTI groups. The horizontal axis is standardized log-NGAL and the vertical axis is standard error of NGAL. The diagonal lines represent the 95&#x0025; confidence limits of estimation.</p></caption>
<graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="fped-12-1368583-g007.tif"/>
</fig>
</sec>
<sec id="s3h"><title>Sensitivity analysis 3: including healthy control groups</title>
<p>Eight studies (<xref ref-type="bibr" rid="B38">38</xref>, <xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B52">52</xref>, <xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B58">58</xref>, <xref ref-type="bibr" rid="B59">59</xref>) with healthy control groups were added in the non-UTI analysis. The median uNGAL value in the non-UTI patient population is 19.56 (95&#x0025; CI of 10.94, 34.94) ng/ml. The Cochran Q statistic 18.6 (31 DF) and <italic>I</italic><sup>2</sup> of 0&#x0025; are statistically insignificant. No potential heterogeneous issue was detected.</p>
</sec>
<sec id="s3i"><title>Sensitivity analysis 4: excluding studies with high/unclear risk of bias</title>
<p>Twelve studies (<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B42">42</xref>, <xref ref-type="bibr" rid="B44">44</xref>, <xref ref-type="bibr" rid="B46">46</xref>&#x2013;<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B50">50</xref>, <xref ref-type="bibr" rid="B53">53</xref>, <xref ref-type="bibr" rid="B57">57</xref>&#x2013;<xref ref-type="bibr" rid="B59">59</xref>) were rated as having low risk of all four domains of bias and were included in analysis. In the non-UTI patient population, The Cochran Q statistic 5.9 (10 DF), <italic>P</italic>&#x2009;&#x003D;&#x2009;0.83, and <italic>I</italic><sup>2</sup> of 0.68&#x0025; are statistically insignificant. No potential heterogeneous issue was detected. The median uNGAL value in the non-UTI group is 24.42 (95&#x0025; CI of 10.23, 58.30) ng/ml. In the UTI patient population, the Cochran Q statistic 12.1 (12 DF), <italic>P</italic>&#x2009;&#x003D;&#x2009;0.44, and <italic>I</italic><sup>2</sup> of 30.2&#x0025; indicated moderate heterogeneous results reported from different studies. The median uNGAL value in the UTI patient population is 197.98 (95&#x0025; CI of 72.97, 537.17) ng/ml. We estimated that the cut-off point of 65.69&#x2005;ng/ml would optimize Youden Index with sensitivity of 98&#x0025; and specificity of 98&#x0025;.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion"><title>Discussion</title>
<p>The use of uNGAL as a diagnostic tool for UTI has been the subject of several studies in recent years. In this review, we aimed to estimate the distribution of uNGAL levels in patients with reported UTI symptoms, comparing samples with culture-confirmed UTI vs. those without UTI. Our meta-analysis found that uNGAL levels were significantly higher in samples with confirmed UTI compared to those without. Median uNGAL values are 22.41 (95&#x0025; CI of 9.94, 50.54) ng/ml in the non-UTI group vs. 118.85 (95&#x0025; CI of 43.07, 327.97) ng/ml in UTI group in the primary analysis of pediatric studies. We estimated the optimal cut-off point of 48.43&#x2005;ng/ml with high sensitivity (96&#x0025;) and specificity (97&#x0025;). Sensitivity analyses by including both pediatric and adult studies, by including healthy control in the non-UTI group, and by excluding studies with small sample sizes provided results consistent with the primary analysis. When both the 17 pediatric studies and 8 adult studies were analyzed, results were comparable to the primary pediatric analysis. The median uNGAL value in the non-UTI pediatric patient population is 23.56 (95&#x0025; CI of 12.35, 44.93) ng/ml. The median uNGAL value in the UTI pediatric patient population is 113.73 (95&#x0025; CI of 56.13, 230.45) ng/ml. In all patients, we estimated that the cut-off point of 50.31&#x2005;ng/ml would optimize Youden Index with sensitive (99&#x0025;) and specificity (99&#x0025;).</p>
<p>Overall, our results support the use of uNGAL as a potential biomarker for diagnosing UTI in both pediatric and adult populations. In a previous smaller meta-analysis of 12 published studies in children and adolescents, Abbasi et al. (<xref ref-type="bibr" rid="B9">9</xref>) compared means and standard deviations between UTI and non-UTI groups and summarized the findings using standardized mean difference. They suggested that 30&#x2013;39.9&#x2005;ng/ml can be used as optimal cut-off point, with sensitivity and specificity of 0.89 (95&#x0025; CI of 0.64, 0.97) and 0.89 (95&#x0025; CI of 0.71, 0.97) respectively, which is similar to our findings in this larger meta-analysis. Shaikh et al. (<xref ref-type="bibr" rid="B11">11</xref>) focused on accuracy values from 12 published studies and examined how accuracy varied with threshold. Recognizing that the distribution of uNGAL is highly skewed and subject to the limit of detections in different studies, our study applied the QE method to mitigate the issues. We first evaluated the distributions of uNGAL in the UTI and non-UTI samples, then estimated the optimal cut-off points for uNGAL based on the estimated distributions.</p>
<p>Our results are consistent with the current literature, including three studies that presented systematic reviews of smaller groups of publications, but without conducting quantitative meta-analysis. Shaikh et al. (<xref ref-type="bibr" rid="B11">11</xref>) compared the performance of uNGAL with the currently used leukocyte esterase (LE) test in diagnosing UTI in febrile children aged 0&#x2013;18 years. Their study included a review of 4 previously published studies and suggested that uNGAL offered a promising and more sensitive alternative to the LE test for diagnosing UTI. Martino et al. (<xref ref-type="bibr" rid="B12">12</xref>) conducted a systematic review of 4 published studies in an adult population and provided a summary of the results indicating encouraging performance of uNGAL. Horvath et al. (<xref ref-type="bibr" rid="B10">10</xref>) summarized 16 studies on uNGAL for predicting UTI in both pediatric and adult population. They suggested that use of uNGAL could improve the sensitivity and specificity of laboratory diagnosis of UTIs.</p>
<p>Pre-clinical studies have established the biological plausibility for the use of uNGAL as a UTI biomarker. In response to inflammation or injury, NGAL is expressed and released from activated neutrophils, as well as from several organs and tissues, especially kidney tubule cells. Within the urinary tract, NGAL plays an essential role in innate immunity and bacteriostasis via its profound iron-chelating properties (<xref ref-type="bibr" rid="B13">13</xref>). NGAL-deficient mice are highly susceptible to bacterial infections and die of sepsis when infected with uropathogenic <italic>E. coli</italic> (<xref ref-type="bibr" rid="B14">14</xref>). Furthermore, uNGAL is dramatically increased with gram-negative UTIs in several animal models (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B15">15</xref>). Earlier studies suggested that uNGAL in UTIs may be derived primarily from activated neutrophils in the kidney and urothelium, since a correlation between urinary WBC count and measured uNGAL concentrations was demonstrated (<xref ref-type="bibr" rid="B16">16</xref>). However, subsequent investigations have illustrated that the alpha-intercalated cells in the kidney collecting duct are the primary source of uNGAL in response to infection or injury (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). Depletion of neutrophils did not affect kidney NGAL expression in mice, and isolated cultured primary kidney tubule cells robustly upregulate NGAL in response to uropathogenic <italic>E. coli</italic> in the complete absence of neutrophils (<xref ref-type="bibr" rid="B17">17</xref>). In addition, specific ablation exclusively of alpha-intercalated cells suppressed uNGAL levels, and impaired bacterial clearance following transurethral inoculation of uropathogenic <italic>E. coli</italic> (<xref ref-type="bibr" rid="B18">18</xref>). Collectively, the pre-clinical data strongly support the utility of kidney-derived uNGAL as a biomarker of UTI, independent of neutrophil presence or activation.</p>
