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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2023.1157123</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Non-linear association of fasting C-peptide and uric acid levels with renal dysfunction based on restricted cubic spline in patients with type 2 diabetes: A real-world study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Lu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2245506"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Hu</surname>
<given-names>Yifei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2245511"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Ma</surname>
<given-names>Yongjun</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="http://loop.frontiersin.org/people/2245514"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Huabin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1255535"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine</institution>, <addr-line>Jinhua, Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Central Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine</institution>, <addr-line>Jinhua, Zhejiang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Paulo Matafome, University of Coimbra, Portugal</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Andrea Fontana, Casa Sollievo della Sofferenza Hospital (IRCCS), Italy; Chung Nguyen, Innsbruck Medical University, Austria; B&#xe1;rbara Oliveiros, University of Coimbra, Portugal</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Yongjun Ma, <email xlink:href="mailto:jhyymyj@126.com">jhyymyj@126.com</email>; Huabin Wang, <email xlink:href="mailto:whb798183844@126.com">whb798183844@126.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Clinical Diabetes, a section of the journal Frontiers in Endocrinology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>23</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1157123</elocation-id>
<history>
<date date-type="received">
<day>02</day>
<month>02</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>08</day>
<month>03</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Chen, Hu, Ma and Wang</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Chen, Hu, Ma and Wang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). 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>Background</title>
<p>Previous studies had showed divergent findings on the associations of C-peptide and/or uric acid (UA) with renal dysfunction odds in patients with type 2 diabetes mellitus (T2DM). We hypothesized that there were non-linear relationships between C-peptide, UA and renal dysfunction odds. This study aimed to further investigate the relationships of different stratification of C-peptide and UA with renal dysfunction in patients with T2DM.</p>
</sec>
<sec>
<title>Method</title>
<p>We conducted a cross-sectional real-world observational study of 411 patients with T2DM. The levels of fasting C-peptide, 2h postprandial C-peptide, the ratio of fasting C-peptide to 2h postprandial C-peptide (C0/C2 ratio), UA and other characteristics were recorded. Restricted cubic spline (RCS) curves was performed to evaluated the associations of stratified C-peptide and UA with renal dysfunction odds.</p>
</sec>
<sec>
<title>Results</title>
<p>Fasting C-peptide, C0/C2 ratio and UA were independently and significantly associated with renal dysfunction in patients with T2DM as assessed by multivariate analyses (p &lt; 0.05). In especial, non-linear relationships with threshold effects were observed among fasting C-peptide, UA and renal dysfunction according to RCS analyses. Compared with patients with 0.28 &#x2264; fasting C-peptide &#x2264; 0.56 nmol/L, patients with fasting C-peptide &lt; 0.28 nmol/L (OR = 1.38, p = 0.246) or fasting C-peptide &gt; 0.56 nmol/L (OR = 1.85, p = 0.021) had relatively higher renal dysfunction odds after adjusting for confounding factors. Similarly, compared with patients with 276 &#x2264; UA &#x2264; 409 &#x3bc;mol/L, patients with UA &lt; 276 &#x3bc;mol/L (OR = 1.32, p = 0.262) or UA &gt; 409 &#x3bc;mol/L (OR = 6.24, p &lt; 0.001) had relatively higher odds of renal dysfunction.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The renal dysfunction odds in patients with T2DM was non-linearly associated with the levels of serum fasting C-peptide and UA. Fasting C-peptide and UA might have the potential role in odds stratification of renal dysfunction.</p>
</sec>
</abstract>
<kwd-group>
<kwd>C-peptide</kwd>
<kwd>non-linear association</kwd>
<kwd>renal dysfunction</kwd>
<kwd>type 2 diabetes</kwd>
<kwd>uric acid</kwd>
</kwd-group>
<contract-sponsor id="cn001">Science and Technology Department of Zhejiang Province<named-content content-type="fundref-id">10.13039/501100008990</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Jinhua Science and Technology Bureau<named-content content-type="fundref-id">10.13039/501100008092</named-content>
</contract-sponsor>
<contract-sponsor id="cn003">Medical Science and Technology Project of Zhejiang Province<named-content content-type="fundref-id">10.13039/501100017594</named-content>
</contract-sponsor>
<counts>
<fig-count count="1"/>
<table-count count="3"/>
<equation-count count="0"/>
<ref-count count="32"/>
<page-count count="8"/>
