Effect of pre-operative HbA1c and blood glucose level on the surgical site infection after lumbar instrumentation surgery

Risk factors for deep surgical site infection following open posterior lumbar fusion: A retrospective case-control study

This study aimed to identify risk factors for deep surgical site infection (SSI) following open posterior lumbar fusion (OPLF). We retrospectively analyzed the clinical data of patients who underwent OPLF between January 2014 and December 2022. Patients were divided into SSI and non-SSI groups according to whether deep SSI occurred following OPLF. Patient's sex, age, body mass index (BMI), history of diabetes mellitus and smoking, American Society of Anesthesiologists score, surgical segment, surgical time, preoperative albumin level, local use of vancomycin, and cerebrospinal fluid (CSF) leakage were compared between the 2 groups. Univariate and multivariate logistic regression analyses were used to identify risk factors for postoperative deep SSI. The deep SSI rate was 5.0% (63/1256). Among them, age (P < .001), BMI (P = .008), surgical segment (P < .001), surgical time (P < .001), prevalence of diabetes mellitus (P = .036), and CSF leakage (P < .001) were significantly higher in the SSI group, whereas the preoperative albumin level (P < .001) and proportion of local use of vancomycin (P = .046) were significantly lower in the SSI group than those in the non-SSI group. Multivariate analysis indicated that higher age (P = .046, odds ratio [OR]: 1.036, 95% confidence interval [CI]: 1.001-1.073), BMI (P = .038, OR: 1.113, 95% CI: 1.006-1.232), lower preoperative albumin level (P = .041, OR: 0.880, 95% CI: 0.778-0.995), higher surgical segment (P = .004, OR: 2.241, 95% CI: 1.297n3.871), and CSF leakage (P = .046, OR: 2.372, 95% CI: 1.015-5.545) were risk factors, and the local use of vancomycin (P < .001, OR: 0.093, 95% CI: 0.036-0.245) was the protective factor for deep SSI following OPLF. We identified 5 risk factors (older age and BMI, lower preoperative albumin level, higher surgical segment, and CSF leakage) and 1 protective factor (local use of vancomycin powder) for deep SSI following OPLF. To address these risk and protective factors, comprehensive evaluations and recommendations should be provided to patients to reduce SSI rates.

Risk factors for surgical site infection after percutaneous endoscopic lumbar discectomy

The objective of this study was to investigate the risk factors associated with surgical site infection (SSI) after percutaneous endoscopic lumbar discectomy (PELD) in patients with lumbar disc herniation (LDH). A retrospective analysis was performed on a cohort of 335 patients who underwent PELD between January 2016 and January 2023. Data were derived from the Hospital Information System (HIS), and a comprehensive statistical assessment was performed using IBM SPSS Statistics version 25.0. Both univariate and multivariate logistic regression analyses assessed a range of risk determinants, such as age, body mass index (BMI), comorbidities, laboratory test parameters and surgery-related variables. The incidence of SSI after PELD was 2.7% (9/335). Univariate analysis highlighted BMI, diabetes mellitus, long-term corticosteroid consumption, surgical time and cerebrospinal fluid leakage as significant predictors of SSI. Multivariate logistic regression identified BMI, diabetes mellitus, long-term corticosteroid consumption, surgical time and cerebrospinal fluid leakage as significant risk factors for SSI after PELD. High BMI, diabetes mellitus, long-term corticosteroid consumption, long surgical time and postoperative cerebrospinal fluid leakage are predisposing factors for SSI in patients undergoing PELD. Precise interventions focused on such risk components, including careful preoperative assessment and strategic postoperative care, are essential to reduce the incidence of SSI and improve surgical efficacy.

A predictive nomogram for surgical site infection in patients who received clean orthopedic surgery: a retrospective study

BACKGROUND

Surgical site infection (SSI) is a common and serious complication of elective clean orthopedic surgery that can lead to severe adverse outcomes. However, the prognostic efficacy of the current staging systems remains uncertain for patients undergoing elective aseptic orthopedic procedures. This study aimed to identify high-risk factors independently associated with SSI and develop a nomogram prediction model to accurately predict the occurrence of SSI.

METHODS

A total of 20,960 patients underwent elective clean orthopedic surgery in our hospital between January 2020 and December 2021, of whom 39 developed SSI; we selected all 39 patients with a postoperative diagnosis of SSI and 305 patients who did not develop postoperative SSI for the final analysis. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted in the training cohort to screen for independent risk factors of SSI, and a nomogram prediction model was developed. The predictive performance of the nomogram was compared with that of the National Nosocomial Infections Surveillance (NNIS) system. Decision curve analysis (DCA) was used to assess the clinical decision-making value of the nomogram.

RESULTS

The SSI incidence was 0.186%. Univariate and multivariate logistic regression analysis identified the American Society of Anesthesiology (ASA) class (odds ratio [OR] 1.564 [95% confidence interval (CI) 1.029-5.99, P = 0.046]), operative time (OR 1.003 [95% CI 1.006-1.019, P < 0.001]), and D-dimer level (OR 1.055 [95% CI 1.022-1.29, P = 0.046]) as risk factors for postoperative SSI. We constructed a nomogram prediction model based on these independent risk factors. In the training and validation cohorts, our predictive model had concordance indices (C-indices) of 0.777 (95% CI 0.672-0.882) and 0.732 (95% CI 0.603-0.861), respectively, both of which were superior to the C-indices of the NNIS system (0.668 and 0.543, respectively). Calibration curves and DCA confirmed that our nomogram model had good consistency and clinical predictive value, respectively.

CONCLUSIONS

Operative time, ASA class, and D-dimer levels are important clinical predictive indicators of postoperative SSI in patients undergoing elective clean orthopedic surgery. The nomogram predictive model based on the three clinical features demonstrated strong predictive performance, calibration capabilities, and clinical decision-making abilities for SSI.