<p>The published literature has identified important advantages to the use of uNGAL as a UTI biomarker over other diagnostic methods. For example, Kim et al. studied 218 children with culture-positive UTI and showed that urine specific gravity did not affect the diagnostic performance of uNGAL, and that uNGAL consistently demonstrated higher AUCs compared to pyuria in both dilute and concentrated urine samples (<xref ref-type="bibr" rid="B55">55</xref>). In a prospective study of febrile children being evaluated for UTIs with paired catheterized and bagged urine samples, bagged sample uNGAL had lower quantitative specificities (73.8&#x0025;) than from catheterized samples (94.3&#x0025;), although the AUC for the positive diagnosis of UTI was comparable in paired catheterized and bagged urine samples, at 0.96 (95&#x0025; CI&#x2009;&#x003D;&#x2009;0.89&#x2013;1.00) and 0.93 (95&#x0025; CI&#x2009;&#x003D;&#x2009;0.87&#x2013;0.99) respectively (<xref ref-type="bibr" rid="B50">50</xref>). Therefore, while bagged specimens can be confounded by contamination issues in young children, the lower specificity for uNGAL in bagged vs. catheterized specimens reported in this study should be taken into consideration and is worthy of further characterization. In older children and adults, uNGAL can be reliably measured in voided urine samples, although one study found that both uNGAL levels and WBC counts were higher in initial-stream urine samples in comparison with midstream, leading to a recommendation that midstream urine sampling is desirable for uNGAL measurements independent of pyuria (<xref ref-type="bibr" rid="B60">60</xref>). In children with neurogenic bladders who are at high risk for UTIs, an elevated uNGAL reliably differentiated culture positive UTIs from either urinary tract colonization (<xref ref-type="bibr" rid="B44">44</xref>) or from asymptomatic bacteriuria (<xref ref-type="bibr" rid="B61">61</xref>), allowing in both instances to safely withhold unnecessary antibiotic treatment.</p>
<p>It is important to note that our review and meta-analysis had some limitations. Firstly, there was significant heterogeneity in the included studies in terms of study design, study population, sample size, and assay type. This heterogeneity may have influenced the accuracy of our meta-analysis results. Secondly, while we included studies from both pediatric and adult populations, most studies included were conducted in children. More research is needed to better establish the diagnostic value of uNGAL in age and/or gender specific populations. Third, the UTI and non-UTI samples were not necessarily matched by demographics. Future studies may wish to use the individual patient pooled data for better analyses adjusting for potential confounding bias. Fourth, we did not include studies that examined plasma NGAL for the diagnosis of UTI, due to the relatively few numbers of publications on that subject (<xref ref-type="bibr" rid="B36">36</xref>, <xref ref-type="bibr" rid="B46">46</xref>, <xref ref-type="bibr" rid="B62">62</xref>&#x2013;<xref ref-type="bibr" rid="B64">64</xref>). Fifth, Western blotting studies have revealed two forms of uNGAL in patients with UTI, including a monomeric (25&#x2005;kDa) forms produced primarily by the kidney tubule epithelial cells and a homodimeric (45&#x2005;kDa) form that emanates from activated neutrophils (<xref ref-type="bibr" rid="B65">65</xref>). Although the studies reported herein utilized sensitive ELISA or standard clinical immunoassays for uNGAL quantification, it is unclear if the assays preferentially detect one or both forms, which might affect their accuracy. Therefore, it is likely that the uNGAL detected in patients with UTI using ELISA or standardized laboratory platforms might represent both the kidney-specific monomeric 25&#x2005;kDa form as well as other homodimeric forms from activated neutrophils.</p>
<p>Finally, it should be acknowledged that uNGAL has also been used as a clinical diagnostic biomarker in other kidney states, especially in AKI (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B28">28</xref>). Indeed, in 2023, the FDA approved uNGAL as a clinical laboratory test (ProNephro AKI<sup>&#x2122;</sup>) for use in critically ill patients aged 3 months through 21 years as an aid in the risk assessment for moderate or severe AKI within 48&#x2013;72&#x2005;h of ICU admission (<xref ref-type="bibr" rid="B66">66</xref>). However, the range of uNGAL concentrations and cut-off points reported in subjects with AKI has generally been much higher than the 48.43&#x2005;ng/ml reported herein for UTIs. For example, an initial meta-analysis of 19 studies that measured uNGAL using ELISA techniques identified a cut-off point range of 100&#x2013;270&#x2005;ng/ml for optimal sensitivity and specificity to predict AKI (<xref ref-type="bibr" rid="B22">22</xref>). A subsequent evaluation of 58 published studies suggested an NGAL cut-off point of &#x003E;150&#x2005;ng/ml, measured on a standardized clinical laboratory platform, as diagnostic for AKI (<xref ref-type="bibr" rid="B27">27</xref>). This summary of studies reporting on uNGAL cut-off points concentrations for AKI found a range from &#x2265;105 to &#x2265;350&#x2005;ng/ml (<xref ref-type="bibr" rid="B27">27</xref>). In a recent meta-analysis of individual study data from 30 publications reporting on uNGAL measurements for AKI prediction using clinical laboratory platforms, a cut-off points concentration of 105&#x2005;ng/ml yielded the optimal combination of sensitivity and specificity, and a cut-off point of &#x003E;580&#x2005;ng/ml provided 95&#x0025; specificity (<xref ref-type="bibr" rid="B28">28</xref>). Nevertheless, clinicians should be aware of some overlap between uNGAL values between the two conditions (UTI and AKI) and exert appropriate caution when interpreting patient-specific results.</p>
<p>In conclusion, our results confirm that uNGAL can accurately distinguish patients with and without confirmed UTI among symptomatic patients with no AKI, CKD, or known congenital anatomic anomalies of the kidney or urinary tract. Future prospective studies to confirm the identified uNGAL cut-off point of 48.43&#x2005;ng/ml for early UTI diagnosis are warranted.</p>
</sec>
</body>
<back>
<sec id="s5" sec-type="data-availability"><title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s9"><bold>Supplementary Material</bold></xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s6" sec-type="author-contributions"><title>Author contributions</title>
<p>YZ: Data curation, Formal Analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. CC: Data curation, Formal Analysis, Investigation, Methodology, Resources, Software, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. MM: Data curation, Formal Analysis, Investigation, Methodology, Validation, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. BH: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. PD: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec id="s7" sec-type="funding-information"><title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article.</p>
<p>PD was supported by the NIH/NIDDK Center of Excellence in Nephrology (P50DK096418). BH was supported by the Center for Clinical and Translational Science and Training, which is supported by the NIH National Center for Advancing Translational Sciences (5UL1TR001425-03).</p>
</sec>
<ack><title>Acknowledgments</title>
<p>PD was supported by the NIH/NIDDK Center of Excellence in Nephrology (P50DK096418). BH was supported by the Center for Clinical and Translational Science and Training, which is supported by the NIH National Center for Advancing Translational Sciences (5UL1TR001425-03). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.</p>
</ack>
<sec id="s8" sec-type="COI-statement"><title>Conflict of interest</title>
<p>PD is a co-inventor on patents submitted for the use of NGAL as a biomarker for acute kidney injury.</p>
<p>The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="disclaimer"><title>Publisher&#x0027;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s9" sec-type="supplementary-material"><title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fped.2024.1368583/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fped.2024.1368583/full&#x0023;supplementary-material</ext-link></p>
<supplementary-material id="SD1" content-type="local-data">
<media mimetype="application" mime-subtype="pdf" xlink:href="Table1.pdf"/></supplementary-material>
</sec>
<ref-list><title>References</title>
<ref id="B1"><label>1.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mattoo</surname><given-names>TK</given-names></name><name><surname>Shaikh</surname><given-names>N</given-names></name><name><surname>Nelson</surname><given-names>CP</given-names></name></person-group>. <article-title>Contemporary management of urinary tract infection in children</article-title>. <source>Pediatrics</source>. (<year>2021</year>) <volume>147</volume>(<issue>2</issue>):<fpage>e2020012138</fpage>. <pub-id pub-id-type="doi">10.1542/peds.2020-012138</pub-id><pub-id pub-id-type="pmid">33479164</pub-id></citation></ref>