<word-count count="4478"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>In china, the incidence of diabetes mellitus has rapidly risen from 0.67% in 1980 to 11.2% in 2020, and its prevalence is increasing every year (<xref ref-type="bibr" rid="B1">1</xref>). Diabetic kidney disease (DKD) occurs in 20% to 40% of patients with diabetes, it has become one of the most common complications of diabetes and the leading cause of end-stage renal disease in most of the world (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). DKD has posed a rapidly growing global health care burden (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B5">5</xref>). Therefore, in order to explore the better preventive and therapeutic methods, and lifestyle of patients with DKD, many researchers have focused on studying the clinical risk factors for occurrence and progression of DKD in patients with diabetes, such as age, gender, blood pressure, glycemic control, diabetes duration, body mass index (BMI), and dyslipidemia, among others (<xref ref-type="bibr" rid="B6">6</xref>&#x2013;<xref ref-type="bibr" rid="B8">8</xref>).</p>
<p>C-peptide consists of 31amino acids, and is formed by the cleavage of pro-insulin (<xref ref-type="bibr" rid="B9">9</xref>). Compared with insulin, C-peptide is secreted in equimolar amounts and has a longer half-life, hence, it is recognized as a reliable indicator of the function of pancreatic &#x3b2;-cell (<xref ref-type="bibr" rid="B10">10</xref>). Recently, C-peptide is no longer considered an inert molecule, it may have multiple functions, including signaling pathways activation, physiological effects, and protection against complications of diabetes (<xref ref-type="bibr" rid="B11">11</xref>). Animal studies have demonstrated that C-peptide can improve functional abnormalities in the glomeruli, reduce the risk of albuminuria and hyper-filtration, and prevent the chronic complications of diabetes (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B12">12</xref>). However, several small-scale clinical trials and/or animal studies showed the divergent findings in the role of C-peptide administration in the outcomes of patients with DKD (<xref ref-type="bibr" rid="B9">9</xref>). Therefore, the association of serum C-peptide with the risk of DKD is complicated, and it needs to be further clarified in patients with diabetes mellitus.</p>
<p>More recently, some studies have identified serum uric acid (UA) as an independent clinical risk factor for chronic kidney disease in patients with diabetes mellitus (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>), however, others do not (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). The association between kidney impairment risk and the different stratification of serum UA level in patients with type 2 diabetes mellitus (T2DM) remains unclear. Given the above, we hypothesized that there were non-linear relationships between C-peptide, UA and renal dysfunction odds. Therefore, we conducted a real-world observational study to further explore the relationships of different stratification of C-peptide and UA levels with renal dysfunction in patients with T2DM.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Study design and population</title>
<p>This cross-sectional real-world observational study was based on 513 patients with T2DM who visited at the Endocrinology Department of the Affiliated Jinhua Hospital, Zhejiang University School of Medicine, between January 2017 and December 2017 (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). The subjects of this study were randomly recruited based on the following exclusion criteria: (1) patients with age &lt; 18 years old; (2) patients with primary kidney diseases before the diagnosis of T2DM; (3) patients with serious autoimmune diseases, liver diseases and/or infectious diseases. In addition, 102 subjects with lack of the laboratory data of fasting C-peptide, 2h postprandial C-peptide and/or UA were excluded. Finally, 411 participants with an average age of 57.60 &#xb1; 13.52 years old were included in this study. Among the subjects cohort, the median diabetic duration was 7 years; 41.12% of them were female, 58.88% were male, and 48.48% had hypertension; the proportion of participants with angiotensin converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB) use was 27.98%. The present study followed the tenets of the Declaration of Helsinki and was approved by the Ethics Committee of Affiliated Jinhua Hospital, Zhejiang University School of Medicine. Ethical approval code: (Research) 2021-Ethical Review-75-01.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Clinical characteristics and definitions</title>
<p>Most clinical information and the laboratory parameters of the subjects were obtained from the electronic medical record system. The clinical characteristics included gender, age, weight, height, diabetic duration, hypertension, diastolic blood pressure (DBP), systolic blood pressure (SBP), and the history of ACEI/ARB use. The laboratory parameters included glycated hemoglobin (HbA1c), serum UA, creatinine, fasting C-peptide, 2h postprandial C-peptide, triglycerides, total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase, aspartate aminotransferase. Among these parameters, the HbA1c level was tested by BIO-RAD D-100 analyzer, the other indicators were detected using Beckman Coulter automatic immuno analyzer or automatic biochemical Analyzer with its original reagents in the department of clinical laboratory. The first or second urine specimens of all the subjects were collected, the levels of urinary creatinine and albumin were detected using Beckman Coulter biochemical Analyzer and Byron Diagnostics reagents (Byron, Shanghai, China).</p>
