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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Surg.</journal-id>
<journal-title>Frontiers in Surgery</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Surg.</abbrev-journal-title>
<issn pub-type="epub">2296-875X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fsurg.2022.815303</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Surgery</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Comparison of Clinical Data Between Patients With Complications and Without Complications After Spinal Tuberculosis Surgery: A Propensity Score Matching Analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Chen</surname> <given-names>Liyi</given-names></name>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
</contrib>
<contrib contrib-type="author">
<name><surname>Liu</surname> <given-names>Chong</given-names></name>
<xref ref-type="author-notes" rid="fn002"><sup>&#x02020;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1356435/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Ye</surname> <given-names>Zhen</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Chen</surname> <given-names>Wuhua</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Sun</surname> <given-names>Xuhua</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Chen</surname> <given-names>Jiarui</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Li</surname> <given-names>Hao</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Liang</surname> <given-names>Tuo</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/941179/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Huang</surname> <given-names>Shengsheng</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Jiang</surname> <given-names>Jie</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Chen</surname> <given-names>Tianyou</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/1284315/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Guo</surname> <given-names>Hao</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Yao</surname> <given-names>Yuanlin</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Liao</surname> <given-names>Shian</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/1284541/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Yu</surname> <given-names>Chaojie</given-names></name>
<uri xlink:href="http://loop.frontiersin.org/people/1280266/overview"/>
</contrib>
<contrib contrib-type="author">
<name><surname>Wu</surname> <given-names>Shaofeng</given-names></name>
</contrib>
<contrib contrib-type="author">
<name><surname>Fan</surname> <given-names>Binguang</given-names></name>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Zhan</surname> <given-names>Xinli</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>&#x0002A;</sup></xref>
<uri xlink:href="http://loop.frontiersin.org/people/1462472/overview"/>
</contrib>
</contrib-group>
<aff><institution>First Affiliated Hospital, Guangxi Medical University</institution>, <addr-line>Nanning</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by"><p>Edited by: Ingo Marzi, Goethe University Frankfurt, Germany</p></fn>
<fn fn-type="edited-by"><p>Reviewed by: Piotr Yablonskii, St-Petersburg Research Institute of Phthisiopulmonology, Russia; Rizaldy Taslim Pinzon, Duta Wacana Christian University, Indonesia</p></fn>
<corresp id="c001">&#x0002A;Correspondence: Xinli Zhan <email>zhanxinli&#x00040;stu.gxmu.edu.cn</email></corresp>
<fn fn-type="other" id="fn001"><p>This article was submitted to Orthopedic Surgery, a section of the journal Frontiers in Surgery</p></fn>
<fn fn-type="equal" id="fn002"><p>&#x02020;These authors have contributed equally to this work and share first authorship</p></fn></author-notes>
<pub-date pub-type="epub">
<day>29</day>
<month>03</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>9</volume>
<elocation-id>815303</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>11</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>07</day>
<month>03</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2022 Chen, Liu, Ye, Chen, Sun, Chen, Li, Liang, Huang, Jiang, Chen, Guo, Yao, Liao, Yu, Wu, Fan and Zhan.</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Chen, Liu, Ye, Chen, Sun, Chen, Li, Liang, Huang, Jiang, Chen, Guo, Yao, Liao, Yu, Wu, Fan and Zhan</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>Purpose</title>
<p>This study used a propensity score matching (PSM) analysis to explore the risk factors of post-operative complications and compared the differences in clinical data between them following spinal tuberculosis surgery.</p></sec>
<sec>
<title>Methods</title>
<p>The clinical data of patients with spinal tuberculosis were collected in our hospital from June 2012 to June 2021, including general information, laboratory results, surgical information, and hospitalization costs. The data were divided into two groups: complication and without complication groups. The baseline data of the two groups were obtained using the PSM analysis. Univariate and multivariate logistic analyses were used to analyze the differences between the two groups.</p></sec>
<sec>
<title>Results</title>
<p>A total of 292 patients were included in the PSM analysis: 146 patients with complications and 146 patients without complications. The operation time, incision length, hospital stay, and albumin quantity in the complications group were 162 &#x000B1; 74.1, 11.2 &#x000B1; 4.76, 14.7 &#x000B1; 9.34, and 1.71 &#x000B1; 2.82, respectively, and those in the without complication group were 138 &#x000B1; 60.5, 10.2 &#x000B1; 3.56, 11.7 &#x000B1; 7.44, and 0.740 &#x000B1; 2.44, respectively. The laboratory costs, examination costs, guardianship costs, oxygen costs, and total costs in the complications group were higher than those in the without complication group. A significant difference was observed in the albumin quantity by logistic regression analysis (<italic>P</italic> &#x0003C; 0.05).</p></sec>
<sec>
<title>Conclusion</title>
<p>Several costs in the complication group were higher than in the without complication group. The albumin quantity may be an independent factor to predict post-operative complications of spinal tuberculosis by logistic regression analysis.</p></sec></abstract>
<kwd-group>
<kwd>propensity score matching</kwd>
<kwd>logistic</kwd>
<kwd>complications</kwd>
<kwd>spinal tuberculosis</kwd>
<kwd>albumin</kwd>
</kwd-group>
<contract-num rid="cn001">81560359</contract-num>
<contract-num rid="cn001">81860393</contract-num>
<contract-sponsor id="cn001">National Natural Science Foundation of China<named-content content-type="fundref-id">10.13039/501100001809</named-content></contract-sponsor>
<counts>
<fig-count count="8"/>
<table-count count="7"/>
<equation-count count="0"/>
<ref-count count="50"/>
<page-count count="13"/>
<word-count count="7213"/>
</counts>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="s1">
<title>Introduction</title>
<p>Spinal tuberculosis is the most common form of extrapulmonary tuberculosis (<xref ref-type="bibr" rid="B1">1</xref>). It has become a major health concern in developing countries due to the emergence of drug-resistant strains (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). Surgical treatment is known to be the best solution in case the anti-tuberculosis treatment fails (<xref ref-type="bibr" rid="B4">4</xref>). However, surgeries are sometimes associated with certain unexpected complications. The results of Zhou et al.&#x00027;s study revealed that 102 patients with L1&#x02013;2 vertebral tuberculosis had 14 patients with pulmonary complications after the surgery (<xref ref-type="bibr" rid="B5">5</xref>). Zhuang et al. applied oblique lateral interbody fusion to lumbar spinal tuberculosis with 10 (16.95%) complications, including peritoneal injury, neurological injury, infection of incisions, segmental artery, iliac vein lacerations, and instrument failure. However, the anterior-only approach was associated with 37.5% complications (<xref ref-type="bibr" rid="B4">4</xref>). Similarly, Susanta et al. reported one case (2.3%) of sinus formation and two cases (4.7%) of superficial wound infection after thoracic tuberculosis surgery (<xref ref-type="bibr" rid="B6">6</xref>). Surgeons should completely understand the surgical approach and post-operative complications of spinal tuberculosis, which is of great significance in treating the disease (<xref ref-type="bibr" rid="B7">7</xref>).</p>
<p>The global tuberculosis situation is particularly tense in developing countries. The incidence of pulmonary or spinal tuberculosis is low in developed countries, however, the incidence is high in developing countries. The incidence of tuberculosis is high in the African region, which accounted for 71% of global tuberculosis and AIDS cases in 2018 (<xref ref-type="bibr" rid="B8">8</xref>). The backward economies of developing countries cannot provide good sanitation and treatment facilities, which is also the reason for the high incidence of tuberculosis (<xref ref-type="bibr" rid="B9">9</xref>). Insufficient course of antituberculosis therapy after spinal tuberculosis surgery due to financial burden, which may increase the recurrence of spinal surgery.</p>