<ref id="B2"><label>2.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shaikh</surname><given-names>N</given-names></name><name><surname>Mattoo</surname><given-names>TK</given-names></name><name><surname>Keren</surname><given-names>R</given-names></name><name><surname>Ivanova</surname><given-names>A</given-names></name><name><surname>Cui</surname><given-names>G</given-names></name><name><surname>Moxey-Mims</surname><given-names>M</given-names></name><etal/></person-group> <article-title>Early antibiotic treatment for pediatric febrile urinary tract infection and renal scarring</article-title>. <source>JAMA Pediatr</source>. (<year>2016</year>) <volume>170</volume>(<issue>9</issue>):<fpage>848</fpage>&#x2013;<lpage>854</lpage>. <pub-id pub-id-type="doi">10.1001/jamapediatrics.2016.1181</pub-id><pub-id pub-id-type="pmid">27455161</pub-id></citation></ref>
<ref id="B3"><label>3.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Williams</surname><given-names>GJ</given-names></name><name><surname>Macaskill</surname><given-names>P</given-names></name><name><surname>Chan</surname><given-names>SF</given-names></name><name><surname>Turner</surname><given-names>R</given-names></name><name><surname>Hodson</surname><given-names>E</given-names></name><name><surname>Craig</surname><given-names>J</given-names></name></person-group>. <article-title>Absolute and relative accuracy of rapid urine tests for urinary tract infection in children: a meta-analysis</article-title>. <source>Lancet Infect Dis</source>. (<year>2010</year>) <volume>10</volume>(<issue>4</issue>):<fpage>240</fpage>&#x2013;<lpage>50</lpage>. <pub-id pub-id-type="doi">10.1016/S1473-3099(10)70031-1</pub-id><pub-id pub-id-type="pmid">20334847</pub-id></citation></ref>
<ref id="B4"><label>4.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Watson</surname><given-names>JR</given-names></name><name><surname>S&#x00E1;nchez</surname><given-names>PJ</given-names></name><name><surname>Spencer</surname><given-names>JD</given-names></name><name><surname>Daniel</surname><given-names>C</given-names></name><name><surname>David</surname><given-names>H</given-names></name></person-group>. <article-title>Urinary tract infection and antimicrobial stewardship in the emergency department</article-title>. <source>Pediatr Emerg Care</source>. (<year>2018</year>) <volume>34</volume>(<issue>2</issue>):<fpage>93</fpage>&#x2013;<lpage>5</lpage>. <pub-id pub-id-type="doi">10.1097/PEC.0000000000000688</pub-id><pub-id pub-id-type="pmid">26855344</pub-id></citation></ref>
<ref id="B5"><label>5.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Gadalla</surname><given-names>AAH</given-names></name><name><surname>Friberg</surname><given-names>IM</given-names></name><name><surname>Kift-Morgan</surname><given-names>A</given-names></name><name><surname>Zhang</surname><given-names>JJ</given-names></name><name><surname>Eberl</surname><given-names>M</given-names></name><name><surname>Toley</surname><given-names>N</given-names></name><etal/></person-group> <article-title>Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms</article-title>. <source>Sci Rep</source>. (<year>2019</year>) <volume>9</volume>(<issue>1</issue>):<fpage>19694</fpage>. <pub-id pub-id-type="doi">10.1038/s41598-019-55523-x</pub-id><pub-id pub-id-type="pmid">31873085</pub-id></citation></ref>
<ref id="B6"><label>6.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mohkam</surname><given-names>M</given-names></name></person-group>. <article-title>Novel urinary biomarkers for diagnosis of acute pyelonephritis in children</article-title>. <source>Iran J Kidney Dis</source>. (<year>2020</year>) <volume>14</volume>(<issue>1</issue>):<fpage>1</fpage>&#x2013;<lpage>7</lpage>.<pub-id pub-id-type="pmid">32156834</pub-id></citation></ref>
<ref id="B7"><label>7.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Watson</surname><given-names>JR</given-names></name><name><surname>Hains</surname><given-names>DS</given-names></name><name><surname>Cohen</surname><given-names>DM</given-names></name><name><surname>Spencer</surname><given-names>J</given-names></name><name><surname>Kline</surname><given-names>J</given-names></name><name><surname>Yin</surname><given-names>H</given-names></name><etal/></person-group> <article-title>Evaluation of novel urinary tract infection biomarkers in children</article-title>. <source>Pediatr Res</source>. (<year>2016</year>) <volume>79</volume>(<issue>6</issue>):<fpage>934</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1038/pr.2016.33</pub-id><pub-id pub-id-type="pmid">26885759</pub-id></citation></ref>
<ref id="B8"><label>8.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Forster</surname><given-names>CS</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name></person-group>. <article-title>Neutrophil gelatinase-associated lipocalin: utility in urologic conditions</article-title>. <source>Pediatr Nephrol</source>. (<year>2017</year>) <volume>32</volume>(<issue>3</issue>):<fpage>377</fpage>&#x2013;<lpage>81</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-016-3540-0</pub-id><pub-id pub-id-type="pmid">27785626</pub-id></citation></ref>
<ref id="B9"><label>9.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Abbasi</surname><given-names>A</given-names></name><name><surname>Nabizadeh</surname><given-names>F</given-names></name><name><surname>Gardeh</surname><given-names>M</given-names></name><name><surname>Ali</surname><given-names>K</given-names></name><name><surname>Yousefifard</surname><given-names>M</given-names></name><name><surname>Hosseini</surname><given-names>M</given-names></name></person-group>. <article-title>Discriminatory precision of neutrophil gelatinase-associated lipocalin in detection of urinary tract infection in children: a systematic review and meta-analysis</article-title>. <source>Arch Acad Emerg Med</source>. (<year>2020</year>) <volume>8</volume>(<issue>1</issue>):<fpage>e56</fpage>.<pub-id pub-id-type="pmid">32440667</pub-id></citation></ref>
<ref id="B10"><label>10.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Horv&#x00E1;th</surname><given-names>J</given-names></name><name><surname>Wullt</surname><given-names>B</given-names></name><name><surname>Naber</surname><given-names>KG</given-names></name><name><surname>K&#x00F6;ves</surname><given-names>B</given-names></name></person-group>. <article-title>Biomarkers in urinary tract infections&#x2014;which ones are suitable for diagnostics and follow-up?</article-title> <source>GMS Infect Dis</source>. (<year>2020</year>) <volume>8</volume>:<fpage>Doc24</fpage>. <pub-id pub-id-type="doi">10.3205/id000068</pub-id></citation></ref>
<ref id="B11"><label>11.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shaikh</surname><given-names>K</given-names></name><name><surname>Rajakumar</surname><given-names>V</given-names></name><name><surname>Osio</surname><given-names>V</given-names></name><name><surname>Shaikh</surname><given-names>N</given-names></name></person-group>. <article-title>Neutrophil gelatinase-associated lipocalin for urinary tract infection and pyelonephritis: a systematic review</article-title>. <source>Pediatr Nephrol</source>. (<year>2021</year>) <volume>36</volume>:<fpage>1481</fpage>&#x2013;<lpage>1487</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-020-04854-3</pub-id><pub-id pub-id-type="pmid">33389090</pub-id></citation></ref>
<ref id="B12"><label>12.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Martino</surname><given-names>FK</given-names></name><name><surname>Novara</surname><given-names>G</given-names></name></person-group>. <article-title>Asymptomatic bacteriuria or urinary tract infection? New and old biomarkers</article-title>. <source>Int J Trans Med</source>. (<year>2022</year>) <volume>2</volume>(<issue>1</issue>):<fpage>52</fpage>&#x2013;<lpage>65</lpage>. <pub-id pub-id-type="doi">10.3390/ijtm2010006</pub-id></citation></ref>
<ref id="B13"><label>13.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Schmidt-Ott</surname><given-names>KM</given-names></name><name><surname>Mori</surname><given-names>K</given-names></name><name><surname>Li</surname><given-names>JY</given-names></name><name><surname>Kalandadze</surname><given-names>A</given-names></name><name><surname>Cohen</surname><given-names>DJ</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name><etal/></person-group> <article-title>Dual action of neutrophil gelatinase-associated lipocalin</article-title>. <source>J Am Soc Nephrol</source>. (<year>2007</year>) <volume>18</volume>(<issue>2</issue>):<fpage>407</fpage>&#x2013;<lpage>13</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.2006080882</pub-id><pub-id pub-id-type="pmid">17229907</pub-id></citation></ref>