<p>Body mass index (BMI) was calculated based on the height and weight of the participants. The ratio of fasting C-peptide to 2h postprandial C-peptide was defined as C0/C2 ratio. The Xiangya equation (<xref ref-type="bibr" rid="B19">19</xref>) based on a large Chinese population was used to calculate the estimated glomerular filtration rate (eGFR). eGFR decline was defined as eGFR &lt; 60 ml/min/1.73m<sup>2</sup>. Albuminuria was defined as urinary albumin-to-creatinine ratio (ACR) &gt; 30 mg/g. In the present study, renal dysfunction was defined as albuminuria and/or eGFR decline.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Statistical analysis</title>
<p>All the statistical analyses of the data in this study were performed by using R software (3.6.4 version) and SPSS 26.0 statistical software. The continuous variables with normally distribution were expressed as mean &#xb1; standard deviation (SD); the continuous variables with skewed distribution were expressed as median (Q1 - Q3); the categorical variables were presented as the number (percentage, %). Unpaired t-tests, Mann-Whitney tests and Pearson&#x2019;s chi-squared tests were performed to execute the between-group comparisons, as appropriate. Logistic regression was conducted for evaluating the relationships between different clinical parameters and the renal dysfunction in patients with T2DM. In addition, because the range of fasting C-peptide values was relatively small (0.02 - 1.53 nmol/L), and the range of serum UA values was relatively wide (148 - 834 &#x3bc;mol/L), hence, fasting C-peptide and UA analyses were also presented as Z-scores and quartiles in the logistic regressions. Restricted cubic spline (RCS) curves based on logistic regression were performed to evaluated the associations of C-peptide and UA values with renal dysfunction odds (odds ratio, OR). According to Akaike Information Criterion (AIC), the knot number corresponding to the minimum AIC value was defined for each model, respectively. In this study, the optimal numbers of knots were 3 for the estimated models, respectively, and these 3 knots located at 10th, 50th, and 90th percentile of the variable distribution were analyzed. The Wald Chi-square test was used to assess both &#x201c;the overall&#x201d; and the &#x201c;nonlinearity&#x201d; hypothesis in the RCS analyses.</p>
<p>The R package called &#x2018;CatPredi&#x2019; was used to categorize the continuous predictors (UA and fasting C-peptide) with &#x201c;Addfor&#x201d; algorithm (<xref ref-type="bibr" rid="B20">20</xref>, <xref ref-type="bibr" rid="B21">21</xref>), and the optimal cut-points were selected out. In this study, according to the RCS analyses, we considered categorizing the UA and fasting C-peptide variables into 3 categories, respectively. Finally, the threshold effects of fasting C-peptide and UA for renal dysfunction odds based on RCS analysis were also evaluated using logistic regression. A two-tailed p-value &lt; 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Characteristics of the participants</title>
<p>Overall the 411 participants with T2DM, 179 (43.55%) had albuminuria, 26 (6.33%) had eGFR decline, the proportion of subjects with renal dysfunction was 183(44.53%). The comparisons of the clinical characteristics between the participants with and without renal dysfunction were summarized in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. The levels of age, SBP, HbA1c, diabetic duration, fasting C-peptide, C0/C2 ratio, UA, serum and urinary creatinine, ACR, eGFR and the proportion of hypertension presented statistically significant differences between participants with and without renal impairment (p &lt; 0.05). However, statistically significant differences between the two groups were not detected for 2h postprandial C-peptide, BMI, DBP, gender, triglycerides, total cholesterol, HDL-C and LDL-C. Although the proportion of ACEI/ARB use was also higher in subjects with renal dysfunction compared with the other group (35.52% vs 21.93%, p = 0.002), of note, almost all the participants with ACEI/ARB use were the patients with hypertension.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinical characteristics of study patients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">Patients without renal dysfunction (n = 228)</th>
<th valign="top" align="center">Patients with renal dysfunction (n = 183)</th>
<th valign="top" align="center">p-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age, years</td>
<td valign="top" align="center">55.80 &#xb1; 12.57</td>
<td valign="top" align="center">59.83 &#xb1; 14.34</td>
<td valign="top" align="center">0.003</td>
</tr>
<tr>
<td valign="top" align="left">Male, n (%)</td>
<td valign="top" align="center">137 (60.09%)</td>
<td valign="top" align="center">105 (57.38%)</td>
<td valign="top" align="center">0.579</td>
</tr>
<tr>
<td valign="top" align="left">BMI, kg/m2</td>
