Postoperative Spinal Implant Infection According to EBJIS Criteria: Risk Factors in Posterior Spinal Instrumentation Surgery

Postoperative Spinal Implant Infection According to EBJIS Criteria: Risk Factors in Posterior Spinal Instrumentation Surgery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Postoperative Spinal Implant Infection According to EBJIS Criteria: Risk Factors in Posterior Spinal Instrumentation Surgery Ali Kutta ÇELİK, Mustafa UĞUZ, Fatih ERDEM, Berfin Çirkin DORUK, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9346562/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Postoperative spinal implant infection (PSII) is a clinically significant complication following spinal instrumentation, with diagnostic challenges related to biofilm formation and the lack of standardized criteria. This study aimed to evaluate PSII according to the European Bone and Joint Infection Society (EBJIS) criteria and to identify associated clinical, laboratory, and perioperative risk factors. Methods: In this retrospective cohort study, 224 adult patients who underwent posterior spinal instrumentation surgery between January 2025 and January 2026 were included. Demographic characteristics, comorbidities, laboratory parameters, perioperative variables, and microbiological findings were obtained from electronic medical records. PSII was defined according to the EBJIS “confirmed infection” criteria. Variables with p < 0.10 in univariate analysis were considered for multivariate logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results: PSII developed in 18 patients (8.0%). No significant association was found between PSII and demographic variables or comorbidities. Elevated C-reactive protein (CRP) levels and lower serum albumin levels were associated with PSII (p < 0.05). In univariate analysis, ASA score ≥3, emergency surgery, perioperative steroid use, low molecular weight heparin use, prone positioning, and intensive care unit admission were significantly associated with PSII. In multivariate analysis, only emergency surgery remained independently associated with PSII (OR: 6.48; 95% CI: 1.28–32.70; p = 0.024). Receiver operating characteristic (ROC) analysis demonstrated limited discriminative ability of the number of fused vertebrae (AUC = 0.613). Conclusions: PSII remains an important complication following spinal instrumentation surgery. Emergency surgery was independently associated with PSII, while CRP elevation and hypoalbuminemia were identified as associated findings rather than independent predictors. The use of standardized diagnostic approaches such as EBJIS may improve diagnostic consistency and facilitate more reliable risk stratification. Postoperative spinal implant infection Spinal instrumentation EBJIS criteria Risk factors Biofilm Emergency surgery C-reactive protein Hypoalbuminemia Figures Figure 1 Figure 2 Figure 3 Background Spinal surgery is widely performed for the management of degenerative, traumatic, deformity-related, and neoplastic spinal disorders. However, parallel to the increasing use of spinal instrumentation, postoperative spinal implant infection (PSII) has emerged as a significant clinical challenge. PSII is associated with substantial morbidity, prolonged hospital stay, repeated surgical interventions, increased healthcare costs, and, in severe cases, mortality [ 1 ]. Reported incidence rates vary widely, ranging from 0.7% to 18%, depending on patient characteristics and surgical factors [ 2 ]. The presence of implanted materials facilitates bacterial adhesion and biofilm formation, which reduces antibiotic penetration and contributes to the persistence and chronicity of infection. PSII is commonly classified according to the timing of onset as early, delayed, and late infection. While early infections typically present with more pronounced clinical findings, delayed and late infections often manifest with subtle and nonspecific symptoms, further complicating diagnosis. The diagnosis of PSII remains challenging. Clinical findings lack specificity, laboratory parameters are often nonspecific, and imaging modalities may be limited by metal-related artifacts [ 3 ]. In addition, prior antibiotic exposure may reduce the yield of microbiological cultures, delaying identification of the causative pathogen. Management strategies for PSII include targeted antimicrobial therapy, surgical debridement, implant retention or removal, and, when necessary, re-instrumentation. Implant retention is generally preferred in early infections (within the first 3 postoperative months), whereas implant removal is often unavoidable in late infections [ 2 ]. However, implant removal may lead to spinal instability, deformity progression, and pseudarthrosis. A major limitation in the literature is the lack of universally accepted diagnostic criteria for implant-related infections, which reduces comparability across studies. Although many studies have used the Centers for Disease Control and Prevention (CDC) surgical site infection definitions [ 4 ], these criteria are primarily designed for acute postoperative infections and may not adequately capture chronic biofilm-related implant infections. To address these limitations, the EBJIS has proposed a standardized diagnostic framework integrating clinical findings, laboratory markers, microbiological evidence, and histopathological evaluation [ 5 ]. Despite the increasing use of EBJIS criteria in implant-related infections, studies specifically evaluating risk factors for PSII based on this standardized definition remain limited, and the available evidence is heterogeneous. Therefore, the aim of this study was to evaluate PSII according to EBJIS criteria and to analyze associated clinical, laboratory, and perioperative risk factors. Methods Study design and setting This retrospective cohort study was conducted at the Department of Neurosurgery, Mersin City Training and Research Hospital. All consecutive adult patients (≥ 18 years) who underwent posterior spinal instrumentation surgery between January 2025 and January 2026 were included. Patient data were retrieved from the electronic hospital information system (Hospital Information System, HIS), and all eligible cases were systematically screened. Patients who developed postoperative spinal implant infection (PSII) were identified through retrospective evaluation. Inclusion and exclusion criteria Only patients who underwent posterior spinal fusion with instrumentation were included. Patients who underwent vertebroplasty alone, isolated laminectomy, or non-instrumented surgery for sacral, coccygeal, or pelvic fractures were excluded. Follow-up All patients were followed for a minimum of 6 months postoperatively. This follow-up duration was considered sufficient based on previous literature evaluating early and delayed implant-related infections. Data collection The following variables were collected: Demographic characteristics: age, sex, blood group Laboratory parameters: hemoglobin, white blood cell count, C-reactive protein (CRP), total protein, serum albumin Comorbidities: diabetes mellitus, hypertension, coronary artery disease, malignancy, and other coexisting conditions Perioperative variables: American Society of Anesthesiologists (ASA) score, preoperative and postoperative length of hospital stay, perioperative glucocorticoid use, perioperative blood transfusion, postoperative intensive care unit (ICU) admission, postoperative positioning, and number of fused vertebrae Microbiological assessment Patients with suspected PSII were evaluated based on clinical, laboratory, and microbiological findings. When available, intraoperative deep tissue samples were obtained, and microbiological culture results were recorded. Whenever feasible, multiple deep tissue samples were collected and processed using standard microbiological methods to increase diagnostic accuracy. Perioperative infection prevention protocol Perioperative infection prevention protocol In our institution, prophylactic antibiotics are routinely administered 30 minutes prior to skin incision. In prolonged procedures, additional intraoperative doses are administered every 3 hours. Diluted povidone–iodine irrigation is routinely used intraoperatively in accordance with CDC