<ref id="B14"><label>14.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Berger</surname><given-names>T</given-names></name><name><surname>Togawa</surname><given-names>A</given-names></name><name><surname>Duncan</surname><given-names>GS</given-names></name><name><surname>Elia</surname><given-names>AJ</given-names></name><name><surname>You-ten</surname><given-names>A</given-names></name><name><surname>Wakeham</surname><given-names>A</given-names></name><etal/></person-group> <article-title>Lipocalin 2-deficient mice exhibit increased sensitivity to Escherichia coli infection but not to ischemia-reperfusion injury</article-title>. <source>Proc Natl Acad Sci U S A</source>. (<year>2006</year>) <volume>103</volume>(<issue>6</issue>):<fpage>1834</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1073/pnas.0510847103</pub-id><pub-id pub-id-type="pmid">16446425</pub-id></citation></ref>
<ref id="B15"><label>15.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Ichino</surname><given-names>M</given-names></name><name><surname>Kuroyanagi</surname><given-names>Y</given-names></name><name><surname>Kusaka</surname><given-names>M</given-names></name><name><surname>Mori</surname><given-names>T</given-names></name><name><surname>Ishikawa</surname><given-names>K</given-names></name><name><surname>Shiroki</surname><given-names>R</given-names></name><etal/></person-group> <article-title>Increased urinary neutrophil gelatinase associated lipocalin levels in a rat model of upper urinary tract infection</article-title>. <source>J Urol</source>. (<year>2009</year>) <volume>181</volume>(<issue>5</issue>):<fpage>2326</fpage>&#x2013;<lpage>31</lpage>. <pub-id pub-id-type="doi">10.1016/j.juro.2009.01.010</pub-id><pub-id pub-id-type="pmid">19303090</pub-id></citation></ref>
<ref id="B16"><label>16.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Decavele</surname><given-names>AS</given-names></name><name><surname>Dhondt</surname><given-names>L</given-names></name><name><surname>De Buyzere</surname><given-names>ML</given-names></name><name><surname>Delanghe</surname><given-names>JR</given-names></name></person-group>. <article-title>Increased urinary neutrophil gelatinase associated lipocalin in urinary tract infections and leukocyturia</article-title>. <source>Clin Chem Lab Med</source>. (<year>2011</year>) <volume>49</volume>(<issue>6</issue>):<fpage>999</fpage>&#x2013;<lpage>1003</lpage>. <pub-id pub-id-type="doi">10.1515/CCLM.2011.156</pub-id><pub-id pub-id-type="pmid">21391867</pub-id></citation></ref>
<ref id="B17"><label>17.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Paragas</surname><given-names>N</given-names></name><name><surname>Qiu</surname><given-names>A</given-names></name><name><surname>Zhang</surname><given-names>Q</given-names></name><name><surname>Samstein</surname><given-names>B</given-names></name><name><surname>Deng</surname><given-names>SX</given-names></name><name><surname>Schmidt-Ott</surname><given-names>K</given-names></name><etal/></person-group> <article-title>The Ngal reporter mouse detects the response of the kidney to injury in real time</article-title>. <source>Nat Med</source>. (<year>2011</year>) <volume>17</volume>(<issue>2</issue>):<fpage>216</fpage>&#x2013;<lpage>22</lpage>. <pub-id pub-id-type="doi">10.1038/nm.2290</pub-id><pub-id pub-id-type="pmid">21240264</pub-id></citation></ref>
<ref id="B18"><label>18.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Paragas</surname><given-names>N</given-names></name><name><surname>Kulkarni</surname><given-names>R</given-names></name><name><surname>Werth</surname><given-names>M</given-names></name><name><surname>Schmidt-Ott</surname><given-names>K</given-names></name><name><surname>Forster</surname><given-names>C</given-names></name><name><surname>Deng</surname><given-names>R</given-names></name><etal/></person-group> <article-title>&#x03B1;-Intercalated cells defend the urinary system from bacterial infection</article-title>. <source>J Clin Invest</source>. (<year>2014</year>) <volume>124</volume>(<issue>7</issue>):<fpage>2963</fpage>&#x2013;<lpage>76</lpage>. <pub-id pub-id-type="doi">10.1172/JCI71630</pub-id><pub-id pub-id-type="pmid">24937428</pub-id></citation></ref>
<ref id="B19"><label>19.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mishra</surname><given-names>J</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><name><surname>Prada</surname><given-names>A</given-names></name><name><surname>Mitsnefes</surname><given-names>M</given-names></name><name><surname>Zahedi</surname><given-names>K</given-names></name><name><surname>Yang</surname><given-names>J</given-names></name><etal/></person-group> <article-title>Identification of neutrophil gelatinase-associated lipocalin as a novel early urinary biomarker for ischemic renal injury</article-title>. <source>J Am Soc Nephrol</source>. (<year>2003</year>) <volume>14</volume>(<issue>10</issue>):<fpage>2534</fpage>&#x2013;<lpage>43</lpage>. <pub-id pub-id-type="doi">10.1097/01.ASN.0000088027.54400.C6</pub-id><pub-id pub-id-type="pmid">14514731</pub-id></citation></ref>
<ref id="B20"><label>20.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Mishra</surname><given-names>J</given-names></name><name><surname>Dent</surname><given-names>C</given-names></name><name><surname>Tarabishi</surname><given-names>R</given-names></name><name><surname>Mitsnefes</surname><given-names>M</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><name><surname>Kelly</surname><given-names>C</given-names></name><etal/></person-group> <article-title>Neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker for acute renal injury after cardiac surgery</article-title>. <source>Lancet</source>. (<year>2005</year>) <volume>365</volume>(<issue>9466</issue>):<fpage>1231</fpage>&#x2013;<lpage>8</lpage>. <pub-id pub-id-type="doi">10.1016/S0140-6736(05)74811-X</pub-id><pub-id pub-id-type="pmid">15811456</pub-id></citation></ref>
<ref id="B21"><label>21.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Bennett</surname><given-names>M</given-names></name><name><surname>Dent</surname><given-names>CL</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><name><surname>Sudha</surname><given-names>D</given-names></name><name><surname>Frank</surname><given-names>G</given-names></name><name><surname>Workman</surname><given-names>F</given-names></name><etal/></person-group> <article-title>Urine NGAL predicts severity of acute kidney injury after cardiac surgery: a prospective study</article-title>. <source>Clin J Am Soc Nephrol</source>. (<year>2008</year>) <volume>3</volume>(<issue>3</issue>):<fpage>665</fpage>&#x2013;<lpage>73</lpage>. <pub-id pub-id-type="doi">10.2215/CJN.04010907</pub-id><pub-id pub-id-type="pmid">18337554</pub-id></citation></ref>
<ref id="B22"><label>22.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Haase</surname><given-names>M</given-names></name><name><surname>Bellomo</surname><given-names>R</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name><name><surname>Schlattmann</surname><given-names>P</given-names></name><name><surname>Haase-Fielitz</surname><given-names>A</given-names></name></person-group>. <article-title>Accuracy of neutrophil gelatinase-associated lipocalin (NGAL) in diagnosis and prognosis in acute kidney injury: a systematic review and meta-analysis</article-title>. <source>Am J Kidney Dis</source>. (<year>2009</year>) <volume>54</volume>(<issue>6</issue>):<fpage>1012</fpage>&#x2013;<lpage>24</lpage>. <pub-id pub-id-type="doi">10.1053/j.ajkd.2009.07.020</pub-id><pub-id pub-id-type="pmid">19850388</pub-id></citation></ref>
<ref id="B23"><label>23.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Krawczeski</surname><given-names>CD</given-names></name><name><surname>Woo</surname><given-names>JG</given-names></name><name><surname>Wang</surname><given-names>Y</given-names></name><name><surname>Bennett</surname><given-names>M</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name></person-group>. <article-title>Neutrophil gelatinase-associated lipocalin concentrations predict development of acute kidney injury in neonates and children after cardiopulmonary bypass</article-title>. <source>J Pediatr</source>. (<year>2011</year>) <volume>158</volume>(<issue>6</issue>):<fpage>1009</fpage>&#x2013;<lpage>1015.e1</lpage>. <pub-id pub-id-type="doi">10.1016/j.jpeds.2010.12.057</pub-id><pub-id pub-id-type="pmid">21300375</pub-id></citation></ref>