<td valign="top" align="center">24.28 &#xb1; 3.28</td>
<td valign="top" align="center">24.51 &#xb1; 3.30</td>
<td valign="top" align="center">0.492</td>
</tr>
<tr>
<td valign="top" align="left">SBP, mmHg</td>
<td valign="top" align="center">133 &#xb1; 19</td>
<td valign="top" align="center">138 &#xb1; 20</td>
<td valign="top" align="center">0.010</td>
</tr>
<tr>
<td valign="top" align="left">DBP, mmHg</td>
<td valign="top" align="center">79 &#xb1; 11</td>
<td valign="top" align="center">79 &#xb1; 12</td>
<td valign="top" align="center">0.868</td>
</tr>
<tr>
<td valign="top" align="left">Hypertension, n (%)</td>
<td valign="top" align="center">88 (38.60%)</td>
<td valign="top" align="center">110 (60.11%)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">ACEI/ARB use, n (%)</td>
<td valign="top" align="center">50 (21.93%)</td>
<td valign="top" align="center">65 (35.52%)</td>
<td valign="top" align="center">0.002</td>
</tr>
<tr>
<td valign="top" align="left">Diabetic duration, years</td>
<td valign="top" align="center">7.05 &#xb1; 5.66</td>
<td valign="top" align="center">9.55 &#xb1; 7.88</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">HbA1c, %</td>
<td valign="top" align="center">8.84 &#xb1; 2.44</td>
<td valign="top" align="center">9.36 &#xb1; 2.63</td>
<td valign="top" align="center">0.041</td>
</tr>
<tr>
<td valign="top" align="left">Total Cholesterol, mmol/L</td>
<td valign="top" align="center">4.53 &#xb1; 1.32</td>
<td valign="top" align="center">4.41 &#xb1; 1.21</td>
<td valign="top" align="center">0.343</td>
</tr>
<tr>
<td valign="top" align="left">Triglyceride, mmol/L</td>
<td valign="top" align="center">1.54 (1.00 - 2.24)</td>
<td valign="top" align="center">1.45 (1.03 - 2.29)</td>
<td valign="top" align="center">0.884</td>
</tr>
<tr>
<td valign="top" align="left">HDL-C, mmol/l</td>
<td valign="top" align="center">1.19 &#xb1; 0.27</td>
<td valign="top" align="center">1.16 &#xb1; 0.32</td>
<td valign="top" align="center">0.288</td>
</tr>
<tr>
<td valign="top" align="left">LDL-C, mmol/l</td>
<td valign="top" align="center">2.92 &#xb1; 0.80</td>
<td valign="top" align="center">2.91 &#xb1; 0.94</td>
<td valign="top" align="center">0.944</td>
</tr>
<tr>
<td valign="top" align="left">Alanine aminotransferase, U/L</td>
<td valign="top" align="center">19.00 (13.85 - 27.65)</td>
<td valign="top" align="center">19.00 (12.90 - 25.75)</td>
<td valign="top" align="center">0.590</td>
</tr>
<tr>
<td valign="top" align="left">Aspartate aminotransferase, U/L</td>
<td valign="top" align="center">20.20 (16.00 - 25.78)</td>
<td valign="top" align="center">20.00 (15.50 - 25.95)</td>
<td valign="top" align="center">0.131</td>
</tr>
<tr>
<td valign="top" align="left">Fasting C-peptide, nmol/L</td>
<td valign="top" align="center">0.44 &#xb1; 0.26</td>
<td valign="top" align="center">0.52 &#xb1; 0.35</td>
<td valign="top" align="center">0.017</td>
</tr>
<tr>
<td valign="top" align="left">2h postprandial C-peptide, nmol/L</td>
<td valign="top" align="center">1.27 &#xb1; 0.87</td>
<td valign="top" align="center">1.28 &#xb1; 0.97</td>
<td valign="top" align="center">0.949</td>
</tr>
<tr>
<td valign="top" align="left">C0/C2 ratio</td>
<td valign="top" align="center">0.39 (0.27 - 0.55)</td>
<td valign="top" align="center">0.44 (0.31 - 0.67)</td>
<td valign="top" align="center">0.002</td>
</tr>
<tr>
<td valign="top" align="left">UA, &#x3bc;mol/L</td>
<td valign="top" align="center">295.36 &#xb1; 69.26</td>
<td valign="top" align="center">330.55 &#xb1; 110.30</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">Serum creatinine, &#x3bc;mol/L</td>
<td valign="top" align="center">72.34 &#xb1; 12.76</td>
<td valign="top" align="center">83.99 &#xb1; 26.50</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">Urinary creatinine, &#x3bc;mol/L</td>
<td valign="top" align="center">7310 (5346.75 - 10355.75)</td>
<td valign="top" align="center">4888(3624 - 7013)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">ACR, mg/g</td>
<td valign="top" align="center">13.32 (8.99 - 19.86)</td>
<td valign="top" align="center">83.84 (44.76 - 277.32)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
<tr>
<td valign="top" align="left">eGFR, ml/min/1.73 m2</td>
<td valign="top" align="center">80 &#xb1; 9</td>
<td valign="top" align="center">74 &#xb1; 14</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; HbA1c, glycated hemoglobin; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; C0/C2 ratio, fasting C-peptide-to-2h C-peptide ratio; UA, uric acid; ACR, albumin-to-creatinine ratio; eGFR, estimated glomerular filtration rate.</p>
</fn>
<fn>
<p>&#x201c;-&#x201d; means &#x201c;not applicable&#x201d;.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>The association of C-peptide and UA with renal dysfunction odds</title>