recommendations [ 6 ]. Definition of PSII PSII was defined according to the “confirmed infection” criteria proposed by the EBJIS [ 7 ]. Patients with suspected infection were retrospectively evaluated using clinical, laboratory, microbiological, and, when available, histopathological findings. Cases were classified as confirmed PSII if at least one of the following criteria was present: Sinus tract communicating with the implant Purulence surrounding the implant Isolation of the same microorganism from at least two separate deep tissue samples Histopathological evidence of acute inflammation Subgroup analysis For subgroup analysis, thoracic and thoracolumbar procedures were evaluated as a single group, whereas lumbar and lumbosacral procedures were analyzed separately. Statistical analysis Continuous variables were tested for normality using the Shapiro–Wilk test. Non-normally distributed variables were expressed as median (interquartile range, IQR), while categorical variables were presented as number and percentage. Comparisons between groups were performed using the Mann–Whitney U test for continuous variables and the chi-square test or Fisher’s exact test for categorical variables, as appropriate. Univariate logistic regression analysis was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Variables with p < 0.10 in univariate analysis and those considered clinically relevant were included in the multivariate logistic regression model. Given the limited number of PSII events (n = 18), the number of variables included in the final multivariate model was intentionally restricted to minimize the risk of overfitting. Receiver operating characteristic (ROC) analysis was performed to evaluate the discriminative performance of the number of fused vertebrae in predicting PSII. A p-value < 0.05 was considered statistically significant. All statistical analyses were conducted using SPSS version 27.0 (IBM Corp., Armonk, NY, USA). Ethical approval This study was approved by Non-Interventional Clinical Research Ethics Committee, Mersin City Training and Research Hospital, Mersin, Türkiye, and the requirement for informed consent was waived due to the retrospective study design. Results A total of 224 patients who underwent posterior spinal instrumentation surgery were included in the study. PSII developed in 18 patients, corresponding to an incidence of 8.0%. The relationship between demographic characteristics and PSII was evaluated (Table 1). No significant associations were found between PSII and sex, diabetes mellitus, hypertension, congestive heart failure, peripheral neuropathy, depression, rheumatoid arthritis, chronic obstructive pulmonary disease, epilepsy, malignancy, thyroid disorders, or chronic kidney disease (all p > 0.05). The median age was similar between patients with and without PSII (58.5 vs 57 years, p = 0.242). Preoperative laboratory parameters were compared between groups (Table 2). Patients who developed PSII had significantly higher CRP levels and lower serum albumin levels compared to those without infection (p = 0.041 and p = 0.048, respectively). No statistically significant differences were observed for hemoglobin, white blood cell count, neutrophil count, lymphocyte count, platelet count, total protein, or glucose levels (all p > 0.05). Univariate analysis of surgical and perioperative variables is presented in Table 3. ASA score ≥3 (OR: 3.12; 95% CI: 1.17–8.29; p = 0.025), emergency surgery (OR: 8.12; 95% CI: 2.12–31.10; p = 0.002), perioperative steroid use (OR: 3.04; 95% CI: 1.14–8.08; p = 0.039), low molecular weight heparin use (OR: 3.48; 95% CI: 1.30–9.27; p = 0.019), prone postoperative positioning (OR: 4.41; 95% CI: 1.57–12.38; p = 0.007), and postoperative ICU admission (OR: 4.61; 95% CI: 1.64–12.98; p = 0.006) were significantly associated with PSII. No significant association was observed between the number of fused vertebrae and PSII (p = 0.459). Preoperative and postoperative hospital length of stay were compared between groups (Table 4). No statistically significant differences were found between patients with and without PSII (p = 0.770 and p = 0.495, respectively). Variables with p < 0.10 in univariate analysis and considered clinically relevant were included in the multivariate logistic regression model. Due to the limited number of PSII events, the number of variables included in the model was restricted to minimize overfitting. In multivariate analysis, only emergency surgery remained independently associated with PSII (OR: 6.48; 95% CI: 1.28–32.70; p = 0.024). ASA score and ICU admission did not retain statistical significance (Table 5). The results of the regression analysis are illustrated in the forest plot (Figure 1). Receiver operating characteristic (ROC) analysis demonstrated that the number of fused vertebrae had limited discriminative ability for predicting PSII (AUC = 0.613). A threshold of ≥5 fused vertebrae provided the best balance between sensitivity (44.4%) and specificity (84.5%) (Figure 2). Microbiological evaluation revealed that coagulase-negative staphylococci were the most frequently isolated organisms, followed by Pseudomonas aeruginosa and Escherichia coli . Among microbiologically confirmed cases, 12 of 18 infections occurred within the first 3 postoperative weeks, while the remaining cases developed between 3 weeks and 3 months (Figure 3), demonstrating a predominance of early postoperative infections. Discussion PSII represents a clinically distinct entity compared to conventional surgical site infections due to early biofilm formation on implant surfaces, which may lead to persistent infection, delayed diagnosis, and reduced response to antimicrobial therapy. The use of EBJIS criteria in this study enhances diagnostic specificity by focusing on confirmed infection cases, thereby reducing misclassification bias in a retrospective cohort. The incidence of PSII in our study was 8%, which falls within the range reported in the literature [2]. This relatively higher rate may be attributed to the inclusion of only posterior instrumentation procedures and the complexity of the surgical population [8,9]. Demographic factors such as age and sex have shown inconsistent associations with infection risk in previous studies [1,10,11]. In our cohort, the mean age of the patients was 55.6 ± 12.0 years (range, 22–84 years), and no significant association was observed between age, sex, and the development of PSII. This finding suggests that perioperative and surgical factors may play a more prominent role than baseline patient characteristics in determining infection risk. In the microbiological evaluation, coagulase-negative staphylococci were the most frequently isolated pathogens, which is consistent with the existing literature [12]. Coagulase-negative staphylococci and Staphylococcus aureus are commonly implicated due to their strong adhesion to implant surfaces and their ability to form biofilms. In addition, Enterococcus , Escherichia coli , and Pseudomonas species were also identified in our cohort, suggesting the potential contribution of perioperative contamination and nosocomial microorganisms. These findings support the importance of obtaining multiple deep tissue samples during revision surgery to improve diagnostic accuracy. The temporal distribution of infections observed in our study was also consistent with previously reported patterns [13,14]. Among microbiologically confirmed PSII cases, 12 of 18 occurred within the first 3 postoperative weeks, while the remaining cases developed between 3 weeks and 3 months (Figure 3). The predominance of infections in the early postoperative period underscores the importance of close clinical monitoring during this critical timeframe. Inflammatory biomarkers have been widely investigated in the diagnosis of postoperative infections [15–17]. Among laboratory parameters, CRP levels were significantly elevated in patients who developed PSII. However, this finding should be interpreted with caution, as postoperative inflammatory responses may also lead to increased CRP levels independent of infection. Similarly, serum albumin levels were lower in the infected group. Hypoalbuminemia has been reported as an important biochemical marker associated with an increased risk