<ref id="B24"><label>24.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Haase</surname><given-names>M</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name><name><surname>Haase-Fielitz</surname><given-names>A</given-names></name><name><surname>Bellomo</surname><given-names>R</given-names></name><name><surname>Cruz</surname><given-names>DN</given-names></name><name><surname>Wagener</surname><given-names>G</given-names></name><etal/></person-group> <article-title>The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: a multicenter pooled analysis of prospective studies</article-title>. <source>J Am Coll Cardiol</source>. (<year>2011</year>) <volume>57</volume>(<issue>17</issue>):<fpage>1752</fpage>&#x2013;<lpage>61</lpage>. <pub-id pub-id-type="doi">10.1016/j.jacc.2010.11.051</pub-id><pub-id pub-id-type="pmid">21511111</pub-id></citation></ref>
<ref id="B25"><label>25.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Krawczeski</surname><given-names>CD</given-names></name><name><surname>Goldstein</surname><given-names>SL</given-names></name><name><surname>Woo</surname><given-names>JG</given-names></name><name><surname>Wang</surname><given-names>Y</given-names></name><name><surname>Piyaphanee</surname><given-names>N</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><etal/></person-group> <article-title>Temporal relationship and predictive value of urinary acute kidney injury biomarkers after pediatric cardiopulmonary bypass</article-title>. <source>J Am Coll Cardiol</source>. (<year>2011</year>) <volume>58</volume>(<issue>22</issue>):<fpage>2301</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1016/j.jacc.2011.08.017</pub-id><pub-id pub-id-type="pmid">22093507</pub-id></citation></ref>
<ref id="B26"><label>26.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Parikh</surname><given-names>CR</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name><name><surname>Zappitelli</surname><given-names>M</given-names></name><name><surname>Thiessen-Philbrook</surname><given-names>H</given-names></name><name><surname>Li</surname><given-names>S</given-names></name><name><surname>Kim</surname><given-names>RW</given-names></name><etal/></person-group> <article-title>Postoperative biomarkers predict acute kidney injury and poor outcomes after pediatric cardiac surgery</article-title>. <source>J Am Soc Nephrol</source>. (<year>2011</year>) <volume>22</volume>(<issue>9</issue>):<fpage>1737</fpage>&#x2013;<lpage>47</lpage>. <pub-id pub-id-type="doi">10.1681/ASN.2010111163</pub-id><pub-id pub-id-type="pmid">21836147</pub-id></citation></ref>
<ref id="B27"><label>27.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Haase-Fielitz</surname><given-names>A</given-names></name><name><surname>Haase</surname><given-names>M</given-names></name><name><surname>Devarajan</surname><given-names>P</given-names></name></person-group>. <article-title>Neutrophil gelatinase-associated lipocalin as a biomarker of acute kidney injury: a critical evaluation of current status</article-title>. <source>Ann Clin Biochem</source>. (<year>2014</year>) <volume>51</volume>(<issue>Pt 3</issue>):<fpage>335</fpage>&#x2013;<lpage>51</lpage>. <pub-id pub-id-type="doi">10.1177/0004563214521795</pub-id><pub-id pub-id-type="pmid">24518531</pub-id></citation></ref>
<ref id="B28"><label>28.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Albert</surname><given-names>C</given-names></name><name><surname>Zapf</surname><given-names>A</given-names></name><name><surname>Haase</surname><given-names>M</given-names></name><name><surname>Rover</surname><given-names>C</given-names></name><name><surname>Pickering</surname><given-names>J</given-names></name><name><surname>Albert</surname><given-names>A</given-names></name><etal/></person-group> <article-title>Neutrophil gelatinase-associated lipocalin measured on clinical laboratory platforms for the prediction of acute kidney injury and the associated need for dialysis therapy: a systematic review and meta-analysis</article-title>. <source>Am J Kidney Dis</source>. (<year>2020</year>) <volume>76</volume>(<issue>6</issue>):<fpage>826</fpage>&#x2013;<lpage>841.e1</lpage>. <pub-id pub-id-type="doi">10.1053/j.ajkd.2020.05.015</pub-id><pub-id pub-id-type="pmid">32679151</pub-id></citation></ref>
<ref id="B29"><label>29.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Stoup</surname><given-names>DF</given-names></name><name><surname>Berlin</surname><given-names>JA</given-names></name><name><surname>Morton</surname><given-names>SC</given-names></name><name><surname>Olkin</surname><given-names>I</given-names></name><name><surname>Williamson</surname><given-names>D</given-names></name><name><surname>Rennie</surname><given-names>D</given-names></name><etal/></person-group> <article-title>Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group</article-title>. <source>JAMA</source>. (<year>2000</year>) <volume>283</volume>(<issue>15</issue>):<fpage>2008</fpage>&#x2013;<lpage>12</lpage>. <pub-id pub-id-type="doi">10.1001/jama.283.15.2008</pub-id><pub-id pub-id-type="pmid">10789670</pub-id></citation></ref>
<ref id="B30"><label>30.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Whiting</surname><given-names>PF</given-names></name><name><surname>Rutjes</surname><given-names>AW</given-names></name><name><surname>Westwood</surname><given-names>ME</given-names></name><name><surname>Mallett</surname><given-names>S</given-names></name><name><surname>Deeks</surname><given-names>JJ</given-names></name><name><surname>Reitsma</surname><given-names>JB</given-names></name><etal/></person-group> <article-title>QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies</article-title>. <source>Ann Intern Med</source>. (<year>2011</year>) <volume>155</volume>(<issue>8</issue>):<fpage>529</fpage>&#x2013;<lpage>36</lpage>. <pub-id pub-id-type="doi">10.7326/0003-4819-155-8-201110180-00009</pub-id><pub-id pub-id-type="pmid">22007046</pub-id></citation></ref>
<ref id="B31"><label>31.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>McGrath</surname><given-names>S</given-names></name><name><surname>Sohn</surname><given-names>H</given-names></name><name><surname>Steele</surname><given-names>R</given-names></name><name><surname>Benedetti</surname><given-names>A</given-names></name></person-group>. <article-title>Meta-analysis of the difference of medians</article-title>. <source>Biom J</source>. (<year>2020</year>) <volume>62</volume>:<fpage>69</fpage>&#x2013;<lpage>98</lpage>. <pub-id pub-id-type="doi">10.1002/bimj.201900036</pub-id><pub-id pub-id-type="pmid">31553488</pub-id></citation></ref>
<ref id="B32"><label>32.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Becker</surname><given-names>S</given-names></name><name><surname>Lang</surname><given-names>H</given-names></name><name><surname>Vollmer Barbosa</surname><given-names>C</given-names></name><name><surname>Tian</surname><given-names>Z</given-names></name><name><surname>Melk</surname><given-names>A</given-names></name><name><surname>Schmidt</surname><given-names>BMW</given-names></name></person-group>. <article-title>Efficacy of CytoSorb&#x00AE;: a systematic review and meta-analysis</article-title>. <source>Crit Care</source>. (<year>2023</year>) <volume>27</volume>(<issue>1</issue>):<fpage>215</fpage>. <pub-id pub-id-type="doi">10.1186/s13054-023-04492-9</pub-id><pub-id pub-id-type="pmid">37259160</pub-id></citation></ref>
<ref id="B33"><label>33.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Daver</surname><given-names>NG</given-names></name><name><surname>Iqbal</surname><given-names>S</given-names></name><name><surname>Renard</surname><given-names>C</given-names></name><name><surname>Chan</surname><given-names>RJ</given-names></name><name><surname>Hasegawa</surname><given-names>K</given-names></name><name><surname>Hu</surname><given-names>H</given-names></name><etal/></person-group> <article-title>Treatment outcomes for newly diagnosed, treatment-na&#x00EF;ve TP53-mutated acute myeloid leukemia: a systematic review and meta-analysis</article-title>. <source>J Hematol Oncol</source>. (<year>2023</year>) <volume>16</volume>(<issue>1</issue>):<fpage>19</fpage>. <pub-id pub-id-type="doi">10.1186/s13045-023-01417-5</pub-id><pub-id pub-id-type="pmid">36879351</pub-id></citation></ref>
<ref id="B34"><label>34.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Laratta</surname><given-names>CR</given-names></name><name><surname>Moore</surname><given-names>LE</given-names></name><name><surname>Jen</surname><given-names>R</given-names></name><name><surname>Campbell</surname><given-names>SM</given-names></name><name><surname>MacLean</surname><given-names>JE</given-names></name><name><surname>Pendharkar</surname><given-names>SR</given-names></name><etal/></person-group> <article-title>Acceptance of and adherence with long-term positive airway pressure treatment in adults with chronic obstructive pulmonary disease: a systematic review protocol</article-title>. <source>PLoS One</source>. (<year>2023</year>) <volume>18</volume>(<issue>7</issue>):<fpage>e0287887</fpage>. <pub-id pub-id-type="doi">10.1371/journal.pone.0287887</pub-id><pub-id pub-id-type="pmid">37399211</pub-id></citation></ref>