<p>In the past, our team&#x00027;s research had found that there were various complications of spine surgery. There was a potential risk of cerebrospinal fluid leakage and reduced albumin after surgery for spinal tuberculosis (<xref ref-type="bibr" rid="B10">10</xref>, <xref ref-type="bibr" rid="B11">11</xref>). In addition, we also found a risk of internal fixation failure following spinal surgery (<xref ref-type="bibr" rid="B12">12</xref>). In a recent study of spinal tuberculosis, our team found that spinal tuberculosis was prone to recurrence after surgery and the risk of pulmonary embolism after multiple surgical treatments (<xref ref-type="bibr" rid="B13">13</xref>). Therefore, we collected a large number of clinical data on spinal tuberculosis surgery with the aim of predicting the risk of complications of spinal tuberculosis.</p>
<p>Although PSM analysis has been favored in spinal surgery, including cervical spine surgery (<xref ref-type="bibr" rid="B14">14</xref>), thoracic surgery (<xref ref-type="bibr" rid="B15">15</xref>), and lumbar spine surgery (<xref ref-type="bibr" rid="B16">16</xref>), only a few reports are available on spinal tuberculosis with PSM analysis. However, a combination of PSM analysis and logistic regression analysis for spinal tuberculosis analysis has not been reported. This study was the first to apply a combination of PSM analysis and logistic regression analysis to study the complications after spinal tuberculosis. We compared the clinical data of complication and without complication groups and explored the factors related to complications after tuberculosis surgery.</p></sec>
<sec sec-type="materials and methods" id="s2">
<title>Materials and Methods</title>
<p>The clinical data of patients with spinal tuberculosis were collected in our hospital from June 2012 to June 2021, including general information, laboratory results, surgical information, post-operative complications, and hospitalization costs. A total of 495 patients were enrolled in the study, including 298 males and 197 females. All data were divided into two groups: complication group with 146 patients (<xref ref-type="fig" rid="F1">Figures 1</xref>&#x02013;<xref ref-type="fig" rid="F3">3</xref>) and without complication group with 349 patients. In this study, 292 patients were included in the PSM analysis: 146 patients in the complication group and 146 patients in the without complication group. The criteria for inclusion were as follows: (1) without other diseases that affected post-operative recovery except hypertension and diabetes, (2) diagnosed with spine tuberculosis by pathological examination, (3) without a history of surgery affecting the spine, (4) complete clinical data, and (5) Lesions involving any part of the spine, including cervical, thoracic, lumbar, and sacral. The criteria for exclusion were as follows: (1) other diseases that affected post-operative recovery except for hypertension and diabetes, (2) without diagnosis of spinal tuberculosis by pathological examination, (3) with a history of surgery affecting the spine, and (4) incomplete clinical data. Post-operative complications of spinal tuberculosis were defined as post-operative wound infection or systemic infection, failure of internal fixation, recurrence of tuberculosis, and surgery-related diseases such as pulmonary embolism, cerebral infarction, and myocardial infarction. According to the fixed vertebral body at the upper end and the fixed vertebral body at the lower end, we choose the appropriate length of incision. &#x0201C;Bottle&#x0201D; was defined as the unit of measurement for albumin quantity. Each bottle of albumin injection was 50 ml, of which albumin accounted for 20%. This study was approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University.</p>
<fig id="F1" position="float">
<label>Figure 1</label>
<caption><p>A typical case of post-operative pleural effusion after spinal tuberculosis. The arrow marks the location of the pleural effusion. <bold>(A)</bold> Post-operative X-ray image in the posterior&#x02013;anterior position. <bold>(B)</bold> Post-operative CT image in the coronal position. <bold>(C)</bold> Post-operative CT image in the cross-section.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0001.tif"/>
</fig>
<fig id="F2" position="float">
<label>Figure 2</label>
<caption><p>A typical case of post-operative wound infection of spinal tuberculosis. The arrow marks the location of inflammatory pus. <bold>(A)</bold> Post-operative MRI image of the sagittal position T1 sequence. <bold>(B)</bold> Post-operative MRI image of the sagittal position T2 sequence. <bold>(C)</bold> Post-operative MRI image of the cross-section T1 sequence. <bold>(D)</bold> Post-operative MRI image of the cross-section T2 sequence.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0002.tif"/>
</fig>
<fig id="F3" position="float">
<label>Figure 3</label>
<caption><p>A typical case of pedicle screw fracture after spinal tuberculosis surgery. The arrow marks the location of pedicle screw fracture. <bold>(A)</bold> Post-operative X-ray image in the posterior&#x02013;anterior position. <bold>(B)</bold> Post-operative X-ray image in the lateral position. <bold>(C)</bold> Post-operative CT image in the cross-section. <bold>(D)</bold> Post-operative CT reconstruction image in the coronal position. <bold>(E)</bold> Post-operative CT reconstruction image in the sagittal position. <bold>(F)</bold> Post-operative CT reconstruction image in the cross-section.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0003.tif"/>
</fig>
<sec>
<title>Data Collection</title>
<p>The general information of patients who underwent spinal tuberculosis surgery in our hospital was collected, including gender, body mass index (BMI), age, hypertension, diabetes, lesion segment, medical history, marriage, systolic blood pressure, diastolic blood pressure, pain, lower limb pain, number of lower limb pain, fatigue, fever, night sweats, appetite, weight loss, Oswestry Disability Index (ODI), Japanese Orthopedic Association (JOA) scores, visual analog scale (VAS), American Spinal Injury Association (ASIA) impairment scale, occupation, race, days before surgery, smoking, and drinking. The laboratory results of patients were collected, including blood glucose, blood type, C-reactive protein (CRP), hepatitis B surface antigen, white blood cells, hemoglobin, platelets, percentage of neutrophils, percentage of lymphocytes, absolute monocytes, percentage of monocytes, total bilirubin, direct bilirubin, indirect bilirubin, total protein, albumin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), AST/ALT, blood urea, blood creatinine, blood uric acid, and erythrocyte sedimentation rate. The surgical information of patients was collected, including titanium cage, internal fixation, abscess, albumin quantity, recurrence, surgical approach, hospital stay, transfusion, local streptomycin, operation time, bleeding volume, red blood cell transfusion, drainage, kyphosis, post-operative complications, and incision length. The hospitalization costs of patients were collected, including antibacterial costs, western medicine costs, surgical costs, anesthesia costs, laboratory costs, examination costs, guardianship costs, transfusion costs, oxygen costs, high consumable costs, care costs, consultation fees, and total costs. Antibacterial costs were defined as the cost of treatment with antibiotics such as penicillin, streptomycin and cefuroxime etc. Western medicine costs were defined as the cost of oral medication such as painkillers, omeprazole and glutathione etc. Surgical costs were defined as the cost of lesion removal, bone graft fusion, reconstruction of spinal stability, etc., but did not include the cost of purchasing internal fixation devices. High consumable costs were defined as the purchase of internal fixation devices such as pedicle screws, titanium cages. Anesthesia costs were defined as the cost of anesthesia during surgery. Laboratory costs were defined as the cost of blood tests before and after surgery. Examine costs were defined as the cost of pre-operative and post-operative imaging examinations, such as X-ray, CT, MRI, etc. Guardianship costs were defined as the cost of monitoring vital signs after surgery. Transfusion costs were defined as the cost of blood transfusions during hospitalization. Oxygen costs were defined as the cost of oxygen therapy during hospitalization. Care costs were defined as the costs of nurses serving patients during hospital stays. Consultation costs were defined as the cost of asking other departments for consultation and treatment during hospitalization. Total costs were defined as the total cost of hospitalization.</p></sec>
<sec>
<title>Statistical Analysis</title>