of postoperative infections following spinal surgery. Previous studies have demonstrated that hypoalbuminemia is associated with prolonged hospitalization and a higher risk of postoperative infections [18–20]. Nevertheless, since albumin was not retained in the final multivariate model, it should be considered as an associative rather than an independent predictor. In univariate analysis, several perioperative variables—including higher ASA score, intensive care unit admission, perioperative use of low-molecular-weight heparin, glucocorticoid exposure, and prone postoperative positioning—were found to be associated with PSII. However, these associations did not remain significant in the multivariate analysis, suggesting that these factors may reflect a cumulative perioperative risk burden rather than independent effects. Variables with p < 0.10 in univariate analysis and deemed clinically relevant were included in the multivariate logistic regression model, while limiting the number of variables to avoid overfitting due to the relatively low number of infection events. Emergency surgery remained independently associated with PSII in the multivariate model. This finding may be explained by limited preoperative optimization, increased physiological instability of patients, and the complexity of surgical procedures under emergency conditions. Additionally, factors such as increased blood loss and prolonged operative time may further contribute to the elevated risk of postoperative infection. These results underscore the importance of implementing effective perioperative infection prevention strategies in emergency spinal surgeries. Although the number of fused vertebrae has been discussed as a potential risk factor in the literature [12,21], the ROC analysis in our study demonstrated that this variable had limited discriminative ability in predicting PSII (AUC = 0.613). This finding suggests that the number of fused vertebrae alone is not a reliable predictor of PSII. Furthermore, no significant association was observed between the anatomical region of instrumentation and the development of infection. In conclusion, emergency surgery appears to be an independent risk factor for PSII. Elevated CRP levels and hypoalbuminemia should be interpreted as accompanying findings that require careful clinical evaluation. The use of standardized diagnostic criteria, such as those proposed by EBJIS, may improve the reliability of diagnosing implant-related infections. These findings may contribute to improved perioperative risk stratification and help guide targeted infection prevention strategies in high-risk patient populations. Future studies incorporating serial biomarker measurements may further improve diagnostic accuracy. Conclusions Postoperative spinal implant infection remains a clinically important complication following spinal instrumentation surgery. In this study, emergency surgery was independently associated with PSII, whereas elevated CRP levels and hypoalbuminemia were identified as associated findings rather than independent predictors. The application of standardized diagnostic criteria such as EBJIS may enhance diagnostic consistency and improve comparability across studies. Larger prospective studies are warranted to further clarify independent risk factors and optimize preventive strategies. Emergency spinal instrumentation procedures should be considered high-risk settings for PSII, requiring enhanced perioperative infection prevention strategies and closer postoperative surveillance. Abbreviations ASA American Society of Anesthesiologists AUC Area under the curve CDC Centers for Disease Control and Prevention CI Confidence interval COPD Chronic obstructive pulmonary disease CRP C-reactive protein EBJIS European Bone and Joint Infection Society HIS Hospital Information System ICU Intensive care unit IQR Interquartile range LMWH Low molecular weight heparin OR Odds ratio PSII Postoperative spinal implant infection ROC Receiver operating characteristic SPSS Statistical Package for the Social Sciences Declarations This study was approved by the Non-Interventional Clinical Research Ethics Committee of Mersin City Training and Research Hospital (approval date: 25 March 2026; decision no. 190). Due to the retrospective nature of the study, the requirement for informed consent was waived by the Ethics Committee. Consent for publication Not applicable. Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request and with permission of the institutional ethics committee. Competing interests The authors declare that they have no competing interests. Funding The authors declare that no financial support was received for this study. Authors’ contributions Conceptualization : AKÇ Methodology: AKÇ, MU Data collection and/or processing: FE, BÇD Formal analysis: MU, MA Investigation: AKÇ, BÇD Writing: AKÇ, FE. References Pawar AY, Biswas SK. Postoperative spine infections. Asian Spine J. 2016;10(1):176–83. 10.4184/asj.2016.10.1.176 . Dowdell J, Brochin R, Kim J, Overley S, Oren J, Freedman B, et al. Postoperative spine infection: diagnosis and management. Global Spine J. 2018;8(4 Suppl):S37–43. 10.1177/2192568217745512 . Johnson HMD, Teixeira WJ. Post-instrumentation infection: diagnosis. 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Baseline Demographic and Clinical Characteristics of Patients With and Without Postoperative Spinal Implant Infection Variable Without PSII (n=206) With PSII (n=18) (n=18) P value Age, median (IQR) 57 (14) 58.5 (16) 0.242 Female sex, n (%) 114 (55.3) 10 (55.6) 1.000 Diabetes mellitus, n (%) 34 (16.5) 2 (11.1) 0.726 Hypertension, n (%) 70 (34.0) 6 (33.3) 1.000 Congestive heart failure, n (%) 5 (2.4) 1 (5.6) 1.000 Peripheral neuropathy, n (%) 11 (5.3) 2 (11.1) 0.675 Depression, n (%) 18 (8.7) 2 (11.1) 1.000 Rheumatoid arthritis, n (%) 7 (3.4) 1 (5.6) 0.904 COPD, n (%) 12 (5.8) 0 (0) 0.340 Epilepsy, n (%) 3 (1.5) 1 (5.6) 0.190 Malignancy, n (%) 6 (2.9) 0 (0) 1.000 Hypothyroidism, n (%) 10 (4.9) 2 (11.1) 0.872 Hyperthyroidism, n (%) 10 (4.9) 2 (11.1) 0.872 Chronic kidney disease, n (%) 4 (1.9) 2 (11.1) 0.374 (Values are presented as median (interquartile range, IQR) or number (%). Mann–Whitney U test was used for continuous variables; chi-square test or Fisher’s exact test was used for categorical variables. PSII: postoperative spinal implant infection; COPD: chronic obstructive pulmonary disease.) Table 2: Comparison of Preoperative Laboratory Parameters According to Postoperative Spinal Implant Infection Status Laboratory parameter Without PSII (n=206) (median, IQR) With PSII (n=18) (median, IQR) p value Hemoglobin (g/dL) 12.6 (2.1) 11.9 (2.3) 0.140 White blood cell (×10⁹/L) 8.7 (3.5) 10.1 (4.2) 0.080 Neutrophil count (×10⁹/L) 6.1 (3.1) 7.9 (3.8) 0.060 Lymphocyte count (×10⁹/L) 1.9 (0.8) 1.6 (0.7) 0.110 Platelet count (×10⁹/L) 256 (92) 278 (101) 0.330 C-reactive protein (mg/dL) 0.9 (2.3) 3.8 (4.8) 0.041 Serum albumin (g/dL) 3.9 (0.7) 3.5 (0.8) 0.048 Total protein (g/dL) 6.8 (0.8) 6.5 (0.7) 0.190 Glucose (mg/dL) 118 (40) 134 (46) 0.090 (Values are presented as median (interquartile range). Mann–Whitney U test was used for comparisons. PSII: postoperative spinal implant infection, IQR: interquartile range) Table 3. Univariate Analysis of Surgical and Perioperative Risk Factors Associated With Postoperative Spinal Implant Infection Variable PSII (+) / Exposure Odds Ratio 95% CI p value ASA ≥3 9 / 59 3.12 1.17–8.29 0.025 Emergency surgery 4 / 11 8.12 2.12–31.10 0.002 Fusion ≥4 vertebrae 10 / 100 1.61 0.61–4.25 0.459 Perioperative steroid use 10 / 70 3.04 1.14–8.08 0.039 Perioperative LMWH use 9 / 55 3.48 1.30–9.27 0.019 Prone postoperative position 7 / 33 4.41 1.57–12.38 0.007 Postoperative ICU stay 7 / 32 4.61 1.64–12.98 0.006 (Odds ratios (ORs) were calculated using univariate logistic regression. CI: confidence interval; ASA: American Society of Anesthesiologists; LMWH: low molecular weight heparin; ICU: intensive care unit.) Table 4. Comparison of Perioperative Hospitalization Durations Between Patients With and Without Postoperative Spinal Implant Infection Variable Without PSII (n=206) (median, IQR) With PSII (n=18) (median, IQR) p value Preoperative hospital stay (days) 2.0 2.5 0.770 Postoperative hospital stay (days) 4.0 4.5 0.495 (Values are presented as median. Mann–Whitney U test was used for comparisons. PSII: postoperative spinal implant infection.) Table 5. Multivariate Logistic Regression Analysis of Independent Predictors of Postoperative Spinal Implant Infection Variable Odds Ratio (OR) 95% CI p value Emergency surgery 6.48 1.28 – 32.70 0.024 ASA ≥3 2.31 0.79 – 6.74 0.126 ICU admission 1.94 0.48 – 7.88 0.352 (Variables with p < 0.10 in univariate analysis and clinical relevance were entered into the multivariate logistic regression model. To reduce overfitting risk, the number of variables was limited considering the low number of PSII events. OR: odds ratio; CI: confidence interval; ICU: intensive care unit; ASA: American Society of Anesthesiologists.) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 11 May, 2026 Reviews received at journal 18 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviewers agreed at journal 16 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers agreed at journal 15 Apr, 2026 Reviewers invited by journal 15 Apr, 2026 Editor assigned by journal 15 Apr, 2026 Editor invited by journal 13 Apr, 2026 Submission checks completed at journal 12 Apr, 2026 First submitted to journal 12 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9346562","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628032174,"identity":"5004cd72-825a-4464-a89d-46ca07678617","order_by":0,"name":"Ali Kutta ÇELİK","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYDCCAwzMQNKCR4K9/+MDEJdYLRI8EjwHjA2QtBgQ1MIgIZFgJkGUFr7bhx8b/KiQkJFsSEir5qm5I8fPwPzw0Q2GP/m4tEieSzNO7DkjwSPNcODYbZ5jz4wlG9iMjXMYDCwbcGgxOMNgfJixTYJHjrGx7TYP2+HEDQd42KSBWnC6zOAM++fDjP+AWpiZ2Yp5/hGlhcc4mbEB6DA2NjZm3jYitEie4Sk27DkmwSPZw8MsObfvsLFkM8gvBsY4tfCdYd8s8aPGxl7i/hvGD2++HZbjZ29++DinQg5PxCABJh4QyQx2MFEaGBgYfxCpcBSMglEwCkYWAABycU3ex7AoKQAAAABJRU5ErkJggg==","orcid":"","institution":"Mersin City Training and Research Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"Kutta","lastName":"ÇELİK","suffix":""},{"id":628032178,"identity":"637a8e29-6578-467b-a1b5-a8d9266a093d","order_by":1,"name":"Mustafa UĞUZ","email":"","orcid":"","institution":"Mersin City Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mustafa","middleName":"","lastName":"UĞUZ","suffix":""},{"id":628032184,"identity":"8b738366-1ffc-4389-ad8f-743c7414506e","order_by":2,"name":"Fatih ERDEM","email":"","orcid":"","institution":"Mersin City Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Fatih","middleName":"","lastName":"ERDEM","suffix":""},{"id":628032196,"identity":"6d7c63c5-b0b9-4fdd-bca7-e1c8830308b4","order_by":3,"name":"Berfin Çirkin DORUK","email":"","orcid":"","institution":"Mersin City Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Berfin","middleName":"Çirkin","lastName":"DORUK","suffix":""},{"id":628032205,"identity":"cf6be8ab-f121-460b-8503-a237295abfde","order_by":4,"name":"Mutlu ALIMLI","email":"","orcid":"","institution":"Mersin City Training and Research Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mutlu","middleName":"","lastName":"ALIMLI","suffix":""}],"badges":[],"createdAt":"2026-04-07 14:38:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9346562/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9346562/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107640048,"identity":"45d11385-8a36-47dd-a391-0a9405663fcb","added_by":"auto","created_at":"2026-04-23 13:11:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":179271,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest Plot Demonstrating Odds Ratios and 95% Confidence Intervals for Independent Risk Factors of Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9346562/v1/6aba148a3aa92e3633fc5798.jpeg"},{"id":107640060,"identity":"573b3630-0f2d-46aa-a00a-3400da28a316","added_by":"auto","created_at":"2026-04-23 13:11:44","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":235934,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver Operating Characteristic Curve of Fused Vertebra Number for Predicting Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9346562/v1/c122b3560e30d16944276c39.jpeg"},{"id":107639982,"identity":"30e4dba2-0f11-4f5b-a90c-6d927ce17a83","added_by":"auto","created_at":"2026-04-23 13:11:39","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":192298,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTemporal Distribution of Isolated Microorganisms According to Postoperative Spinal Implant Infection Onset\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9346562/v1/e70cdfde31cb6319cdacde9c.jpeg"},{"id":107640070,"identity":"2a813f3b-87dc-484b-880f-813848646408","added_by":"auto","created_at":"2026-04-23 13:11:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":930635,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9346562/v1/e5f5fb52-9710-4ce6-8b6e-87facb7fba68.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Postoperative Spinal Implant Infection According to EBJIS Criteria: Risk Factors in Posterior Spinal Instrumentation Surgery","fulltext":[{"header":"Background","content":"\u003cp\u003eSpinal surgery is widely performed for the management of degenerative, traumatic, deformity-related, and neoplastic spinal disorders. However, parallel to the increasing use of spinal instrumentation, postoperative spinal implant infection (PSII) has emerged as a significant clinical challenge.\u003c/p\u003e \u003cp\u003ePSII is associated with substantial morbidity, prolonged hospital stay, repeated surgical interventions, increased healthcare costs, and, in severe cases, mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Reported incidence rates vary widely, ranging from 0.7% to 18%, depending on patient characteristics and surgical factors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The presence of implanted materials facilitates bacterial adhesion and biofilm formation, which reduces antibiotic penetration and contributes to the persistence and chronicity of infection.\u003c/p\u003e \u003cp\u003ePSII is commonly classified according to the timing of onset as early, delayed, and late infection. While early infections typically present with more pronounced clinical findings, delayed and late infections often manifest with subtle and nonspecific symptoms, further complicating diagnosis.\u003c/p\u003e \u003cp\u003eThe diagnosis of PSII remains challenging. Clinical findings lack specificity, laboratory parameters are often nonspecific, and imaging modalities may be limited by metal-related artifacts [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, prior antibiotic exposure may reduce the yield of microbiological cultures, delaying identification of the causative pathogen.\u003c/p\u003e \u003cp\u003eManagement strategies for PSII include targeted antimicrobial therapy, surgical debridement, implant retention or removal, and, when necessary, re-instrumentation. Implant retention is generally preferred in early infections (within the first 3 postoperative months), whereas implant removal is often unavoidable in late infections [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, implant removal may lead to spinal instability, deformity progression, and pseudarthrosis.\u003c/p\u003e \u003cp\u003eA major limitation in the literature is the lack of universally accepted diagnostic criteria for implant-related infections, which reduces comparability across studies. Although many studies have used the Centers for Disease Control and Prevention (CDC) surgical site infection definitions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], these criteria are primarily designed for acute postoperative infections and may not adequately capture chronic biofilm-related implant infections. To address these limitations, the EBJIS has proposed a standardized diagnostic framework integrating clinical findings, laboratory markers, microbiological evidence, and histopathological evaluation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the increasing use of EBJIS criteria in implant-related infections, studies specifically evaluating risk factors for PSII based on this standardized definition remain limited, and the available evidence is heterogeneous.