<ref id="B35"><label>35.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Perkins</surname><given-names>NJ</given-names></name><name><surname>Schisterman</surname><given-names>EF</given-names></name></person-group>. <article-title>The Youden index and the optimal cut-point corrected for measurement error</article-title>. <source>Biom J</source>. (<year>2005</year>) <volume>47</volume>(<issue>4</issue>):<fpage>428</fpage>&#x2013;<lpage>41</lpage>. <pub-id pub-id-type="doi">10.1002/bimj.200410133</pub-id><pub-id pub-id-type="pmid">16161802</pub-id></citation></ref>
<ref id="B36"><label>36.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Petrovic</surname><given-names>S</given-names></name><name><surname>Bogavac-Stanojevic</surname><given-names>N</given-names></name><name><surname>Peco-Antic</surname><given-names>A</given-names></name><name><surname>Ivanisevic</surname><given-names>I</given-names></name><name><surname>Kotur-Stevuljevic</surname><given-names>J</given-names></name><name><surname>Paripovic</surname><given-names>D</given-names></name><etal/></person-group> <article-title>Clinical application neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 as indicators of inflammation persistence and acute kidney injury in children with urinary tract infection</article-title>. <source>Biomed Res Int</source>. (<year>2013</year>) <volume>2013</volume>:<fpage>947157</fpage>. <pub-id pub-id-type="doi">10.1155/2013/947157</pub-id><pub-id pub-id-type="pmid">23936859</pub-id></citation></ref>
<ref id="B37"><label>37.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>BH</given-names></name><name><surname>Yu</surname><given-names>N</given-names></name><name><surname>Kim</surname><given-names>HR</given-names></name><name><surname>Yun</surname><given-names>KW</given-names></name><name><surname>Lim</surname><given-names>IS</given-names></name><name><surname>Kim</surname><given-names>TH</given-names></name><etal/></person-group> <article-title>Evaluation of the optimal neutrophil gelatinase-associated lipocalin value as a screening biomarker for urinary tract infections in children</article-title>. <source>Ann Lab Med</source>. (<year>2014</year>) <volume>34</volume>(<issue>5</issue>):<fpage>354</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.3343/alm.2014.34.5.354</pub-id><pub-id pub-id-type="pmid">25187887</pub-id></citation></ref>
<ref id="B38"><label>38.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Urbschat</surname><given-names>A</given-names></name><name><surname>Oberm&#x00FC;ller</surname><given-names>N</given-names></name><name><surname>Paulus</surname><given-names>P</given-names></name><name><surname>Reissig</surname><given-names>M</given-names></name><name><surname>Hadji</surname><given-names>P</given-names></name><name><surname>Hofmann</surname><given-names>R</given-names></name><etal/></person-group> <article-title>Upper and lower urinary tract infections can be detected early but not be discriminated by urinary NGAL in adults</article-title>. <source>Int Urol Nephrol</source>. (<year>2014</year>) <volume>46</volume>(<issue>12</issue>):<fpage>2243</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1007/s11255-014-0831-x</pub-id><pub-id pub-id-type="pmid">25218613</pub-id></citation></ref>
<ref id="B39"><label>39.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lee</surname><given-names>HE</given-names></name><name><surname>Kim</surname><given-names>DK</given-names></name><name><surname>Kang</surname><given-names>HK</given-names></name><name><surname>Park</surname><given-names>K</given-names></name></person-group>. <article-title>The diagnosis of febrile urinary tract infection in children may be facilitated by urinary biomarkers</article-title>. <source>Pediatr Nephrol</source>. (<year>2015</year>) <volume>30</volume>(<issue>1</issue>):<fpage>123</fpage>&#x2013;<lpage>30</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-014-2905-5</pub-id><pub-id pub-id-type="pmid">25127917</pub-id></citation></ref>
<ref id="B40"><label>40.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Nickavar</surname><given-names>A</given-names></name><name><surname>Safaeian</surname><given-names>B</given-names></name><name><surname>Valavi</surname><given-names>E</given-names></name><name><surname>Moradpour</surname><given-names>F</given-names></name></person-group>. <article-title>Validity of neutrophil gelatinase associated lipocaline as a biomarker for diagnosis of children with acute pyelonephritis</article-title>. <source>Urol J</source>. (<year>2016</year>) <volume>13</volume>(<issue>5</issue>):<fpage>2860</fpage>&#x2013;<lpage>3</lpage>.<pub-id pub-id-type="pmid">27734430</pub-id></citation></ref>
<ref id="B41"><label>41.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Price</surname><given-names>JR</given-names></name><name><surname>Guran</surname><given-names>L</given-names></name><name><surname>Lim</surname><given-names>JY</given-names></name><name><surname>Megli</surname><given-names>CJ</given-names></name><name><surname>Clark</surname><given-names>AL</given-names></name><name><surname>Edwards</surname><given-names>SR</given-names></name><etal/></person-group> <article-title>Neutrophil gelatinase-associated lipocalin biomarker and urinary tract infections: a diagnostic case-control study (NUTI study)</article-title>. <source>Female Pelvic Med Reconstr Surg</source>. (<year>2017</year>) <volume>23</volume>(<issue>2</issue>):<fpage>101</fpage>&#x2013;<lpage>7</lpage>. <pub-id pub-id-type="doi">10.1097/SPV.0000000000000366</pub-id><pub-id pub-id-type="pmid">28106649</pub-id></citation></ref>
<ref id="B42"><label>42.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lubell</surname><given-names>TR</given-names></name><name><surname>Barasch</surname><given-names>JM</given-names></name><name><surname>Xu</surname><given-names>K</given-names></name><name><surname>Leni</surname><given-names>M</given-names></name><name><surname>Cabrera</surname><given-names>KI</given-names></name><name><surname>Dayan</surname><given-names>PS</given-names></name><etal/></person-group> <article-title>Urinary neutrophil gelatinase-associated lipocalin for the diagnosis of urinary tract infections</article-title>. <source>Pediatrics</source>. (<year>2017</year>) <volume>140</volume>(<issue>6</issue>):<fpage>e20171090</fpage>. <pub-id pub-id-type="doi">10.1542/peds.2017-1090</pub-id><pub-id pub-id-type="pmid">29146619</pub-id></citation></ref>
<ref id="B43"><label>43.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Valdimarsson</surname><given-names>S</given-names></name><name><surname>Jodal</surname><given-names>U</given-names></name><name><surname>Barreg&#x00E5;rd</surname><given-names>L</given-names></name><name><surname>Hansson</surname><given-names>S</given-names></name></person-group>. <article-title>Urine neutrophil gelatinase-associated lipocalin and other biomarkers in infants with urinary tract infection and in febrile controls</article-title>. <source>Pediatr Nephrol</source>. (<year>2017</year>) <volume>32</volume>(<issue>11</issue>):<fpage>2079</fpage>&#x2013;<lpage>87</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-017-3709-1</pub-id><pub-id pub-id-type="pmid">28756475</pub-id></citation></ref>
<ref id="B44"><label>44.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Forster</surname><given-names>CS</given-names></name><name><surname>Jackson</surname><given-names>E</given-names></name><name><surname>Ma</surname><given-names>Q</given-names></name><name><surname>Bennett</surname><given-names>M</given-names></name><name><surname>Shah</surname><given-names>SS</given-names></name><name><surname>Goldstein</surname><given-names>SL</given-names></name></person-group>. <article-title>Predictive ability of NGAL in identifying urinary tract infection in children with neurogenic bladders</article-title>. <source>Pediatr Nephrol</source>. (<year>2018</year>) <volume>33</volume>(<issue>8</issue>):<fpage>1365</fpage>&#x2013;<lpage>74</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-018-3936-0</pub-id><pub-id pub-id-type="pmid">29532235</pub-id></citation></ref>