<p>The propensity score usually includes four methods, namely covariate adjustment using the propensity score, matching on the propensity score, stratification on the propensity score, and inverse probability of treatment weighting using the propensity score. The most popular of these in medical research is matching on the propensity score (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>). Khawar et al. constructed groups for propensity score matching research based on outcomes after hip fractures sustained in the hospital (<xref ref-type="bibr" rid="B19">19</xref>). Omar et al. constructed the non-elderly group and the elderly group after robotic ventral hernia repair for PSM research (<xref ref-type="bibr" rid="B20">20</xref>). Maze et al. used the PSM method to analyze the clinical data according to the presence or absence of intracranial hemorrhage (<xref ref-type="bibr" rid="B21">21</xref>). We referred to previous research strategies and used the PSM method to analyze the clinical data based on the presence or absence of complications after spinal tuberculosis surgery. PSM can reduce the interference factors of the outcome after matching the baseline data of treatment and control groups (<xref ref-type="bibr" rid="B22">22</xref>, <xref ref-type="bibr" rid="B23">23</xref>). Although PSM analysis has been favored in spinal surgery, including cervical spine surgery (<xref ref-type="bibr" rid="B14">14</xref>), thoracic surgery (<xref ref-type="bibr" rid="B15">15</xref>), and lumbar spine surgery (<xref ref-type="bibr" rid="B16">16</xref>), only a few reports are available on spinal tuberculosis with PSM analysis.</p>
<p>Univariate and multivariate analyses were usually applied to the analysis of related factors in the study of spinal tuberculosis. A study by Surachai et al. used logistic regression analysis and found that signal cord change and notable Cobb angle could be used as predictive factors for the neurological deficit in spinal tuberculosis (<xref ref-type="bibr" rid="B24">24</xref>). Moreover, Wang et al. used logistic regression analysis and found that the independent risk factors of lower extremity motor or sensory deficits were age, worrying of sickness, location, and spinal compression in patients with spinal tuberculosis (<xref ref-type="bibr" rid="B25">25</xref>).</p>
<p>The RStudio software (version 1.4.1717) and R software (version 4.1.0) were used for data analysis. To eliminate the confounding factors that affected the results, we selected certain parameters for the PSM analysis, including gender, BMI, age, hypertension, diabetes, abscess, titanium cage, internal fixation, percentage of lymphocytes, albumin, and lesion segment. The balance of the matched data was tested using the classical method; the alpha was set to 5. In addition, the balance of the matched data was tested using the standard difference method; the alpha was set to 15. The data following the PSM analysis were included in univariate analysis. We refer to previous published articles (<xref ref-type="bibr" rid="B26">26</xref>, <xref ref-type="bibr" rid="B27">27</xref>), and on the basis of fully considering the clinical significance and statistical significance of the parameters. Parameters with <italic>P</italic> &#x0003C;0.1 in the univariate analysis were included in the multivariate logistic regression analysis. The validity of the logistic regression model was evaluated by the receiver operating characteristic (ROC) curve. The statistical difference was considered as <italic>P</italic>-value &#x0003C;0.05.</p></sec></sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<p>There were differences in baseline data before propensity matching, but none were statistically significant after propensity matching (<xref ref-type="table" rid="T1">Table 1</xref>). The histogram showed a difference between categorical variables, including gender (<xref ref-type="fig" rid="F4">Figure 4A</xref>), hypertension (<xref ref-type="fig" rid="F4">Figure 4B</xref>), diabetes (<xref ref-type="fig" rid="F4">Figure 4C</xref>), abscess (<xref ref-type="fig" rid="F4">Figure 4D</xref>), titanium cage (<xref ref-type="fig" rid="F4">Figure 4E</xref>), and internal fixation (<xref ref-type="fig" rid="F4">Figure 4F</xref>), before and after matching. The frequency distribution graph showed a difference in quantitative variables, including BMI (<xref ref-type="fig" rid="F5">Figure 5A</xref>), age (<xref ref-type="fig" rid="F5">Figure 5B</xref>), percentage of lymphocytes (<xref ref-type="fig" rid="F5">Figure 5C</xref>), albumin (<xref ref-type="fig" rid="F5">Figure 5D</xref>), and lesion segment (<xref ref-type="fig" rid="F5">Figure 5E</xref>) before and after matching. The balance of the standardized differences of covariates was evaluated using the standard difference method; the results showed that the standardized difference of the matched data was significantly smaller than that of the unmatched data (<xref ref-type="fig" rid="F5">Figure 5F</xref>).</p>
<table-wrap position="float" id="T1">
<label>Table 1</label>
<caption><p>Baseline data before and after propensity score matching analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>Before propensity score-matching</bold></th>
<th valign="top" align="center" colspan="3" style="border-bottom: thin solid #000000;"><bold>After propensity score-matching</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 349</bold></th>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 349</bold></th>
<th/>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 349</bold></th>
<th valign="top" align="center"><italic><bold>N</bold></italic> <bold>&#x0003D; 349</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Gender (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Female</td>
<td valign="top" align="center">151 (43.3)</td>
<td valign="top" align="center">47 (32.2)</td>
<td valign="top" align="center">0.028<xref ref-type="table-fn" rid="TN1"><sup>&#x0002A;</sup></xref></td>
<td valign="top" align="center">49 (33.6)</td>
<td valign="top" align="center">47 (32.2)</td>
<td valign="top" align="center">0.901</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Male</td>
<td valign="top" align="center">198 (56.7)</td>
<td valign="top" align="center">99 (67.8)</td>
<td/>
<td valign="top" align="center">97 (66.4)</td>
<td valign="top" align="center">99 (67.8)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Titanium cage (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">196 (56.2)</td>
<td valign="top" align="center">69 (47.3)</td>
<td valign="top" align="center">0.087</td>
<td valign="top" align="center">72 (49.3)</td>
<td valign="top" align="center">69 (47.3)</td>
<td valign="top" align="center">0.815</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">153 (48.3)</td>
<td valign="top" align="center">77 (52.7)</td>
<td/>
<td valign="top" align="center">74 (50.7)</td>
<td valign="top" align="center">77 (52.7)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;BMI [mean (SD)]</td>
<td valign="top" align="center">20.25 (3.20)</td>
<td valign="top" align="center">20.80 (3.32)</td>
<td valign="top" align="center">0.084</td>
<td valign="top" align="center">20.49 (3.25)</td>
<td valign="top" align="center">20.80 (3.32)</td>
<td valign="top" align="center">0.414</td>
</tr>
<tr>
<td valign="top" align="left">Internal fixation (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">36 (10.3)</td>
<td valign="top" align="center">19 (13.0)</td>
<td valign="top" align="center">0.475</td>
<td valign="top" align="center">18 (12.3)</td>
<td valign="top" align="center">19 (13.0)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">313 (89.7)</td>
<td valign="top" align="center">127 (87.0)</td>
<td/>
<td valign="top" align="center">128 (87.7)</td>
<td valign="top" align="center">127 (87.0)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Age [mean (SD)]</td>
<td valign="top" align="center">49.81 (17.89)</td>
<td valign="top" align="center">51.08 (16.48)</td>
<td valign="top" align="center">0.461</td>
<td valign="top" align="center">51.73 (16.54)</td>
<td valign="top" align="center">51.08 (16.48)</td>
<td valign="top" align="center">0.739</td>
</tr>
<tr>
<td valign="top" align="left">Hypertension (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">316 (90.5)</td>
<td valign="top" align="center">134 (91.8)</td>
<td valign="top" align="center">0.791</td>
<td valign="top" align="center">135 (92.5)</td>
<td valign="top" align="center">134 (91.8)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">33 (9.5)</td>
<td valign="top" align="center">12 (8.2)</td>
<td/>
<td valign="top" align="center">11 (7.5)</td>
<td valign="top" align="center">12 (8.2)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Diabetes (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">337 (96.6)</td>
<td valign="top" align="center">139 (95.2)</td>
<td valign="top" align="center">0.646</td>
<td valign="top" align="center">139 (95.2)</td>