<p>On the whole, the levels of fasting C-peptide, C0/C2 ratio and UA were significantly related with the probability of renal dysfunction in patients with T2DM in univariate logistic regression analysis using the continuous values of these three parameters. After adjustment for the potential confounders (age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, UA, fasting C-peptide and hypertension), the strength of this association remained statistically significant (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Every 1 SD increase of fasting C-peptide, C0/C2 ratio and UA, the odds of renal dysfunction increased by about 34%, 28% and 49%, respectively. (The SD of fasting C-peptide, C0/C2 ratio and UA were 0.30 nmol/L, 0.32 C0/C2 and 91.45 &#x3bc;mol/L, respectively.) However, in the multivariate analysis of these three stratified parameters (quartiles, Q1 - Q4), the participants with higher levels (Q2 - Q4) of the three indicators did not present a statistically significant differences of renal impairment odds compared with the subjects with the lowest levels (Q1) of these three parameters (p &#x2265; 0.05), respectively. In addition, the interaction effect between fasting C-peptide and UA for renal dysfunction odds was also performed in the logistic regression analyses. After adjustment for the potential confounders, no statistical interaction effect was found (OR = 1.09, p = 0.339), indicating that there was no multiplication interaction for the renal dysfunction odds between fasting C-peptide and UA.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>The associations of fasting C-peptide, C0/C2 and UA with the odds of renal dysfunction in patients with type 2 diabetes.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Variables</th>
<th valign="top" colspan="2" align="center">Univariate analyses</th>
<th valign="top" colspan="2" align="center">Multivariate analyses#</th>
</tr>    <tr>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">p-value</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">p-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Fasting C-peptide (nmol/L)</td>
<td valign="top" align="center">2.18 (1.14 - 4.18)</td>
<td valign="top" align="center">0.018</td>
<td valign="top" align="center">2.64 (1.17 - 5.97)</td>
<td valign="top" align="center">0.019</td>
</tr>
<tr>
<td valign="top" align="right">*Continuous, per SD</td>
<td valign="top" align="center">1.27 (1.04 - 1.56)</td>
<td valign="top" align="center">0.018</td>
<td valign="top" align="center">1.34 (1.05 - 1.72)</td>
<td valign="top" align="center">0.019</td>
</tr>
<tr>
<td valign="top" align="right">Q1 (0.02 - 0.25)</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="right">Q2 (0.26 - 0.41)</td>
<td valign="top" align="center">0.71 (0.41 - 1.22)</td>
<td valign="top" align="center">0.216</td>
<td valign="top" align="center">0.75 (0.41 - 1.38)</td>
<td valign="top" align="center">0.352</td>
</tr>
<tr>
<td valign="top" align="right">Q3 (0.42 - 0.63)</td>
<td valign="top" align="center">0.48 (0.27 - 0.85)</td>
<td valign="top" align="center">0.011</td>
<td valign="top" align="center">1.09 (0.58 - 2.05)</td>
<td valign="top" align="center">0.784</td>
</tr>
<tr>
<td valign="top" align="right">Q4 (0.64 - 1.53)</td>
<td valign="top" align="center">0.63 (0.36 - 1.10)</td>
<td valign="top" align="center">0.106</td>
<td valign="top" align="center">1.55 (0.81 - 2.98)</td>
<td valign="top" align="center">0.191</td>
</tr>
<tr>
<td valign="top" align="left">C0/C2 ratio</td>
<td valign="top" align="center">2.44 (1.23 - 4.82)</td>
<td valign="top" align="center">0.011</td>
<td valign="top" align="center">2.15 (1.04 - 4.44)</td>
<td valign="top" align="center">0.038</td>
</tr>
<tr>
<td valign="top" align="right">**Continuous, per SD</td>
<td valign="top" align="center">1.34 (1.07 - 1.67)</td>
<td valign="top" align="center">0.011</td>
<td valign="top" align="center">1.28 (1.01 - 1.62)</td>
<td valign="top" align="center">0.038</td>
</tr>
<tr>
<td valign="top" align="right">Q1 (0.09 - 0.26)</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="right">Q2 (0.27 - 0.41)</td>
<td valign="top" align="center">1.16 (0.66 - 2.02)</td>
<td valign="top" align="center">0.614</td>
<td valign="top" align="center">0.83 (0.45 - 1.55)</td>
<td valign="top" align="center">0.563</td>
</tr>
<tr>
<td valign="top" align="right">Q3 (0.42 - 0.61)</td>
<td valign="top" align="center">1.50 (0.86 - 2.61)</td>
<td valign="top" align="center">0.156</td>
<td valign="top" align="center">0.99 (0.52 - 1.92)</td>
<td valign="top" align="center">0.982</td>
</tr>
<tr>
<td valign="top" align="right">Q4 (0.62 - 3.26)</td>
<td valign="top" align="center">2.09 (1.20 - 3.64)</td>
<td valign="top" align="center">0.009</td>
<td valign="top" align="center">1.52 (0.84 - 3.07)</td>
<td valign="top" align="center">0.152</td>
</tr>
<tr>
<td valign="top" align="left">UA (&#x3bc;mol/L)</td>
<td valign="top" align="center">1.004 (1.002 - 1.007)</td>
<td valign="top" align="center">&lt; 0.001</td>
<td valign="top" align="center">1.004 (1.002 - 1.007)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="right">***Continuous, per SD</td>
<td valign="top" align="center">1.50 (1.21 - 1.86)</td>
<td valign="top" align="center">&lt; 0.001</td>
<td valign="top" align="center">1.49 (1.17 - 1.91)</td>
<td valign="top" align="center">0.001</td>
</tr>
<tr>
<td valign="top" align="right">Q1 (148 - 249)</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="right">Q2 (250 - 300)</td>
<td valign="top" align="center">0.65 (0.37 - 1.13)</td>
<td valign="top" align="center">0.127</td>
<td valign="top" align="center">0.68 (0.37 - 1.26)</td>
<td valign="top" align="center">0.223</td>
</tr>
<tr>
<td valign="top" align="right">Q3 (301 - 355)</td>
<td valign="top" align="center">0.83 (0.47 - 1.44)</td>
<td valign="top" align="center">0.502</td>
<td valign="top" align="center">0.79 (0.43 - 1.46)</td>