<ref id="B45"><label>45.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Jung</surname><given-names>N</given-names></name><name><surname>Byun</surname><given-names>HJ</given-names></name><name><surname>Park</surname><given-names>JH</given-names></name><name><surname>Kim</surname><given-names>JS</given-names></name><name><surname>Kim</surname><given-names>HW</given-names></name><name><surname>Ha</surname><given-names>JY</given-names></name></person-group>. <article-title>Diagnostic accuracy of urinary biomarkers in infants younger than 3 months with urinary tract infection</article-title>. <source>Korean J Pediatr</source>. (<year>2018</year>) <volume>61</volume>(<issue>1</issue>):<fpage>24</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.3345/kjp.2018.61.1.24</pub-id><pub-id pub-id-type="pmid">29441109</pub-id></citation></ref>
<ref id="B46"><label>46.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Krzemie&#x0144;</surname><given-names>G</given-names></name><name><surname>Pa&#x0144;czyk-Tomaszewska</surname><given-names>M</given-names></name><name><surname>Adamczuk</surname><given-names>D</given-names></name><name><surname>Adamczuk</surname><given-names>D</given-names></name><name><surname>Kotula</surname><given-names>I</given-names></name><name><surname>Demkow</surname><given-names>U</given-names></name><etal/></person-group> <article-title>Neutrophil gelatinase-associated lipocalin: a biomarker for early diagnosis of urinary tract infections in infants</article-title>. <source>Adv Exp Med Biol</source>. (<year>2018</year>) <volume>1047</volume>:<fpage>71</fpage>&#x2013;<lpage>80</lpage>. <pub-id pub-id-type="doi">10.1007/5584_2017_107</pub-id></citation></ref>
<ref id="B47"><label>47.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Forster</surname><given-names>CS</given-names></name><name><surname>Loechtenfeldt</surname><given-names>AM</given-names></name><name><surname>Shah</surname><given-names>SS</given-names></name><name><surname>Goldstein</surname><given-names>S</given-names></name></person-group>. <article-title>Urine neutrophil gelatinaseassociated lipocalin in girls with recurrent urinary tract infections</article-title>. <source>Pediatr Nephrol</source>. (<year>2020</year>) <volume>35</volume>(<issue>11</issue>):<fpage>2121</fpage>&#x2013;<lpage>8</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-020-04654-9</pub-id><pub-id pub-id-type="pmid">32564279</pub-id></citation></ref>
<ref id="B48"><label>48.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shaikh</surname><given-names>N</given-names></name><name><surname>Martin</surname><given-names>JM</given-names></name><name><surname>Hoberman</surname><given-names>A</given-names></name><name><surname>Skae</surname><given-names>M</given-names></name><name><surname>Milkovich</surname><given-names>L</given-names></name><name><surname>McElheny</surname><given-names>C</given-names></name><etal/></person-group> <article-title>Biomarkers that differentiate false positive urinalyses from true urinary tract infection</article-title>. <source>Pediatr Nephrol</source>. (<year>2020</year>) <volume>35</volume>(<issue>2</issue>):<fpage>321</fpage>&#x2013;<lpage>9</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-019-04403-7</pub-id><pub-id pub-id-type="pmid">31758242</pub-id></citation></ref>
<ref id="B49"><label>49.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Forster</surname><given-names>CS</given-names></name><name><surname>Lamanna</surname><given-names>OK</given-names></name><name><surname>Rounds</surname><given-names>A</given-names></name><name><surname>Sprague</surname><given-names>BM</given-names></name><name><surname>Ljungberg</surname><given-names>I</given-names></name><name><surname>Groah</surname><given-names>SL</given-names></name></person-group>. <article-title>The association between urine neutrophil gelatinase-associated lipocalin and UTI in people with neurogenic lower urinary tract dysfunction</article-title>. <source>Spinal Cord</source>. (<year>2021</year>) <volume>59</volume>(<issue>9</issue>):<fpage>959</fpage>&#x2013;<lpage>66</lpage>. <pub-id pub-id-type="doi">10.1038/s41393-020-00552-x</pub-id><pub-id pub-id-type="pmid">32963362</pub-id></citation></ref>
<ref id="B50"><label>50.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Lubell</surname><given-names>TR</given-names></name><name><surname>Barasch</surname><given-names>JM</given-names></name><name><surname>King</surname><given-names>B</given-names></name><name><surname>Ochs</surname><given-names>JB</given-names></name><name><surname>Fan</surname><given-names>WJ</given-names></name><name><surname>Duong</surname><given-names>J</given-names></name><etal/></person-group> <article-title>Urinary tract infections in children: testing a novel, noninvasive, point-of-care diagnostic marker</article-title>. <source>Acad Emerg Med</source>. (<year>2022</year>) <volume>29</volume>(<issue>3</issue>):<fpage>326</fpage>&#x2013;<lpage>33</lpage>. <pub-id pub-id-type="doi">10.1111/acem.14402</pub-id><pub-id pub-id-type="pmid">34665891</pub-id></citation></ref>
<ref id="B51"><label>51.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Moon</surname><given-names>JH</given-names></name><name><surname>Yoo</surname><given-names>KH</given-names></name><name><surname>Yim</surname><given-names>HE</given-names></name></person-group>. <article-title>Urinary neutrophil gelatinase-associated lipocalin: a marker of urinary tract infection among febrile children</article-title>. <source>Clin Exp Pediatr</source>. (<year>2021</year>) <volume>64</volume>(<issue>7</issue>):<fpage>347</fpage>&#x2013;<lpage>54</lpage>. <pub-id pub-id-type="doi">10.3345/cep.2020.01130</pub-id><pub-id pub-id-type="pmid">33091975</pub-id></citation></ref>
<ref id="B52"><label>52.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Pamuk</surname><given-names>U</given-names></name><name><surname>Kalman</surname><given-names>S</given-names></name><name><surname>Tascilar</surname><given-names>M</given-names></name><name><surname>Sertoglu</surname><given-names>E</given-names></name></person-group>. <article-title>Neutrophil gelatinase-associated lipocalin as a biomarker for the diagnosis of urinary tract infection in children</article-title>. <source>Turk J Vasc Surg</source>. (<year>2022</year>) <volume>11</volume>(<issue>1</issue>):<fpage>70</fpage>&#x2013;<lpage>4</lpage>. <pub-id pub-id-type="doi">10.5455/medscience.2021.06.202</pub-id></citation></ref>
<ref id="B53"><label>53.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shaikh</surname><given-names>N</given-names></name><name><surname>Liu</surname><given-names>H</given-names></name><name><surname>Kurs-Lasky</surname><given-names>M</given-names></name><name><surname>Forster</surname><given-names>CS</given-names></name></person-group>. <article-title>Biomarkers for febrile urinary tract infection in children</article-title>. <source>Pediatr Nephrol</source>. (<year>2022</year>) <volume>37</volume>(<issue>1</issue>):<fpage>171</fpage>&#x2013;<lpage>7</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-021-05173-x</pub-id><pub-id pub-id-type="pmid">34251495</pub-id></citation></ref>
<ref id="B54"><label>54.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Haley</surname><given-names>E</given-names></name><name><surname>Luke</surname><given-names>N</given-names></name><name><surname>Mathur</surname><given-names>M</given-names></name><name><surname>Festa</surname><given-names>RA</given-names></name><name><surname>Wang</surname><given-names>J</given-names></name><name><surname>Jiang</surname><given-names>Y</given-names></name><etal/></person-group> <article-title>Comparison shows that multiplex polymerase chain reaction identifies infection-associated urinary biomarker-positive urinary tract infections that are missed by standard urine culture</article-title>. <source>Eur Urol Open Sci</source>. (<year>2023</year>) <volume>58</volume>:<fpage>73</fpage>&#x2013;<lpage>81</lpage>. <pub-id pub-id-type="doi">10.1016/j.euros.2023.10.008</pub-id><pub-id pub-id-type="pmid">38152485</pub-id></citation></ref>
<ref id="B55"><label>55.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>DY</given-names></name><name><surname>Yim</surname><given-names>HE</given-names></name><name><surname>Son</surname><given-names>MH</given-names></name><name><surname>Yoo</surname><given-names>KH</given-names></name></person-group>. <article-title>Urine specific gravity, pyuria, and neutrophil gelatinase-associated lipocalin for identifying urinary tract infection in young children</article-title>. <source>Pediatr Nephrol</source>. (<year>2023</year>) <volume>38</volume>(<issue>10</issue>):<fpage>3337</fpage>&#x2013;<lpage>46</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-023-05957-3</pub-id><pub-id pub-id-type="pmid">37074426</pub-id></citation></ref>