\u003c/p\u003e \u003cp\u003eTherefore, the aim of this study was to evaluate PSII according to EBJIS criteria and to analyze associated clinical, laboratory, and perioperative risk factors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study was conducted at the Department of Neurosurgery, Mersin City Training and Research Hospital. All consecutive adult patients (\u0026ge;\u0026thinsp;18 years) who underwent posterior spinal instrumentation surgery between January 2025 and January 2026 were included.\u003c/p\u003e \u003cp\u003ePatient data were retrieved from the electronic hospital information system (Hospital Information System, HIS), and all eligible cases were systematically screened. Patients who developed postoperative spinal implant infection (PSII) were identified through retrospective evaluation.\u003c/p\u003e \u003cp\u003eInclusion and exclusion criteria\u003c/p\u003e \u003cp\u003eOnly patients who underwent posterior spinal fusion with instrumentation were included. Patients who underwent vertebroplasty alone, isolated laminectomy, or non-instrumented surgery for sacral, coccygeal, or pelvic fractures were excluded.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFollow-up\u003c/h3\u003e\n\u003cp\u003eAll patients were followed for a minimum of 6 months postoperatively. This follow-up duration was considered sufficient based on previous literature evaluating early and delayed implant-related infections.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe following variables were collected:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eDemographic characteristics: age, sex, blood group\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLaboratory parameters: hemoglobin, white blood cell count, C-reactive protein (CRP), total protein, serum albumin\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eComorbidities: diabetes mellitus, hypertension, coronary artery disease, malignancy, and other coexisting conditions\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePerioperative variables: American Society of Anesthesiologists (ASA) score, preoperative and postoperative length of hospital stay, perioperative glucocorticoid use, perioperative blood transfusion, postoperative intensive care unit (ICU) admission, postoperative positioning, and number of fused vertebrae\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eMicrobiological assessment\u003c/h3\u003e\n\u003cp\u003ePatients with suspected PSII were evaluated based on clinical, laboratory, and microbiological findings. When available, intraoperative deep tissue samples were obtained, and microbiological culture results were recorded. Whenever feasible, multiple deep tissue samples were collected and processed using standard microbiological methods to increase diagnostic accuracy.\u003c/p\u003e\n\u003ch3\u003ePerioperative infection prevention protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003ePerioperative infection prevention protocol\u003c/div\u003e \u003cp\u003eIn our institution, prophylactic antibiotics are routinely administered 30 minutes prior to skin incision. In prolonged procedures, additional intraoperative doses are administered every 3 hours. Diluted povidone\u0026ndash;iodine irrigation is routinely used intraoperatively in accordance with CDC recommendations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of PSII\u003c/h2\u003e \u003cp\u003ePSII was defined according to the \u0026ldquo;confirmed infection\u0026rdquo; criteria proposed by the EBJIS [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Patients with suspected infection were retrospectively evaluated using clinical, laboratory, microbiological, and, when available, histopathological findings.\u003c/p\u003e \u003cp\u003eCases were classified as confirmed PSII if at least one of the following criteria was present:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSinus tract communicating with the implant\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePurulence surrounding the implant\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIsolation of the same microorganism from at least two separate deep tissue samples\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHistopathological evidence of acute inflammation\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSubgroup analysis\u003c/h3\u003e\n\u003cp\u003eFor subgroup analysis, thoracic and thoracolumbar procedures were evaluated as a single group, whereas lumbar and lumbosacral procedures were analyzed separately.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were tested for normality using the Shapiro\u0026ndash;Wilk test. Non-normally distributed variables were expressed as median (interquartile range, IQR), while categorical variables were presented as number and percentage.\u003c/p\u003e \u003cp\u003eComparisons between groups were performed using the Mann\u0026ndash;Whitney U test for continuous variables and the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables, as appropriate.\u003c/p\u003e \u003cp\u003eUnivariate logistic regression analysis was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs). Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.10 in univariate analysis and those considered clinically relevant were included in the multivariate logistic regression model.\u003c/p\u003e \u003cp\u003eGiven the limited number of PSII events (n\u0026thinsp;=\u0026thinsp;18), the number of variables included in the final multivariate model was intentionally restricted to minimize the risk of overfitting.\u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) analysis was performed to evaluate the discriminative performance of the number of fused vertebrae in predicting PSII.\u003c/p\u003e \u003cp\u003eA p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All statistical analyses were conducted using SPSS version 27.0 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e \u003c/div\u003e\n\u003ch2\u003eEthical approval\u003c/h2\u003e\n\u003cp\u003eThis study was approved by Non-Interventional Clinical Research Ethics Committee, Mersin City Training and Research Hospital, Mersin, T\u0026uuml;rkiye, and the requirement for informed consent was waived due to the retrospective study design.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 224 patients who underwent posterior spinal instrumentation surgery were included in the study. PSII developed in 18 patients, corresponding to an incidence of 8.0%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe relationship between demographic characteristics and PSII was evaluated (Table 1). No significant associations were found between PSII and sex, diabetes mellitus, hypertension, congestive heart failure, peripheral neuropathy, depression, rheumatoid arthritis, chronic obstructive pulmonary disease, epilepsy, malignancy, thyroid disorders, or chronic kidney disease (all p \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe median age was similar between patients with and without PSII (58.5 vs 57 years, p = 0.242).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePreoperative laboratory parameters were compared between groups (Table 2). Patients who developed PSII had significantly higher CRP levels and lower serum albumin levels compared to those without infection (p = 0.041 and p = 0.048, respectively).\u003c/p\u003e\n\u003cp\u003eNo statistically significant differences were observed for hemoglobin, white blood cell count, neutrophil count, lymphocyte count, platelet count, total protein, or glucose levels (all p \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003eUnivariate analysis of surgical and perioperative variables is presented in Table 3. ASA score \u0026ge;3 (OR: 3.12; 95% CI: 1.17\u0026ndash;8.29; p = 0.025), emergency surgery (OR: 8.12; 95% CI: 2.12\u0026ndash;31.10; p = 0.002), perioperative steroid use (OR: 3.04; 95% CI: 1.14\u0026ndash;8.08; p = 0.039), low molecular weight heparin use (OR: 3.48; 95% CI: 1.30\u0026ndash;9.27; p = 0.019), prone postoperative positioning (OR: 4.41; 95% CI: 1.57\u0026ndash;12.38; p = 0.007), and postoperative ICU admission (OR: 4.61; 95% CI: 1.64\u0026ndash;12.98; p = 0.006) were significantly associated with PSII.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo significant association was observed between the number of fused vertebrae and PSII (p = 0.459).