<td valign="top" align="center">0.453</td>
</tr>
<tr>
<td valign="top" align="right">Q4 (356 - 834)</td>
<td valign="top" align="center">1.80 (1.04 - 3.13)</td>
<td valign="top" align="center">0.037</td>
<td valign="top" align="center">1.59 (0.83 - 3.05)</td>
<td valign="top" align="center">0.161</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>
<sup>#</sup>Adjusted for age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, and hypertension (yes or no), UA, fasting C-peptide; *1 SD = 0.30 nmol/L; **1 SD = 0.32 C0/C2; ***1 SD = 91.45 &#x3bc;mol/L; C0/C2 ratio, fasting C-peptide-to-2h C-peptide ratio; UA, uric acid; OR, odds ratio. SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; HbA1c, glycated hemoglobin.</p>
</fn>
<fn>
<p>&#x201c;-&#x201d; means &#x201c;not applicable&#x201d;.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>RCS analysis based on logistic regression</title>
<p>
<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref> showed the association of renal dysfunction odds with the levels of fasting C-peptide, C0/C2 ratio and UA after adjustment for the potential confounders. The non-linear relationships of fasting C-peptide (p<sub>non-linear</sub> = 0.043) and UA (p<sub>non-linear</sub> = 0.009) with the renal dysfunction odds were observed, however, there was no non-linear relationship between C0/C2 ratio and the renal dysfunction odds (p<sub>non-linear</sub> = 0.561). These results indicated that although the odds of renal impairment increase with the increment of fasting C-peptide and/or UA levels in general, the relationships were not linear. Based on the RCS curves, both of the UA and fasting C-peptide variables were considered to divided into 3 categories for selecting the optimal cut-points, respectively. Finally, the optimal cut-points for UA were 276 and 409 &#x3bc;mol/L, and the optimal cut-points for fasting C-peptide were 0.28 and 0.56 nmol/L.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The RCS analysis based on logistic regression showed the association of renal dysfunction odds with the levels of Fasting C-peptide <bold>(A)</bold>, C0/C2 ratio <bold>(B)</bold> and UA <bold>(C)</bold> after adjustment for age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, and hypertension (yes or no). RCS, restricted cubic spline; C0/C2 ratio, fasting C-peptide-to-2h C-peptide ratio; UA, uric acid; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; HbA1c, glycated hemoglobin.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1157123-g001.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Threshold effects of fasting C-peptide and UA for renal dysfunction odds</title>
<p>The interval effects of fasting C-peptide and UA for renal dysfunction odds were evaluated using logistic regression analysis (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). After adjustment for age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, UA and hypertension (yes or no), the odds of renal impairment in the patients with fasting C-peptide &lt; 0.28 nmol/L and patients with fasting C-peptide &gt; 0.56 nmol/L relatively increased by about 38% and 85%, respectively, compared with that in the patients with 0.28 &#x2264; fasting C-peptide &#x2264; 0.56 nmol/L. Compared with patients with 276 &#x2264; UA &#x2264; 409 &#x3bc;mol/L, patients with UA &gt; 409 &#x3bc;mol/L significantly increased 5.24-folds odds (p &lt; 0.001) of renal dysfunction, although the increase of renal dysfunction odds in the subjects with UA &lt; 276 &#x3bc;mol/L had no statistical significance (OR = 1.32, p = 0.262).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Threshold effect analyses of fasting C-peptide and UA on the odds of renal dysfunction in patients with type 2 diabetes.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Variables</th>
<th valign="top" colspan="2" align="center">Univariate analyses</th>
<th valign="top" colspan="2" align="center">Multivariate analyses<sup>#</sup>
</th>
</tr>
<tr>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">p-value</th>
<th valign="top" align="center">OR (95% CI)</th>
<th valign="top" align="center">p-value</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="top" colspan="5" align="left">Fasting C-peptide (nmol/L)</th>
</tr>
<tr>
<td valign="top" align="right">0.28 - 0.56 nmol/L</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="right">&lt; 0.28nmol/L</td>
<td valign="top" align="center">1.55 (0.95 - 2.52)</td>
<td valign="top" align="center">0.080</td>
<td valign="top" align="center">1.38 (0.81 - 2.38)</td>
<td valign="top" align="center">0.246</td>
</tr>
<tr>
<td valign="top" align="right">&gt; 0.56 nmol/L</td>
<td valign="top" align="center">2.02 (1.26 - 3.23)</td>
<td valign="top" align="center">0.003</td>
<td valign="top" align="center">1.85 (1.10 - 3.12)</td>
<td valign="top" align="center">0.021</td>
</tr>
<tr>
<th valign="top" colspan="5" align="left">UA (&#x3bc;mol/L)</th>
</tr>
<tr>
<td valign="top" align="right">276 - 409 &#x3bc;mol/L</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center">1.0 (reference)</td>
<td valign="top" align="center">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="right">&lt; 276 &#x3bc;mol/L</td>
<td valign="top" align="center">1.29 (0.84 - 1.97)</td>
<td valign="top" align="center">0.238</td>
<td valign="top" align="center">1.32 (0.81 - 2.13)</td>