<ref id="B56"><label>56.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Parnell</surname><given-names>LKS</given-names></name><name><surname>Luke</surname><given-names>N</given-names></name><name><surname>Mathur</surname><given-names>M</given-names></name><name><surname>Festa</surname><given-names>RA</given-names></name><name><surname>Haley</surname><given-names>E</given-names></name><name><surname>Wang</surname><given-names>J</given-names></name><etal/></person-group> <article-title>Elevated UTI biomarkers in symptomatic patients with urine microbial densities of 10,000&#x2005;CFU/ml indicate a lower threshold for diagnosing UTIs</article-title>. <source>Diagnostics (Basel)</source>. (<year>2023</year>) <volume>13</volume>(<issue>16</issue>):<fpage>2688</fpage>. <pub-id pub-id-type="doi">10.3390/diagnostics13162688</pub-id><pub-id pub-id-type="pmid">37627948</pub-id></citation></ref>
<ref id="B57"><label>57.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Shaikh</surname><given-names>N</given-names></name><name><surname>Kurs-Lasky</surname><given-names>M</given-names></name><name><surname>Liu</surname><given-names>H</given-names></name><name><surname>Rajakumar</surname><given-names>V</given-names></name><name><surname>Qureini</surname><given-names>H</given-names></name><name><surname>Conway</surname><given-names>IO</given-names></name><etal/></person-group> <article-title>Biomarkers for febrile urinary tract infection in children</article-title>. <source>Front Pediatr</source>. (<year>2023</year>) <volume>11</volume>:<fpage>1163546</fpage>. <pub-id pub-id-type="doi">10.3389/fped.2023.1163546</pub-id><pub-id pub-id-type="pmid">37228436</pub-id></citation></ref>
<ref id="B58"><label>58.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Akhlaghpour</surname><given-names>M</given-names></name><name><surname>Haley</surname><given-names>E</given-names></name><name><surname>Parnell</surname><given-names>L</given-names></name><name><surname>Luke</surname><given-names>N</given-names></name><name><surname>Mathur</surname><given-names>M</given-names></name><name><surname>Festa</surname><given-names>RA</given-names></name><etal/></person-group> <article-title>Urine biomarkers individually and as a consensus model show high sensitivity and specificity for detecting UTIs</article-title>. <source>BMC Infect Dis</source>. (<year>2024</year>) <volume>24</volume>(<issue>1</issue>):<fpage>153</fpage>. <pub-id pub-id-type="doi">10.1186/s12879-024-09044-2</pub-id><pub-id pub-id-type="pmid">38297221</pub-id></citation></ref>
<ref id="B59"><label>59.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Bilsen</surname><given-names>MP</given-names></name><name><surname>Treep</surname><given-names>MM</given-names></name><name><surname>Aantjes</surname><given-names>MJ</given-names></name><name><surname>van Andel</surname><given-names>E</given-names></name><name><surname>Stalenhoef</surname><given-names>JE</given-names></name><name><surname>van Nieuwkoop</surname><given-names>C</given-names></name><etal/></person-group> <article-title>Diagnostic accuracy of urine biomarkers for urinary tract infection in older women: a case-control study</article-title>. <source>Clin Microbiol Infect</source>. (<year>2024</year>) <volume>30</volume>(<issue>2</issue>):<fpage>216</fpage>&#x2013;<lpage>22</lpage>. <pub-id pub-id-type="doi">10.1016/j.cmi.2023.09.023</pub-id><pub-id pub-id-type="pmid">37805035</pub-id></citation></ref>
<ref id="B60"><label>60.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Morita</surname><given-names>Y</given-names></name><name><surname>Kurano</surname><given-names>M</given-names></name><name><surname>Tanaka</surname><given-names>M</given-names></name><name><surname>Hisasue</surname><given-names>T</given-names></name><name><surname>Sato</surname><given-names>M</given-names></name><name><surname>Ono</surname><given-names>Y</given-names></name><etal/></person-group> <article-title>Midstream urine sampling is necessary for accurate measurement of the urinary level of neutrophil gelatinase-associated lipocalin in healthy female subjects</article-title>. <source>Clin Biochem</source>. (<year>2020</year>) <volume>79</volume>:<fpage>70</fpage>&#x2013;<lpage>4</lpage>. <pub-id pub-id-type="doi">10.1016/j.clinbiochem.2020.03.005</pub-id><pub-id pub-id-type="pmid">32184106</pub-id></citation></ref>
<ref id="B61"><label>61.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Gupta</surname><given-names>S</given-names></name><name><surname>Preece</surname><given-names>J</given-names></name><name><surname>Haynes</surname><given-names>A</given-names></name><name><surname>Becknell</surname><given-names>B</given-names></name><name><surname>Ching</surname><given-names>C</given-names></name></person-group>. <article-title>Differentiating asymptomatic bacteriuria from urinary tract infection in the pediatric neurogenic bladder population: NGAL as a promising biomarker</article-title>. <source>Top Spinal Cord Inj Rehabil</source>. (<year>2019</year>) <volume>25</volume>(<issue>3</issue>):<fpage>214</fpage>&#x2013;<lpage>21</lpage>. <pub-id pub-id-type="doi">10.1310/sci2503-214</pub-id><pub-id pub-id-type="pmid">31548788</pub-id></citation></ref>
<ref id="B62"><label>62.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Sim</surname><given-names>JH</given-names></name><name><surname>Yim</surname><given-names>HE</given-names></name><name><surname>Choi</surname><given-names>BM</given-names></name><name><surname>Lee</surname><given-names>JH</given-names></name><name><surname>Yoo</surname><given-names>KH</given-names></name></person-group>. <article-title>Plasma neutrophil gelatinase-associated lipocalin predicts acute pyelonephritis in children with urinary tract infections</article-title>. <source>Pediatr Res</source>. (<year>2015</year>) <volume>78</volume>(<issue>1</issue>):<fpage>48</fpage>&#x2013;<lpage>55</lpage>. <pub-id pub-id-type="doi">10.1038/pr.2015.59</pub-id><pub-id pub-id-type="pmid">25790277</pub-id></citation></ref>
<ref id="B63"><label>63.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Kim</surname><given-names>BK</given-names></name><name><surname>Yim</surname><given-names>HE</given-names></name><name><surname>Yoo</surname><given-names>KH</given-names></name></person-group>. <article-title>Plasma neutrophil gelatinase-associated lipocalin: a marker of acute pyelonephritis in children</article-title>. <source>Pediatr Nephrol</source>. (<year>2017</year>) <volume>32</volume>(<issue>3</issue>):<fpage>477</fpage>&#x2013;<lpage>84</lpage>. <pub-id pub-id-type="doi">10.1007/s00467-016-3518-y</pub-id><pub-id pub-id-type="pmid">27744618</pub-id></citation></ref>
<ref id="B64"><label>64.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Yun</surname><given-names>BA</given-names></name><name><surname>Yang</surname><given-names>EM</given-names></name><name><surname>Kim</surname><given-names>CJ</given-names></name></person-group>. <article-title>Plasma neutrophil gelatinase-associated lipocalin as a predictor of renal parenchymal involvement in infants with febrile urinary tract infection: a preliminary study</article-title>. <source>Ann Lab Med</source>. (<year>2018</year>) <volume>38</volume>(<issue>5</issue>):<fpage>425</fpage>&#x2013;<lpage>30</lpage>. <pub-id pub-id-type="doi">10.3343/alm.2018.38.5.425</pub-id><pub-id pub-id-type="pmid">29797812</pub-id></citation></ref>
<ref id="B65"><label>65.</label><citation citation-type="journal"><person-group person-group-type="author"><name><surname>Cai</surname><given-names>L</given-names></name><name><surname>Rubin</surname><given-names>J</given-names></name><name><surname>Han</surname><given-names>W</given-names></name><name><surname>Venge</surname><given-names>P</given-names></name><name><surname>Xu</surname><given-names>S</given-names></name></person-group>. <article-title>The origin of multiple molecular forms in urine of HNL/NGAL</article-title>. <source>Clin J Am Soc Nephrol</source>. (<year>2010</year>) <volume>5</volume>(<issue>12</issue>):<fpage>2229</fpage>&#x2013;<lpage>35</lpage>. <pub-id pub-id-type="doi">10.2215/CJN.00980110</pub-id><pub-id pub-id-type="pmid">20829422</pub-id></citation></ref>
<ref id="B66"><label>66.</label><citation citation-type="journal"><comment>Available online at:</comment> <ext-link ext-link-type="uri" xlink:href="https://www.globenewswire.com/news-release/2023/12/07/2792907/0/en/BioPorto-Receives-FDA-510-k-Clearance-for-NGAL-Test-in-the-United-States-First-Test-to-Aid-in-Assessing-AKI-Risk-for-Patients-Aged-3-Months-Through-21-Years.html">https://www.globenewswire.com/news-release/2023/12/07/2792907/0/en/BioPorto-Receives-FDA-510-k-Clearance-for-NGAL-Test-in-the-United-States-First-Test-to-Aid-in-Assessing-AKI-Risk-for-Patients-Aged-3-Months-Through-21-Years.html</ext-link></citation></ref></ref-list>
</back>
</article>