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePreoperative and postoperative hospital length of stay were compared between groups (Table 4). No statistically significant differences were found between patients with and without PSII (p = 0.770 and p = 0.495, respectively).\u003c/p\u003e\n\u003cp\u003eVariables with p \u0026lt; 0.10 in univariate analysis and considered clinically relevant were included in the multivariate logistic regression model. Due to the limited number of PSII events, the number of variables included in the model was restricted to minimize overfitting.\u003c/p\u003e\n\u003cp\u003eIn multivariate analysis, only emergency surgery remained independently associated with PSII (OR: 6.48; 95% CI: 1.28\u0026ndash;32.70; p = 0.024). ASA score and ICU admission did not retain statistical significance (Table 5).\u003c/p\u003e\n\u003cp\u003eThe results of the regression analysis are illustrated in the forest plot (Figure 1).\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristic (ROC) analysis demonstrated that the number of fused vertebrae had limited discriminative ability for predicting PSII (AUC = 0.613). A threshold of \u0026ge;5 fused vertebrae provided the best balance between sensitivity (44.4%) and specificity (84.5%) (Figure 2).\u003c/p\u003e\n\u003cp\u003eMicrobiological evaluation revealed that \u003cem\u003ecoagulase-negative staphylococci\u003c/em\u003e were the most frequently isolated organisms, followed by \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003eEscherichia coli\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eAmong microbiologically confirmed cases, 12 of 18 infections occurred within the first 3 postoperative weeks, while the remaining cases developed between 3 weeks and 3 months (Figure 3), demonstrating a predominance of early postoperative infections.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003ePSII represents a clinically distinct entity compared to conventional surgical site infections due to early biofilm formation on implant surfaces, which may lead to persistent infection, delayed diagnosis, and reduced response to antimicrobial therapy.\u003c/p\u003e\n\u003cp\u003eThe use of EBJIS criteria in this study enhances diagnostic specificity by focusing on confirmed infection cases, thereby reducing misclassification bias in a retrospective cohort.\u003c/p\u003e\n\u003cp\u003eThe incidence of PSII in our study was 8%, which falls within the range reported in the literature [2]. This relatively higher rate may be attributed to the inclusion of only posterior instrumentation procedures and the complexity of the surgical population [8,9].\u003c/p\u003e\n\u003cp\u003eDemographic factors such as age and sex have shown inconsistent associations with infection risk in previous studies [1,10,11]. In our cohort, the mean age of the patients was 55.6 \u0026plusmn; 12.0 years (range, 22\u0026ndash;84 years), and no significant association was observed between age, sex, and the development of PSII. This finding suggests that perioperative and surgical factors may play a more prominent role than baseline patient characteristics in determining infection risk.\u003c/p\u003e\n\u003cp\u003eIn the microbiological evaluation, \u003cem\u003ecoagulase-negative staphylococci\u003c/em\u003e were the most frequently isolated pathogens, which is consistent with the existing literature [12]. \u003cem\u003eCoagulase-negative staphylococci\u0026nbsp;\u003c/em\u003eand \u003cem\u003eStaphylococcus aureus\u003c/em\u003e are commonly implicated due to their strong adhesion to implant surfaces and their ability to form biofilms. In addition, \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e species were also identified in our cohort, suggesting the potential contribution of perioperative contamination and nosocomial microorganisms. These findings support the importance of obtaining multiple deep tissue samples during revision surgery to improve diagnostic accuracy.\u003c/p\u003e\n\u003cp\u003eThe temporal distribution of infections observed in our study was also consistent with previously reported patterns [13,14]. Among microbiologically confirmed PSII cases, 12 of 18 occurred within the first 3 postoperative weeks, while the remaining cases developed between 3 weeks and 3 months (Figure 3). The predominance of infections in the early postoperative period underscores the importance of close clinical monitoring during this critical timeframe.\u003c/p\u003e\n\u003cp\u003eInflammatory biomarkers have been widely investigated in the diagnosis of postoperative infections [15\u0026ndash;17]. Among laboratory parameters, CRP levels were significantly elevated in patients who developed PSII. However, this finding should be interpreted with caution, as postoperative inflammatory responses may also lead to increased CRP levels independent of infection. Similarly, serum albumin levels were lower in the infected group. Hypoalbuminemia has been reported as an important biochemical marker associated with an increased risk of postoperative infections following spinal surgery. Previous studies have demonstrated that hypoalbuminemia is associated with prolonged hospitalization and a higher risk of postoperative infections [18\u0026ndash;20]. Nevertheless, since albumin was not retained in the final multivariate model, it should be considered as an associative rather than an independent predictor.\u003c/p\u003e\n\u003cp\u003eIn univariate analysis, several perioperative variables\u0026mdash;including higher ASA score, intensive care unit admission, perioperative use of low-molecular-weight heparin, glucocorticoid exposure, and prone postoperative positioning\u0026mdash;were found to be associated with PSII. However, these associations did not remain significant in the multivariate analysis, suggesting that these factors may reflect a cumulative perioperative risk burden rather than independent effects.\u003c/p\u003e\n\u003cp\u003eVariables with p \u0026lt; 0.10 in univariate analysis and deemed clinically relevant were included in the multivariate logistic regression model, while limiting the number of variables to avoid overfitting due to the relatively low number of infection events. Emergency surgery remained independently associated with PSII in the multivariate model. This finding may be explained by limited preoperative optimization, increased physiological instability of patients, and the complexity of surgical procedures under emergency conditions. Additionally, factors such as increased blood loss and prolonged operative time may further contribute to the elevated risk of postoperative infection. These results underscore the importance of implementing effective perioperative infection prevention strategies in emergency spinal surgeries.\u003c/p\u003e\n\u003cp\u003eAlthough the number of fused vertebrae has been discussed as a potential risk factor in the literature [12,21], the ROC analysis in our study demonstrated that this variable had limited discriminative ability in predicting PSII (AUC = 0.613). This finding suggests that the number of fused vertebrae alone is not a reliable predictor of PSII. Furthermore, no significant association was observed between the anatomical region of instrumentation and the development of infection.\u003c/p\u003e\n\u003cp\u003eIn conclusion, emergency surgery appears to be an independent risk factor for PSII. Elevated CRP levels and hypoalbuminemia should be interpreted as accompanying findings that require careful clinical evaluation. The use of standardized diagnostic criteria, such as those proposed by EBJIS, may improve the reliability of diagnosing implant-related infections.\u003c/p\u003e\n\u003cp\u003eThese findings may contribute to improved perioperative risk stratification and help guide targeted infection prevention strategies in high-risk patient populations. Future studies incorporating serial biomarker measurements may further improve diagnostic accuracy.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003ePostoperative spinal implant infection remains a clinically important complication following spinal instrumentation surgery. In this study, emergency surgery was independently associated with PSII, whereas elevated CRP levels and hypoalbuminemia were identified as associated findings rather than independent predictors.