<td valign="top" align="center">0.262</td>
</tr>
<tr>
<td valign="top" align="right">&gt; 409 &#x3bc;mol/L</td>
<td valign="top" align="center">6.19 (3.00 - 12.80)</td>
<td valign="top" align="center">&lt; 0.001</td>
<td valign="top" align="center">6.24 (2.88 - 13.49)</td>
<td valign="top" align="center">&lt; 0.001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>
<sup>#</sup>Adjusted for age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, and hypertension (yes or no), UA, fasting C-peptide; UA, uric acid; OR, odds ratio; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; HbA1c, glycated hemoglobin.&#x201c;-&#x201d; means &#x201c;not applicable&#x201d;.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In the present study, we found that although fasting C-peptide, C0/C2 ratio and UA were independently associated with the odds of renal dysfunction in patients with T2DM, the probability of renal dysfunction did not linearly rise with the increase of serum fasting C-peptide and UA levels. Based on the RCS analysis, the renal impairment risk was non-linearly associated with the fasting C-peptide and UA levels after adjustment for the potential confounders, including age, gender, SBP, DBP, BMI, HbA1c level, diabetic duration, and hypertension (yes or no). Specifically, when 0.28 &#x2264; fasting C-peptide &#x2264; 0.56 nmol/L and/or when 276 &#x2264; UA &#x2264; 409 &#x3bc;mol/L, patients with T2DM might have the relatively lower renal dysfunction odds.</p>
<p>Chronic kidney disease is a very common complication of T2DM in clinical practice, its early diagnosis, intervention and treatment may have a critical impact on the delay of its progression to end-stage renal disease and the improvement of the patients prognosis (<xref ref-type="bibr" rid="B22">22</xref>). In recent years, the physiological function of C-peptide has been gradually discovered (<xref ref-type="bibr" rid="B11">11</xref>), C-peptide may block the activity of renal Na<sup>+</sup>-K<sup>+</sup>-ATPase, thus decreasing the Na<sup>+</sup> reabsorption by the proximal convoluted tubule and the glomerular filtration pressure (<xref ref-type="bibr" rid="B9">9</xref>); the decrease of C-peptide may also promote the occurrence of microvascular complications in patients with diabetes mellitus (<xref ref-type="bibr" rid="B23">23</xref>). Therefore, some researchers had focused on exploring the effects of exogenous human C-peptide supplementation on the improvement of DKD (<xref ref-type="bibr" rid="B24">24</xref>&#x2013;<xref ref-type="bibr" rid="B26">26</xref>). A clinical trial included twenty-one normotensive patients with microalbuminuria demonstrated that combined human C-peptide (600 nmol/24&#xa0;h) and insulin administration for 3 months might improve the kidney function by decreasing the urinary albumin excretion in patients with type 1 diabetes mellitus (<xref ref-type="bibr" rid="B24">24</xref>). An animal model study showed the similar findings that the supplementation of exogenous C-peptide could reduce the urinary albumin excretion and inhibit the upregulation of type IV collagen <italic>via</italic> interaction with the TGF-beta signal in glomerular podocytes in mouses with type 1 diabetes mellitus (<xref ref-type="bibr" rid="B25">25</xref>). However, Samneg&#xe5;rd B et&#xa0;al. conducted an animal study of 9 rats without diabetes and 22 rats with type 1 diabetes mellitus, they found that neither the albuminuria level nor the glomerular basement membrane had statistically significant improvement after the supplementation of exogenous C-peptide for 4 weeks (<xref ref-type="bibr" rid="B26">26</xref>). Most these previous study for C-peptide effects on DKD were conducted in patients or animals with type 1 diabetes mellitus (<xref ref-type="bibr" rid="B24">24</xref>&#x2013;<xref ref-type="bibr" rid="B26">26</xref>). In addition, the C-peptide levels fluctuated greatly in different stages of T2DM (<xref ref-type="bibr" rid="B27">27</xref>), therefore, the role of C-peptide in renal injury in patients with T2DM is still controversial and needs more studies.</p>
<p>In the present study, the association of C-peptide with the renal dysfunction odds in patients with T2DM was investigated. Compared with 2h postprandial C-peptide, fasting C-peptide was independently and significantly related with the renal dysfunction prevalence. Although on the whole the odds of renal impairment raised with increase of fasting C-peptide in the multivariate regression analysis using the continuous values, a non-linear relationship was showed between the renal dysfunction odds and the different stratification of fasting C-peptide. The study of Huang Y, et&#xa0;al. (<xref ref-type="bibr" rid="B23">23</xref>) demonstrated that among the patients with T2DM, these one with 1.71 &#x2264; C-peptide &lt; 2.51 ng/mL had a higher glycemic control rate, however, it did not clarify the specific relationships between the stratified C-peptide levels and the renal dysfunction odds. In this study, our findings showed that the patients with 0.28 &#x2264; fasting C-peptide &#x2264; 0.56 nmol/L had lower renal impairment chance compared with the patients with fasting C-peptide &lt; 0.28 nmol/L or fasting C-peptide &gt; 0.56 nmol/L. It indicated that moderate level of fasting C-peptide might be a clinically protective factor for renal impairment, on the contrary, low-level and excessive fasting C-peptide might be the risk factors for renal dysfunction in patients with T2DM. In addition, to a certain extent, the changes between fasting and postprandial C-peptide levels were correlated with the improvement of patient prognosis after intensive therapy, which reflected the reserve function of pancreatic &#x3b2; cell (<xref ref-type="bibr" rid="B28">28</xref>). Therefore, in the present study the correlation between C2/C0 ratio and renal dysfunction odds was also analyzed. Unlike fasting C-peptide, C2/C0 ratio did not show a statistically significant non-linear relationship with the odds of renal dysfunction.</p>