<td valign="top" align="center">139 (95.2)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">12 (3.4)</td>
<td valign="top" align="center">7 (4.8)</td>
<td/>
<td valign="top" align="center">7 (4.8)</td>
<td valign="top" align="center">7 (4.8)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Abscess (%)</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">96 (27.5)</td>
<td valign="top" align="center">22 (15.1)</td>
<td valign="top" align="center">0.004<xref ref-type="table-fn" rid="TN2"><sup>&#x0002A;&#x0002A;</sup></xref></td>
<td valign="top" align="center">17 (11.6)</td>
<td valign="top" align="center">22 (15.1)</td>
<td valign="top" align="center">0.491</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">253 (72.5)</td>
<td valign="top" align="center">124 (84.9)</td>
<td/>
<td valign="top" align="center">129 (88.4)</td>
<td valign="top" align="center">124 (84.9)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Percentage of lymphocytes [mean (SD)]</td>
<td valign="top" align="center">0.24 (0.10)</td>
<td valign="top" align="center">0.22 (0.11)</td>
<td valign="top" align="center">0.028<xref ref-type="table-fn" rid="TN1"><sup>&#x0002A;</sup></xref></td>
<td valign="top" align="center">0.23 (0.09)</td>
<td valign="top" align="center">0.22 (0.11)</td>
<td valign="top" align="center">0.38</td>
</tr>
<tr>
<td valign="top" align="left">Albumin [mean (SD)]</td>
<td valign="top" align="center">38.43 (5.91)</td>
<td valign="top" align="center">36.61 (4.96)</td>
<td valign="top" align="center">0.001<xref ref-type="table-fn" rid="TN2"><sup>&#x0002A;&#x0002A;</sup></xref></td>
<td valign="top" align="center">36.78 (5.45)</td>
<td valign="top" align="center">36.61 (4.96)</td>
<td valign="top" align="center">0.779</td>
</tr>
<tr>
<td valign="top" align="left">Number of vertebrae [mean (SD)]</td>
<td valign="top" align="center">2.17 (0.84)</td>
<td valign="top" align="center">2.36 (0.91)</td>
<td valign="top" align="center">0.024<xref ref-type="table-fn" rid="TN1"><sup>&#x0002A;</sup></xref></td>
<td valign="top" align="center">2.36 (1.07)</td>
<td valign="top" align="center">2.36 (0.91)</td>
<td valign="top" align="center">1</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN1"><label>&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.05</italic>.</p></fn> 
<fn id="TN2"><label>&#x0002A;&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.01</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="F4" position="float">
<label>Figure 4</label>
<caption><p>Comparison of grade clinical data between complication and without complication groups before and after propensity score matching analysis. <bold>(A)</bold> Gender. <bold>(B)</bold> Hypertension. <bold>(C)</bold> Diabetes. <bold>(D)</bold> Abscess. <bold>(E)</bold> Titanium cage. <bold>(F)</bold> Internal fixation.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0004.tif"/>
</fig>
<fig id="F5" position="float">
<label>Figure 5</label>
<caption><p>Comparison of continuous clinical data between complication and without complication groups before and after the propensity score matching analysis. <bold>(A)</bold> BMI. <bold>(B)</bold> Age. <bold>(C)</bold> Percentage of lymphocytes. <bold>(D)</bold> Albumin. <bold>(E)</bold> Lesion segment. <bold>(F)</bold> Standardized differences of covariates.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0005.tif"/>
</fig>
<p>The general data between the two groups using the PSM analysis revealed that the <italic>P</italic>-value of appetite and occupation was &#x0003C;0.1, and that of other parameters was more than 0.1 (<xref ref-type="table" rid="T2">Table 2</xref>). The laboratory results showed that only the comparison of AST/ALT between the two groups was &#x0003C;0.1 (<italic>P</italic> = 0.067), and there were no significant differences in other parameters (<xref ref-type="table" rid="T3">Table 3</xref>). The albumin quantity (<xref ref-type="fig" rid="F6">Figure 6A</xref>), operation time (<xref ref-type="fig" rid="F6">Figure 6B</xref>), incision length (<xref ref-type="fig" rid="F6">Figure 6C</xref>), and hospital stay (<xref ref-type="fig" rid="F7">Figure 7F</xref>) in the complication group were 1.71 &#x000B1; 2.82 bottles, 162 &#x000B1; 74.1 min, 11.2 &#x000B1; 4.76 cm, and 14.7 &#x000B1; 9.34 days, respectively, and these values in the without complication group were 0.740 &#x000B1; 2.44 bottles, 138 &#x000B1; 60.5 min, 10.2 &#x000B1; 3.56 cm, and 11.7 &#x000B1; 7.44 days, respectively (<xref ref-type="table" rid="T4">Table 4</xref>). There were statistical differences between the two groups (<italic>P</italic> &#x0003C; 0.05). In addition, there were statistical differences in the surgical approach between the two groups (<italic>P</italic> &#x0003C; 0.1). The laboratory costs (<xref ref-type="fig" rid="F7">Figure 7A</xref>), examination costs (<xref ref-type="fig" rid="F7">Figure 7B</xref>), guardianship costs (<xref ref-type="fig" rid="F7">Figure 7C</xref>), oxygen costs (<xref ref-type="fig" rid="F7">Figure 7D</xref>), and total costs (<xref ref-type="fig" rid="F7">Figure 7E</xref>) in the complication group were 2,900 &#x000B1; 2,080 RMB, 425 &#x000B1; 826 RMB, 791 &#x000B1; 1,940 RMB, 154 &#x000B1; 210 RMB, and 51,700 &#x000B1; 31,800 RMB, respectively, and those in the without complication group were 2,280 &#x000B1; 1,360 RMB, 272 &#x000B1; 422 RMB, 441 &#x000B1; 186 RMB, 103 &#x000B1; 106 RMB, and 42,800 &#x000B1; 24,200 RMB, respectively (<xref ref-type="table" rid="T5">Table 5</xref>). These costs were higher in the complication group than in the without complication group (<italic>P</italic> &#x0003C; 0.05). There were no significant differences in other costs, including antibacterial costs, western medicine costs, surgical costs, anesthesia costs, transfusion costs, high consumable costs, care costs, and consultation costs, between the two groups (<italic>P</italic> &#x0003E; 0.05).</p>
<table-wrap position="float" id="T2">
<label>Table 2</label>
<caption><p>General information comparison between complication and without complication groups after propensity score matching analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="4">Gender</td>
<td/>
<td/>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Female</td>
<td valign="top" align="center">49 (34%)</td>
<td valign="top" align="center">47 (32%)</td>
<td valign="top" align="center">0.901</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Male</td>
<td valign="top" align="center">97 (66%)</td>
<td valign="top" align="center">99 (68%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">BMI</td>
<td valign="top" align="center">20.5 &#x000B1; 3.25</td>
<td valign="top" align="center">20.8 &#x000B1; 3.32</td>
<td valign="top" align="center">0.414</td>
</tr>
<tr>
<td valign="top" align="left">Age</td>
<td valign="top" align="center">51.7 &#x000B1; 16.5</td>
<td valign="top" align="center">51.1 &#x000B1; 16.5</td>
<td valign="top" align="center">0.739</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Hypertension</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">135 (92%)</td>
<td valign="top" align="center">134 (92%)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">11 (8%)</td>
<td valign="top" align="center">12 (8%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Diabetes</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">139 (95%)</td>
<td valign="top" align="center">139 (95%)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">7 (5%)</td>
<td valign="top" align="center">7 (5%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Lesion segment</td>
<td valign="top" align="center">2.36 &#x000B1; 1.07</td>
<td valign="top" align="center">2.36 &#x000B1; 0.909</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">Medical history (months)</td>
<td valign="top" align="center">10.8 &#x000B1; 32.3</td>
<td valign="top" align="center">7.60 &#x000B1; 13.0</td>
<td valign="top" align="center">0.271</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Marriage</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">20 (14%)</td>
<td valign="top" align="center">16 (11%)</td>
<td valign="top" align="center">0.593</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">126 (86%)</td>
<td valign="top" align="center">130 (89%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Systolic blood pressure (mmHg)</td>
<td valign="top" align="center">127 &#x000B1; 18.6</td>
<td valign="top" align="center">128 &#x000B1; 20.3</td>
<td valign="top" align="center">0.659</td>
</tr>
<tr>
<td valign="top" align="left">Diastolic blood pressure (mmHg)</td>
<td valign="top" align="center">79.8 &#x000B1; 11.6</td>
<td valign="top" align="center">78.7 &#x000B1; 11.5</td>
<td valign="top" align="center">0.417</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Pain</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">7 (5%)</td>
<td valign="top" align="center">4 (3%)</td>
<td valign="top" align="center">0.539</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">139 (95%)</td>