\u003c/p\u003e\n\u003cp\u003eThe application of standardized diagnostic criteria such as EBJIS may enhance diagnostic consistency and improve comparability across studies. Larger prospective studies are warranted to further clarify independent risk factors and optimize preventive strategies. Emergency spinal instrumentation procedures should be considered high-risk settings for PSII, requiring enhanced perioperative infection prevention strategies and closer postoperative surveillance.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eASA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Anesthesiologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCenters for Disease Control and Prevention\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic obstructive pulmonary disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEBJIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEuropean Bone and Joint Infection Society\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHospital Information System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eIntensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLMWH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLow molecular weight heparin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSII\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePostoperative spinal implant infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis study was approved by the Non-Interventional Clinical Research Ethics Committee of Mersin City Training and Research Hospital (approval date: 25 March 2026; decision no. 190). Due to the retrospective nature of the study, the requirement for informed consent was waived by the Ethics Committee.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author upon reasonable request and with permission of the institutional ethics committee.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors declare that no financial support was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization : AK\u0026Ccedil;\u003c/p\u003e\n\u003cp\u003eMethodology: AK\u0026Ccedil;, MU\u003c/p\u003e\n\u003cp\u003eData collection and/or processing: FE, B\u0026Ccedil;D\u003c/p\u003e\n\u003cp\u003eFormal analysis: MU, MA\u003c/p\u003e\n\u003cp\u003eInvestigation: AK\u0026Ccedil;, B\u0026Ccedil;D\u003c/p\u003e\n\u003cp\u003eWriting: AK\u0026Ccedil;, FE.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePawar AY, Biswas SK. 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Spine (Phila Pa 1976). 2020;45(23):E1564\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/BRS.0000000000003684\u003c/span\u003e\u003cspan address=\"10.1097/BRS.0000000000003684\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Liu P, You J. Risk factors for surgical site infection following spinal surgery: a meta-analysis. Medicine (Baltimore). 2022;101(8):e28836. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000028836\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000028836\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline Demographic and Clinical Characteristics of Patients With and Without Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithout PSII \u0026nbsp;(n=206)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWith PSII (n=18) (n=18)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eAge, median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e57 (14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e58.5 (16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eFemale sex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e114 (55.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e10 (55.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eDiabetes mellitus, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e34 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e70 (34.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e6 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCongestive heart failure, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;5 (2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003ePeripheral neuropathy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e11 (5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.675\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eDepression, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e18 (8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eRheumatoid arthritis, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e7 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eCOPD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e12 (5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eEpilepsy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e3 (1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e1 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eMalignancy, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e6 (2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eHypothyroidism, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e10 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eHyperthyroidism, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e10 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eChronic kidney disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e4 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e2 (11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e0.374\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(Values are presented as median (interquartile range, IQR) or number (%).\u0026nbsp;\u003cbr\u003e\u0026nbsp;Mann\u0026ndash;Whitney U test was used for continuous variables; chi-square test or Fisher\u0026rsquo;s exact test was used for categorical variables. \u0026nbsp;PSII: postoperative spinal implant infection; COPD: chronic obstructive pulmonary disease.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Comparison of Preoperative Laboratory Parameters According to Postoperative Spinal Implant Infection Status\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory parameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithout PSII (n=206) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eWith PSII (n=18) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e12.6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e11.9 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eWhite blood cell (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e8.7 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e10.1 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.080\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eNeutrophil count (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e6.1 (3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e7.9 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eLymphocyte count (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.9 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e1.6 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003ePlatelet count (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e256 (92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e278 (101)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eC-reactive protein (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e0.9 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.8 (4.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eSerum albumin (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.9 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e3.5 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.048\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eTotal protein (g/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e6.8 (0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e6.5 (0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e118 (40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 25%;\"\u003e\n \u003cp\u003e134 (46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(Values are presented as median (interquartile range). Mann\u0026ndash;Whitney U test was used for comparisons. PSII: postoperative spinal implant infection, IQR: interquartile range)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Univariate Analysis of Surgical and Perioperative Risk Factors Associated With Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePSII (+) / Exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds Ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eASA \u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9 / 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.17\u0026ndash;8.