<p>A number of previous studies had shown the association between the UA levels and the kidney disease (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B29">29</xref>). The mechanisms of UA induced kidney disease had been identified by several preclinical studies (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). High UA levels induced and accelerated renal disease on their own without the deposition of UA crystals (<xref ref-type="bibr" rid="B29">29</xref>). Reducing the UA level by using xanthine oxidase inhibitor or a uricosuric agent in rats could prevent renal hypertrophy, and proteinuria (<xref ref-type="bibr" rid="B30">30</xref>). However, the clinical trials showed the divergent findings of the UA effects for predicting the incidence and development of chronic kidney disease in patients with diabetes (<xref ref-type="bibr" rid="B15">15</xref>, <xref ref-type="bibr" rid="B16">16</xref>). In the present study, we found that on the whole, the higher UA level was correlated with increased incidence of renal dysfunction, with a 49% increase in renal dysfunction odds for each SD (1 SD = 91.45 &#x3bc;mol/L) increment independently of potential confounders. In addition, to the best of our knowledge, there are no studies that have reported the U-shape association of serum UA level with renal dysfunction odds in patients with T2DM. Our findings showed the non-linear relationship between them, indicating that in a proper range, the renal impairment incidence did not rise with the increment of UA levels. Additionally, the previous studies had indicated that fasting C-peptide was significantly associated with UA in patients with T2DM (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>), however, no multiplication interaction effect between these two clinical factors for the renal dysfunction odds was found in the present study.</p>
<p>The highlights of the present study were that we conducted a real-world study and clarified the non-linear associations of fasting C-peptide and UA with the incidence of renal impairment in patients with T2DM. However, several potential limitations of this study are worth noting. First, we did not assess <italic>post-hoc</italic> statistical power and the statistical power achieved for the main outcome measure in the present study. Second, this was a cross-sectional observational study, these findings could not provide strong evidences of the non-linear associations of the new-onset occurrence odds of renal dysfunction with the C-peptide and UA levels. Generally, this exploratory study highlighted and paved the way for the need to design and conduct a prospective confirmatory study in a random sample with the proper dimension that demonstrated evidence of a non-linear association of new cases of renal dysfunction with C-peptide and UA levels.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>In conclusion, the odds of renal dysfunction was non-linearly associated with the levels of serum fasting C-peptide and UA. When 0.28 &#x2264; fasting C-peptide &#x2264; 0.56 nmol/L and/or when 276 &#x2264; UA &#x2264; 409 &#x3bc;mol/L, patients with T2DM might have the relatively lower renal dysfunction odds. Our results suggested that fasting C-peptide and UA might have the potential role in odds stratification of renal dysfunction, and provided laboratory evidence for prevention and treatment of renal disease in patients with T2DM and no primary kidney diseases, serious autoimmune diseases, liver diseases and/or infectious diseases.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving human participants were reviewed and approved by Ethics Committee of Affiliated Jinhua Hospital, Zhejiang University School of Medicine. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>Study design: LC, YH, and HW; Statistical analysis: HW and YM; Manuscript writing: LC and HW; Data collection: LC and YH. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>This research received the grant from Science Technology Department of Zhejiang province, China (LGF22H200021), Jinhua Science and Technology Bureau (2021-3-088), Medical Science and Technology Project of Zhejiang Province (2021KY384).</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We thank all the participants and all the colleagues of department of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine.</p>
</ack>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The 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="s11" sec-type="disclaimer">
<title>Publisher&#x2019;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>
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