<td valign="top" align="center">142 (97%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Lower limb pain</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">66 (45%)</td>
<td valign="top" align="center">69 (47%)</td>
<td valign="top" align="center">0.814</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">80 (55%)</td>
<td valign="top" align="center">77 (53%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Number of lower limb pain</td>
<td valign="top" align="center">0.959 &#x000B1; 0.931</td>
<td valign="top" align="center">0.897 &#x000B1; 0.908</td>
<td valign="top" align="center">0.567</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Fatigue</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">106 (73%)</td>
<td valign="top" align="center">106 (73%)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">40 (27%)</td>
<td valign="top" align="center">40 (27%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Fever</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">102 (70%)</td>
<td valign="top" align="center">109 (75%)</td>
<td valign="top" align="center">0.433</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">44 (30%)</td>
<td valign="top" align="center">37 (25%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Night sweats</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">113 (77%)</td>
<td valign="top" align="center">119 (82%)</td>
<td valign="top" align="center">0.469</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">33 (23%)</td>
<td valign="top" align="center">27 (18%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Appetite</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">65 (45%)</td>
<td valign="top" align="center">48 (33%)</td>
<td valign="top" align="center">0.055<xref ref-type="table-fn" rid="TN3"><sup>&#x00023;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">81 (55%)</td>
<td valign="top" align="center">98 (67%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Weight loss (Kg)</td>
<td valign="top" align="center">2.70 &#x000B1; 3.59</td>
<td valign="top" align="center">2.21 &#x000B1; 3.47</td>
<td valign="top" align="center">0.237</td>
</tr>
<tr>
<td valign="top" align="left">ODI</td>
<td valign="top" align="center">17.9 &#x000B1; 8.45</td>
<td valign="top" align="center">17.9 &#x000B1; 8.45</td>
<td valign="top" align="center">0.95</td>
</tr>
<tr>
<td valign="top" align="left">JOA</td>
<td valign="top" align="center">18.0 &#x000B1; 6.26</td>
<td valign="top" align="center">17.7 &#x000B1; 6.08</td>
<td valign="top" align="center">0.684</td>
</tr>
<tr>
<td valign="top" align="left">VAS</td>
<td valign="top" align="center">7.34 &#x000B1; 1.49</td>
<td valign="top" align="center">7.32 &#x000B1; 1.37</td>
<td valign="top" align="center">0.903</td>
</tr>
<tr>
<td valign="top" align="left">ASIA</td>
<td valign="top" align="center">4.48 &#x000B1; 0.896</td>
<td valign="top" align="center">4.52 &#x000B1; 0.865</td>
<td valign="top" align="center">0.69</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Occupation</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Non-farmer</td>
<td valign="top" align="center">64 (44%)</td>
<td valign="top" align="center">49 (34%)</td>
<td valign="top" align="center">0.093&#x00023;</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Farmer</td>
<td valign="top" align="center">82 (56%)</td>
<td valign="top" align="center">97 (66%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Race</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Non-Han</td>
<td valign="top" align="center">66 (45%)</td>
<td valign="top" align="center">76 (52%)</td>
<td valign="top" align="center">0.292</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Han</td>
<td valign="top" align="center">80 (55%)</td>
<td valign="top" align="center">70 (48%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Days before surgery (days)</td>
<td valign="top" align="center">5.38 &#x000B1; 5.80</td>
<td valign="top" align="center">4.82 &#x000B1; 3.84</td>
<td valign="top" align="center">0.33</td>
</tr>
<tr>
<td valign="top" align="left">Smoking (pieces)</td>
<td valign="top" align="center">62.5 &#x000B1; 190</td>
<td valign="top" align="center">62.8 &#x000B1; 170</td>
<td valign="top" align="center">0.988</td>
</tr>
<tr>
<td valign="top" align="left">Drinking (ml)</td>
<td valign="top" align="center">645 &#x000B1; 2,360</td>
<td valign="top" align="center">657 &#x000B1; 2,680</td>
<td valign="top" align="center">0.968</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN3"><label>&#x00023;</label><p><italic>This means that the P-value is &#x0003C;0.1</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T3">
<label>Table 3</label>
<caption><p>Laboratory test results between complication and without complication groups after the propensity score matching analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Blood glucose (mmol/L)</td>
<td valign="top" align="center">5.23 &#x000B1; 1.31</td>
<td valign="top" align="center">5.48 &#x000B1; 1.95</td>
<td valign="top" align="center">0.19</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Blood type</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;A</td>
<td valign="top" align="center">26 (18%)</td>
<td valign="top" align="center">26 (18%)</td>
<td valign="top" align="center">0.992</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;B</td>
<td valign="top" align="center">44 (30%)</td>
<td valign="top" align="center">42 (29%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;AB</td>
<td valign="top" align="center">11 (8%)</td>
<td valign="top" align="center">12 (8%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;O</td>
<td valign="top" align="center">65 (45%)</td>
<td valign="top" align="center">66 (45%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">C-reactive protein (mg/L)</td>
<td valign="top" align="center">0.370 &#x000B1; 0.484</td>
<td valign="top" align="center">0.397 &#x000B1; 0.491</td>
<td valign="top" align="center">0.632</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Hepatitis B surface antigen</td>
</tr>
<tr>
<td valign="top" align="left">Negative</td>
<td valign="top" align="center">135 (92%)</td>
<td valign="top" align="center">131 (90%)</td>
<td valign="top" align="center">0.538</td>
</tr>
<tr>
<td valign="top" align="left">Positive</td>
<td valign="top" align="center">11 (8%)</td>
<td valign="top" align="center">15 (10%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">White blood cells (<sup>&#x0002A;</sup>10<sup>9</sup>/L)</td>
<td valign="top" align="center">7.33 &#x000B1; 2.93</td>
<td valign="top" align="center">7.41 &#x000B1; 2.87</td>
<td valign="top" align="center">0.823</td>
</tr>
<tr>
<td valign="top" align="left">Hemoglobin (g/L)</td>
<td valign="top" align="center">120 &#x000B1; 17.2</td>
<td valign="top" align="center">118 &#x000B1; 18.1</td>
<td valign="top" align="center">0.289</td>
</tr>
<tr>
<td valign="top" align="left">Platelets (<sup>&#x0002A;</sup>10<sup>9</sup>/L)</td>
<td valign="top" align="center">310 &#x000B1; 94.8</td>
<td valign="top" align="center">309 &#x000B1; 110</td>
<td valign="top" align="center">0.942</td>
</tr>
<tr>
<td valign="top" align="left">Percentage of neutrophils (%)</td>
<td valign="top" align="center">0.633 &#x000B1; 0.111</td>
<td valign="top" align="center">0.645 &#x000B1; 0.139</td>
<td valign="top" align="center">0.427</td>
</tr>
<tr>
<td valign="top" align="left">Percentage of lymphocytes (%)</td>
<td valign="top" align="center">0.229 &#x000B1; 0.0896</td>
<td valign="top" align="center">0.219 &#x000B1; 0.110</td>
<td valign="top" align="center">0.38</td>
</tr>
<tr>
<td valign="top" align="left">Absolute monocytes (<sup>&#x0002A;</sup>10<sup>9</sup>/L)</td>
<td valign="top" align="center">0.658 &#x000B1; 0.312</td>
<td valign="top" align="center">0.668 &#x000B1; 0.270</td>
<td valign="top" align="center">0.778</td>
</tr>
<tr>
<td valign="top" align="left">Percentage of monocytes (%)</td>
<td valign="top" align="center">0.0964 &#x000B1; 0.0540</td>
<td valign="top" align="center">0.0943 &#x000B1; 0.0313</td>
<td valign="top" align="center">0.684</td>
</tr>
<tr>
<td valign="top" align="left">Total bilirubin (umol/L)</td>
<td valign="top" align="center">8.89 &#x000B1; 7.05</td>
<td valign="top" align="center">9.06 &#x000B1; 9.71</td>
<td valign="top" align="center">0.862</td>
</tr>
<tr>
<td valign="top" align="left">Direct bilirubin (umol/L)</td>
<td valign="top" align="center">3.91 &#x000B1; 4.57</td>
<td valign="top" align="center">4.06 &#x000B1; 5.69</td>
<td valign="top" align="center">0.801</td>
</tr>
<tr>
<td valign="top" align="left">Indirect bilirubin (umol/L)</td>
<td valign="top" align="center">4.93 &#x000B1; 3.51</td>
<td valign="top" align="center">4.99 &#x000B1; 4.44</td>
<td valign="top" align="center">0.899</td>
</tr>
<tr>
<td valign="top" align="left">Total protein (g/L)</td>
<td valign="top" align="center">69.3 &#x000B1; 7.76</td>
<td valign="top" align="center">69.8 &#x000B1; 8.47</td>
<td valign="top" align="center">0.585</td>
</tr>
<tr>
<td valign="top" align="left">Albumin (g/L)</td>