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eEmergency surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4 / 11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e8.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e2.12\u0026ndash;31.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eFusion \u0026ge;4 vertebrae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10 / 100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0.61\u0026ndash;4.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePerioperative steroid use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10 / 70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.14\u0026ndash;8.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.039\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePerioperative LMWH use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e9 / 55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.30\u0026ndash;9.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eProne postoperative position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 / 33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.57\u0026ndash;12.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePostoperative ICU stay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7 / 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1.64\u0026ndash;12.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(Odds ratios (ORs) were calculated using univariate logistic regression. CI: confidence interval; ASA: American Society of Anesthesiologists; LMWH: low molecular weight heparin; ICU: intensive care unit.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Comparison of Perioperative Hospitalization Durations Between Patients With and Without Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWithout PSII (n=206)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;(median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWith PSII (n=18)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePreoperative hospital stay (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.770\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePostoperative hospital stay (days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.495\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(Values are presented as median. Mann\u0026ndash;Whitney U test was used for comparisons. PSII: postoperative spinal implant infection.)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Multivariate Logistic Regression Analysis of Independent Predictors of Postoperative Spinal Implant Infection\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds Ratio (OR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmergency surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.48\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e1.28 \u0026ndash; 32.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eASA \u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.79 \u0026ndash; 6.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003eICU admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.48 \u0026ndash; 7.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(Variables with p \u0026lt; 0.10 in univariate analysis and clinical relevance were entered into the multivariate logistic regression model. To reduce overfitting risk, the number of variables was limited considering the low number of PSII events. OR: odds ratio; CI: confidence interval; ICU: intensive care unit; ASA: American Society of Anesthesiologists.)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Postoperative spinal implant infection, Spinal instrumentation, EBJIS criteria, Risk factors, Biofilm, Emergency surgery, C-reactive protein, Hypoalbuminemia","lastPublishedDoi":"10.21203/rs.3.rs-9346562/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9346562/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePostoperative spinal implant infection (PSII) is a clinically significant complication following spinal instrumentation, with diagnostic challenges related to biofilm formation and the lack of standardized criteria. This study aimed to evaluate PSII according to the European Bone and Joint Infection Society (EBJIS) criteria and to identify associated clinical, laboratory, and perioperative risk factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eIn this retrospective cohort study, 224 adult patients who underwent posterior spinal instrumentation surgery between January 2025 and January 2026 were included. Demographic characteristics, comorbidities, laboratory parameters, perioperative variables, and microbiological findings were obtained from electronic medical records. PSII was defined according to the EBJIS “confirmed infection” criteria. Variables with p \u0026lt; 0.10 in univariate analysis were considered for multivariate logistic regression. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003ePSII developed in 18 patients (8.0%). No significant association was found between PSII and demographic variables or comorbidities. Elevated C-reactive protein (CRP) levels and lower serum albumin levels were associated with PSII (p \u0026lt; 0.05). In univariate analysis, ASA score ≥3, emergency surgery, perioperative steroid use, low molecular weight heparin use, prone positioning, and intensive care unit admission were significantly associated with PSII. In multivariate analysis, only emergency surgery remained independently associated with PSII (OR: 6.48; 95% CI: 1.28–32.70; p = 0.024). Receiver operating characteristic (ROC) analysis demonstrated limited discriminative ability of the number of fused vertebrae (AUC = 0.613).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003ePSII remains an important complication following spinal instrumentation surgery. Emergency surgery was independently associated with PSII, while CRP elevation and hypoalbuminemia were identified as associated findings rather than independent predictors. The use of standardized diagnostic approaches such as EBJIS may improve diagnostic consistency and facilitate more reliable risk stratification.\u003c/p\u003e","manuscriptTitle":"Postoperative Spinal Implant Infection According to EBJIS Criteria: Risk Factors in Posterior Spinal Instrumentation Surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 13:10:48","doi":"10.21203/rs.3.rs-9346562/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-11T18:26:38+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-18T21:46:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-16T22:03:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23694008793175861697514624311930918454","date":"2026-04-16T21:56:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50501486689688441736822359578464494078","date":"2026-04-16T00:45:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168428266039173074845111212888065968537","date":"2026-04-15T22:35:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-15T22:11:39+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-15T07:48:41+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-13T07:16:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-12T11:03:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Musculoskeletal Disorders","date":"2026-04-12T11:00:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-musculoskeletal-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmsd","sideBox":"Learn more about [BMC Musculoskeletal Disorders](http://bmcmusculoskeletdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12891","title":"BMC Musculoskeletal Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10979bed-eabb-470c-be8c-85cccfc9a49e","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-11T18:26:38+00:00","index":51,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-23T13:10:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 13:10:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9346562","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9346562","identity":"rs-9346562","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}