<td valign="top" align="center">36.8 &#x000B1; 5.45</td>
<td valign="top" align="center">36.6 &#x000B1; 4.96</td>
<td valign="top" align="center">0.779</td>
</tr>
<tr>
<td valign="top" align="left">Aspartate aminotransferase (U/L)</td>
<td valign="top" align="center">25.1 &#x000B1; 15.1</td>
<td valign="top" align="center">26.7 &#x000B1; 24.1</td>
<td valign="top" align="center">0.519</td>
</tr>
<tr>
<td valign="top" align="left">Alanine aminotransferase (U/L)</td>
<td valign="top" align="center">23.9 &#x000B1; 23.8</td>
<td valign="top" align="center">23.5 &#x000B1; 23.5</td>
<td valign="top" align="center">0.91</td>
</tr>
<tr>
<td valign="top" align="left">AST/ALT</td>
<td valign="top" align="center">1.33 &#x000B1; 0.668</td>
<td valign="top" align="center">1.50 &#x000B1; 0.968</td>
<td valign="top" align="center">0.076<xref ref-type="table-fn" rid="TN4"><sup>&#x00023;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Blood urea (mmol/L)</td>
<td valign="top" align="center">4.36 &#x000B1; 1.79</td>
<td valign="top" align="center">5.30 &#x000B1; 7.71</td>
<td valign="top" align="center">0.152</td>
</tr>
<tr>
<td valign="top" align="left">Blood creatinine (umol/L)</td>
<td valign="top" align="center">67.9 &#x000B1; 18.6</td>
<td valign="top" align="center">71.5 &#x000B1; 65.7</td>
<td valign="top" align="center">0.522</td>
</tr>
<tr>
<td valign="top" align="left">Blood uric acid (umol/L)</td>
<td valign="top" align="center">398 &#x000B1; 191</td>
<td valign="top" align="center">382 &#x000B1; 164</td>
<td valign="top" align="center">0.459</td>
</tr>
<tr>
<td valign="top" align="left">Erythrocyte sedimentation rate (mm/h)</td>
<td valign="top" align="center">43.9 &#x000B1; 26.0</td>
<td valign="top" align="center">40.1 &#x000B1; 23.9</td>
<td valign="top" align="center">0.197</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN4"><label>&#x00023;</label><p><italic>This means that the P-value is &#x0003C;0.1</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="F6" position="float">
<label>Figure 6</label>
<caption><p>Post-operative information comparison between complication and without complication groups after the propensity score matching analysis. <bold>(A)</bold> Albumin quantity. <bold>(B)</bold> Operation time. <bold>(C)</bold> Incision length. &#x0002A;This means that the <italic>P</italic>-value is &#x0003C;0.05. &#x0002A;&#x0002A;This means that the <italic>P</italic>-value is &#x0003C;0.01.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0006.tif"/>
</fig>
<fig id="F7" position="float">
<label>Figure 7</label>
<caption><p>The hospital costs and days with <italic>P</italic> &#x0003C; 0.05 after the propensity score matching analysis. <bold>(A)</bold> Laboratory costs. <bold>(B)</bold> Examination costs. <bold>(C)</bold> Guardianship costs. <bold>(D)</bold> Oxygen costs. <bold>(E)</bold> Total costs. <bold>(F)</bold> Hospital stay. &#x0002A;This means that the <italic>P</italic>-value is &#x0003C;0.05. &#x0002A;&#x0002A;This means that the <italic>P</italic>-value is &#x0003C;0.01.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0007.tif"/>
</fig>
<table-wrap position="float" id="T4">
<label>Table 4</label>
<caption><p>Post-operative information comparison between complication and without complication groups after the propensity score matching analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left" colspan="4">Titanium cage</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">72 (49%)</td>
<td valign="top" align="center">69 (47%)</td>
<td valign="top" align="center">0.815</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">74 (51%)</td>
<td valign="top" align="center">77 (53%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Internal fixation</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">18 (12%)</td>
<td valign="top" align="center">19 (13%)</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">128 (88%)</td>
<td valign="top" align="center">127 (87%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Abscess</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">17 (12%)</td>
<td valign="top" align="center">22 (15%)</td>
<td valign="top" align="center">0.491</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">129 (88%)</td>
<td valign="top" align="center">124 (85%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Albumin quantity (bottles)</td>
<td valign="top" align="center">0.740 &#x000B1; 2.44</td>
<td valign="top" align="center">1.71 &#x000B1; 2.82</td>
<td valign="top" align="center">0.002<xref ref-type="table-fn" rid="TN7"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Recurrence</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">141 (97%)</td>
<td valign="top" align="center">106 (73%)</td>
<td valign="top" align="center">&#x0003C;0.001<xref ref-type="table-fn" rid="TN7"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">5 (3%)</td>
<td valign="top" align="center">40 (27%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Surgical approach</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Anterior</td>
<td valign="top" align="center">97 (66%)</td>
<td valign="top" align="center">79 (54%)</td>
<td valign="top" align="center">0.086<xref ref-type="table-fn" rid="TN5"><sup>&#x00023;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Posterior</td>
<td valign="top" align="center">44 (30%)</td>
<td valign="top" align="center">62 (42%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Anteroposterior</td>
<td valign="top" align="center">5 (3%)</td>
<td valign="top" align="center">5 (3%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Hospital stay (days)</td>
<td valign="top" align="center">11.7 &#x000B1; 7.44</td>
<td valign="top" align="center">14.7 &#x000B1; 9.34</td>
<td valign="top" align="center">0.003<xref ref-type="table-fn" rid="TN7"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Transfusion</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">99 (68%)</td>
<td valign="top" align="center">90 (62%)</td>
<td valign="top" align="center">0.327</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">47 (32%)</td>
<td valign="top" align="center">56 (38%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Local streptomycin</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">22 (15%)</td>
<td valign="top" align="center">14 (10%)</td>
<td valign="top" align="center">0.213</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">124 (85%)</td>
<td valign="top" align="center">132 (90%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Operation time (minutes)</td>
<td valign="top" align="center">138 &#x000B1; 60.5</td>
<td valign="top" align="center">162 &#x000B1; 74.1</td>
<td valign="top" align="center">0.002<xref ref-type="table-fn" rid="TN7"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Bleeding volume (ml)</td>
<td valign="top" align="center">476 &#x000B1; 457</td>
<td valign="top" align="center">582 &#x000B1; 1,070</td>
<td valign="top" align="center">0.269</td>
</tr>
<tr>
<td valign="top" align="left">Red blood cell transfusion (U)</td>
<td valign="top" align="center">1.16 &#x000B1; 2.06</td>
<td valign="top" align="center">1.37 &#x000B1; 2.78</td>
<td valign="top" align="center">0.455</td>
</tr>
<tr>
<td valign="top" align="left">Drainage (ml)</td>
<td valign="top" align="center">359 &#x000B1; 287</td>
<td valign="top" align="center">419 &#x000B1; 342</td>
<td valign="top" align="center">0.11</td>
</tr>
<tr>
<td valign="top" align="left" colspan="4">Kyphosis</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;No</td>
<td valign="top" align="center">78 (53%)</td>
<td valign="top" align="center">70 (48%)</td>
<td valign="top" align="center">0.413</td>
</tr>
<tr>
<td valign="top" align="left">&#x000A0;Yes</td>
<td valign="top" align="center">68 (47%)</td>
<td valign="top" align="center">76 (52%)</td>
<td/>
</tr>
<tr>
<td valign="top" align="left">Incision length (cm)</td>
<td valign="top" align="center">10.2 &#x000B1; 3.56</td>
<td valign="top" align="center">11.2 &#x000B1; 4.76</td>
<td valign="top" align="center">0.048<xref ref-type="table-fn" rid="TN6"><sup>&#x0002A;</sup></xref></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN5"><label>&#x00023;</label><p><italic>This means that the P-value is &#x0003C;0.1</italic>.</p></fn> 
<fn id="TN6"><label>&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.05</italic>.</p></fn>
<fn id="TN7"><label>&#x0002A;&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.01</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<table-wrap position="float" id="T5">
<label>Table 5</label>
<caption><p>The cost of hospitalization comparison between complication and without complication groups after the propensity score matching analysis.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>Without complications</bold></th>
<th valign="top" align="center"><bold>Complications</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic><bold>-value</bold></th>
</tr>
<tr>
<th/>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th valign="top" align="center"><bold>(<italic>N</italic> &#x0003D; 146)</bold></th>
<th/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Antibacterial costs (RMB)</td>
<td valign="top" align="center">377 &#x000B1; 1,110</td>
<td valign="top" align="center">1,220 &#x000B1; 2,430</td>
<td valign="top" align="center">&#x0003C;0.001<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Western medicine costs (RMB)</td>
<td valign="top" align="center">4,510 &#x000B1; 4,330</td>
<td valign="top" align="center">7,080 &#x000B1; 7,650</td>
<td valign="top" align="center">&#x0003C;0.001<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Surgical costs (RMB)</td>
<td valign="top" align="center">6,220 &#x000B1; 3,280</td>
<td valign="top" align="center">6,620 &#x000B1; 3,920</td>
<td valign="top" align="center">0.34</td>
</tr>
<tr>
<td valign="top" align="left">Anesthesia costs (RMB)</td>
<td valign="top" align="center">782 &#x000B1; 265</td>
<td valign="top" align="center">844 &#x000B1; 367</td>
<td valign="top" align="center">0.099</td>
</tr>
<tr>
<td valign="top" align="left">Laboratory costs (RMB)</td>
<td valign="top" align="center">2,280 &#x000B1; 1,360</td>
<td valign="top" align="center">2,900 &#x000B1; 2,080</td>
<td valign="top" align="center">0.003<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Examine costs (RMB)</td>
<td valign="top" align="center">272 &#x000B1; 422</td>
<td valign="top" align="center">425 &#x000B1; 826</td>
<td valign="top" align="center">0.047<xref ref-type="table-fn" rid="TN8"><sup>&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Guardianship costs (RMB)</td>
<td valign="top" align="center">441 &#x000B1; 186</td>
<td valign="top" align="center">791 &#x000B1; 1,940</td>
<td valign="top" align="center">0.032<xref ref-type="table-fn" rid="TN8"><sup>&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Transfusion costs (RMB)</td>
<td valign="top" align="center">418 &#x000B1; 676</td>
<td valign="top" align="center">680 &#x000B1; 1,990</td>
<td valign="top" align="center">0.133</td>
</tr>
<tr>
<td valign="top" align="left">Oxygen costs (RMB)</td>
<td valign="top" align="center">103 &#x000B1; 106</td>
<td valign="top" align="center">154 &#x000B1; 210</td>
<td valign="top" align="center">0.009<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">High consumable costs (RMB)</td>
<td valign="top" align="center">23,300 &#x000B1; 16,500</td>
<td valign="top" align="center">26,400 &#x000B1; 19,200</td>
<td valign="top" align="center">0.131</td>
</tr>
<tr>
<td valign="top" align="left">Care costs (RMB)</td>
<td valign="top" align="center">193 &#x000B1; 141</td>
<td valign="top" align="center">273 &#x000B1; 239</td>
<td valign="top" align="center">&#x0003C;0.001<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Consultation costs (RMB)</td>
<td valign="top" align="center">12.3 &#x000B1; 29.3</td>
<td valign="top" align="center">29.3 &#x000B1; 44.5</td>
<td valign="top" align="center">&#x0003C;0.001<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Total costs (RMB)</td>
<td valign="top" align="center">42,800 &#x000B1; 24,200</td>
<td valign="top" align="center">51,700 &#x000B1; 31,800</td>
<td valign="top" align="center">0.008<xref ref-type="table-fn" rid="TN9"><sup>&#x0002A;&#x0002A;</sup></xref></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN8"><label>&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.05</italic>.</p></fn> 
<fn id="TN9"><label>&#x0002A;&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.01</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>We constructed a logistic regression model to further explore the risk factors that affected the complications. The parameters with <italic>P</italic>-values &#x0003C;0.1 were included in the logistic regression analysis, including appetite, occupation, AST/ALT, albumin quantity, surgical approach, operation time, and incision length. There was a significant difference in the albumin quantity using the logistic regression model analysis (<xref ref-type="table" rid="T6">Table 6</xref>). Furthermore, there was a significant difference in the intercept of the regression model (<italic>P</italic> &#x0003C; 0.05). However, there were no statistical differences in other parameters, including appetite, occupation, AST/ALT, surgical approach, operation time, and incision length (<italic>P</italic> &#x0003E; 0.05).</p>
<table-wrap position="float" id="T6">
<label>Table 6</label>
<caption><p>Multivariate logistic regression analysis results.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th/>
<th valign="top" align="center"><bold>&#x003B2;</bold></th>
<th valign="top" align="center"><bold>OR</bold></th>
<th valign="top" align="center"><bold>OR (95%CI)</bold></th>
<th valign="top" align="center"><italic><bold>P</bold></italic></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Intercept</td>
<td valign="top" align="center">&#x02212;1.6262</td>
<td valign="top" align="center">0.1967</td>
<td valign="top" align="center">0.0437&#x02013;0.8120</td>
<td valign="top" align="center">0.0281<xref ref-type="table-fn" rid="TN10"><sup>&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Albumin quantity</td>
<td valign="top" align="center">0.1570</td>
<td valign="top" align="center">1.1700</td>
<td valign="top" align="center">1.0273&#x02013;1.3595</td>
<td valign="top" align="center">0.0265<xref ref-type="table-fn" rid="TN10"><sup>&#x0002A;</sup></xref></td>
</tr>
<tr>
<td valign="top" align="left">Operation time</td>
<td valign="top" align="center">0.0016</td>
<td valign="top" align="center">1.0016</td>
<td valign="top" align="center">0.9969&#x02013;1.0064</td>
<td valign="top" align="center">0.5035</td>
</tr>
<tr>
<td valign="top" align="left">Incision length</td>
<td valign="top" align="center">0.0360</td>
<td valign="top" align="center">1.0367</td>
<td valign="top" align="center">0.9554&#x02013;1.1288</td>
<td valign="top" align="center">0.3929</td>
</tr>
<tr>
<td valign="top" align="left">Appetite</td>
<td valign="top" align="center">0.2236</td>
<td valign="top" align="center">1.2506</td>
<td valign="top" align="center">0.6978&#x02013;2.2480</td>
<td valign="top" align="center">0.4527</td>
</tr>
<tr>
<td valign="top" align="left">Surgical approach</td>
<td valign="top" align="center">0.2949</td>
<td valign="top" align="center">1.3430</td>
<td valign="top" align="center">0.74283&#x02013;2.4528</td>
<td valign="top" align="center">0.3304</td>
</tr>
<tr>
<td valign="top" align="left">Occupation</td>
<td valign="top" align="center">0.2789</td>
<td valign="top" align="center">1.3216</td>
<td valign="top" align="center">0.7425&#x02013;2.3577</td>
<td valign="top" align="center">0.3431</td>
</tr>
<tr>
<td valign="top" align="left">AST/ALT</td>
<td valign="top" align="center">0.1338</td>
<td valign="top" align="center">1.1432</td>
<td valign="top" align="center">0.8224&#x02013;1.6285</td>
<td valign="top" align="center">0.4361</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="TN10"><label>&#x0002A;</label><p><italic>This means that the P-value is &#x0003C;0.05</italic>.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>The goodness of fit of the logistic regression model was assessed by HL-test and the chi-square value. <italic>P</italic>-values were 4.534 and 0.806, respectively. The confidence interval of the odds ratio (<xref ref-type="table" rid="T6">Table 6</xref>) was further used to evaluate the logistic regression model. The ROC curve was applied to evaluate the validity of the logistic regression model. The area under the curve (AUC) was 0.75 (<xref ref-type="fig" rid="F8">Figure 8</xref>).</p>
<fig id="F8" position="float">
<label>Figure 8</label>
<caption><p>ROC curve. The area under the curve was 0.75.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fsurg-09-815303-g0008.tif"/>
</fig>
<p>In this study, various complications occurred after spinal tuberculosis surgery during post-operative follow-up (<xref ref-type="table" rid="T7">Table 7</xref>). Eight patients were transferred to ICU for treatment due to post-operative respiratory failure, hypoxia, and inability to remove the ventilator. Wound infection occurred in 77 patients. After intensive wound management or two-stage debridement, they can recover well. Pedicle screw fracture occurred in 1 patient, requiring a second surgery to re-implant the internal fixation device.</p>
<table-wrap position="float" id="T7">
<label>Table 7</label>
<caption><p>Various types of complications after spinal tuberculosis surgery.</p></caption>
<table frame="hsides" rules="groups">
<thead><tr>
<th valign="top" align="left"><bold>Complications</bold></th>
<th valign="top" align="center"><bold>Numbers</bold></th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Transfer to ICU</td>
<td valign="top" align="center">8</td>
</tr>
<tr>
<td valign="top" align="left">Pulmonary embolism</td>
<td valign="top" align="center">2</td>
</tr>
<tr>
<td valign="top" align="left">Pneumonia</td>
<td valign="top" align="center">15</td>
</tr>
<tr>
<td valign="top" align="left">Intracranial infection</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">Pedicle screw fracture</td>
<td valign="top" align="center">1</td>
</tr>
<tr>
<td valign="top" align="left">Cerebrospinal fluid leak</td>
<td valign="top" align="center">2</td>
</tr>
<tr>
<td valign="top" align="left">Wound infection</td>
<td valign="top" align="center">77</td>
</tr>
<tr>
<td valign="top" align="left">Deep vein thrombosis of lower extremity</td>
<td valign="top" align="center">2</td>
</tr>
<tr>
<td valign="top" align="left">Pleural effusion</td>
<td valign="top" align="center">6</td>
</tr>
<tr>
<td valign="top" align="left">Other complications</td>
<td valign="top" align="center">32</td>
</tr>
</tbody>
</table>
</table-wrap></sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>Spinal tuberculosis surgery has become the most common treatment for spinal tuberculosis, including anterior (<xref ref-type="bibr" rid="B28">28</xref>), posterior (<xref ref-type="bibr" rid="B29">29</xref>), and combined anterior and posterior approaches (<xref ref-type="bibr" rid="B30">30</xref>). Moreover, the literature reports that spinal tuberculosis surgery includes minimally invasive procedures and combined open and minimally invasive procedures (<xref ref-type="bibr" rid="B7">7</xref>). However, post-operative complications are often unexpected and also a challenge for surgeons (<xref ref-type="bibr" rid="B31">31</xref>, <xref ref-type="bibr" rid="B32">32</xref>). The complications of spinal tuberculosis vary depending on the location. The complications in cervical tuberculosis have been reported to be more than in non-cervical tuberculosis (<xref ref-type="bibr" rid="B33">33</xref>). In addition, post-operative complications of spinal tuberculosis vary depending on the surgical approach. The complications of the anterior approach were higher than in the posterior approach (<xref ref-type="bibr" rid="B7">7</xref>).</p>
<p>The parameters with a <italic>P</italic>-value &#x0003C;0.05 in the univariate analysis included albumin quantity, operation time, and incision length. Patients with classic spinal tuberculosis were often accompanied by weight loss (<xref ref-type="bibr" rid="B34">34</xref>); these patients who underwent surgical treatment were prone to poor wound healing due to post-operative nutritional insufficiency (<xref ref-type="bibr" rid="B35">35</xref>&#x02013;<xref ref-type="bibr" rid="B37">37</xref>). Under such conditions, clinicians often use albumin supplementation to promote the recovery of patients (<xref ref-type="bibr" rid="B38">38</xref>). In addition, a longer surgical incision results in more secretion of fluid from the incision and increased susceptibility to wound infection (<xref ref-type="bibr" rid="B39">39</xref>). This could be the reason that the length of the incision in the complication group in this study was longer than that in the without complication group, and the albumin quantity in the former was more than that in the latter. If the operation time exceeded 3 h, the second group of antibiotics often needed to be increased, which potentially increased the risk of post-operative infection and other complications in case of prolonged operation time (<xref ref-type="bibr" rid="B40">40</xref>). Therefore, the operation time in the complication group was higher than in the without complication group.</p>
<p>Various costs, including hospital stay, laboratory costs, examination costs, guardianship costs, oxygen costs, and total costs, were higher in the complication group than in the without complication group. Research by Marah et al. showed that post-operative respiratory failure increased the cost of surgery by more than 50% (<xref ref-type="bibr" rid="B41">41</xref>). Mark et al. studied the relationship between surgical complications and hospitalization costs and found that hospitalization costs were on an average of $19,626 higher in patients with complications than in those without complications (<xref ref-type="bibr" rid="B42">42</xref>). The findings of Hunt et al. showed that post-operative complications not only increased the length of hospital stay but also increased the cost of hospitalization (<xref ref-type="bibr" rid="B43">43</xref>). This was consistent with the results of our study.</p>
<p>In the present study, only the albumin quantity was significantly different by multivariate logistic regression analysis. In addition, the albumin quantity in the complication group was higher than that in the without complication group. Li et al.&#x00027;s study of spinal tuberculosis found that the albumin in the anterior approach group decreased from 37 g/L pre-operatively to 24.2 g/L post-operatively and that in the posterior approach group decreased from 38.6 to 28.2 g/L, with pneumonia and other complications in both groups of surgical approaches (<xref ref-type="bibr" rid="B44">44</xref>). A close relationship existed between albumin and post-operative complications (<xref ref-type="bibr" rid="B45">45</xref>), and albumin supplementation may accelerate the recovery of the post-operative condition (<xref ref-type="bibr" rid="B46">46</xref>).</p>
<p>The logistic regression model was tested through the HL test method, and the <italic>P</italic>-value was 0.806 (<italic>P</italic> &#x0003E; 0.05), which implied no difference between the logistic regression model and the actual application. The value of the area under the ROC curve was 0.75, implying that this regression model can be used in clinical applications.</p>
<p>PSM analysis strategies, such as tumor chemotherapy (<xref ref-type="bibr" rid="B47">47</xref>), cervical spine surgery (<xref ref-type="bibr" rid="B48">48</xref>), robot-assisted surgery (<xref ref-type="bibr" rid="B49">49</xref>), and other areas, are widely used in medical research. The PSM analysis can reduce the difference between the two groups of comparable data and decrease the effect of interfering factors on the results by adjusting the balance of baseline data (<xref ref-type="bibr" rid="B22">22</xref>). Such a model allows the researchers to measure the probability of an outcome event occurring between treatment and control groups (<xref ref-type="bibr" rid="B50">50</xref>). The pre-matched imbalance and post-matched balance were assessed using the balance standardized differences (<xref ref-type="bibr" rid="B23">23</xref>). We found a significant difference in the laboratory results of albumin value between the complication and without complication groups, which inevitably became a disturbing factor for another result that the albumin quantity was an independent risk by the logistic regression analysis. The albumin values of the two groups before the operation were adjusted to be the same by the PSM analysis, and the results of the study were more comparable.</p>
<p>However, this study had certain limitations. (1) Some data were lost after the PSM analysis. (2) More sample data should be collected to obtain more pairs. (3) This subject was a single-center study, and the results need to be verified by a multi-center study.</p></sec>
<sec sec-type="conclusions" id="s5">
<title>Conclusion</title>
<p>In this study, the costs in the complication group were generally higher than in the without complication group. Multivariate logistic regression analysis found that albumin quantity could be an independent factor for predicting post-operative complications of spinal tuberculosis. Therefore, surgeons should pay more attention to the patient&#x00027;s economy and the occurrence of post-operative complications in clinical work.</p></sec>
<sec sec-type="data-availability" id="s6">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.</p></sec>
<sec id="s7">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. The patients/participants provided their written informed consent to participate in this study.</p></sec>
<sec id="s8">
<title>Author Contributions</title>
<p>LC wrote the article and prepared <xref ref-type="fig" rid="F1">Figures 1</xref>&#x02013;<xref ref-type="fig" rid="F8">8</xref> and <xref ref-type="table" rid="T1">Tables 1</xref>&#x02013;<xref ref-type="table" rid="T6">6</xref>. All authors reviewed the article, including SH, TC, HL, TL, ZY, WC, XS, JJ, JC, HG, YY, SL, CY, BF, SW, and XZ. All authors contributed to the article and approved the submitted version.</p></sec>
<sec sec-type="funding-information" id="s9">
<title>Funding</title>
<p>This work was sponsored by the National Natural Science Foundation of China (81560359) and National Natural Science Foundation of China (81860393). Funding bodies had no role in the study design, collection, analysis, and interpretation of the data or in writing the manuscript.</p></sec>
<sec sec-type="COI-statement" id="conf1">
<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 sec-type="disclaimer" id="s10">
<title>Publisher&#x00027;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></body>
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