Establishment of a suitable combination of serological markers to diagnose surgical site infection following spine surgery: A novel surgical site infection scoring system

Predicting Surgical Site Infections in Spine Surgery: Association of Postoperative Lymphocyte Reduction

OBJECTIVE

Postoperative lymphopenia is reported as an excellent indicator to predict surgical-site infection (SSI) after spine surgery. However, there is still controversy concerning which serological markers can predict spinal SSI. This study aims to evaluate excellent and early indicators for detecting SSI, focusing on spine instrumented surgery.

MATERIALS AND METHODS

This study included 268 patients who underwent spinal instrumented surgery from January 2022 to December 2023 (159 female and 109 male, average 62.9 years). The SSI group included 20 patients, and the non-SSI group comprised 248 patients. Surgical time, intraoperative blood loss, and glycemic levels were measured in both groups. The complete blood cell counts, differential counts, albumin, and C-reactive protein (CRP) levels were measured pre-surgery and postoperative on Days 1, 3, and 7. In comparing the groups, the Mann-Whitney U test analysis was used for continuous variables, while the chi-squared test and Fisher's exact test were used for dichotomous variables.

RESULTS

The incidence of SSI after spinal instrumentation was 7.46% and was relatively higher in scoliosis surgery. The SSI group had significantly longer surgical times (248 min vs. 180 min, p = 0.0004) and a higher intraoperative blood loss (772 mL vs. 372 mL, p < 0.0001) than the non-SSI group. In the SSI group, the Day 3 (10.5 ± 6.2% vs. 13.8 ± 6.0%, p = 0.012) and Day 7 (14.4 ± 4.8% vs. 18.8 ± 7.1%, p = 0.012) lymphocyte ratios were lower than the non-SSI group. Albumin levels on Day 1 in the SSI group were lower than in the non-SSI group (2.94 ± 0.30 mg/dL vs. 3.09 ± 0.38 mg/dL, p = 0.045). There is no difference in CRP and lymphocyte count between the two groups.

CONCLUSIONS

SSI patients had lower lymphocyte percentages than non-SSI patients, which was a risk factor for SSI, with constant high inflammation. The Day 3 lymphocyte percentage may predict SSI after spinal instrumented surgery.

Efficacy of Antibiotic Bone Cement in the Treatment of Burkholderia cepacia Infection After Spinal Internal Fixation Surgery: Case Report and Literature Review

BACKGROUND

In recent years, the number of spinal internal fixation operations has increased significantly, correlating with an elevated risk of postoperative surgical site infection and a rising incidence rate. While the conventional treatment approach involves surgical debridement combined with antibiotic administration, there is a notable gap in reported strategies for Burkholderia cepacia infection and patients exhibiting multidrug resistance.

METHODS

Surgical site infection occurred in a patient following internal fixation surgery for thoracic vertebral fractures. Despite the application of systemic antibiotics and regular dressing changes, no improvement was observed. Bacterial culture and drug sensitivity experiments revealed a multidrug-resistant Burkholderia cepacia infection. Two comprehensive debridement procedures were performed along with continuous post-operative irrigation combined with antibiotic administration; however, no significant improvement was observed. The patient's infection was significantly controlled following treatment with vancomycin loaded bone cement.

RESULTS

Following spinal internal fixation surgery, the management of a B. cepacian infection with multidrug resistance presented a significant challenge, despite the application of debridement procedures and systemic antibiotics. In this case, after 20 days of treatment with vancomycin-loaded bone cement, the patient's C-reactive protein level decreased to 54 mg/L, was normalized by February, and normal levels were maintained in the surgical area 1 month and 6 months after bone cement removal.

CONCLUSIONS

The use of vancomycin-loaded bone cement proves effective in treating postoperative B. cepacian infection in a multidrug-resistant case following spinal internal fixation surgery.

Using multiple indicators to predict the risk of surgical site infection after ORIF of tibia fractures: a machine learning based study

OBJECTIVE

Surgical site infection (SSI) are a serious complication that can occur after open reduction and internal fixation (ORIF) of tibial fractures, leading to severe consequences. This study aimed to develop a machine learning (ML)-based predictive model to screen high-risk patients of SSI following ORIF of tibial fractures, thereby aiding in personalized prevention and treatment.

METHODS

Patients who underwent ORIF of tibial fractures between January 2018 and October 2022 at the Department of Emergency Trauma Surgery at Ganzhou People's Hospital were retrospectively included. The demographic characteristics, surgery-related variables and laboratory indicators of patients were collected in the inpatient electronic medical records. Ten different machine learning algorithms were employed to develop the prediction model, and the performance of the models was evaluated to select the best predictive model. Ten-fold cross validation for the training set and ROC curves for the test set were used to evaluate model performance. The decision curve and calibration curve analysis were used to verify the clinical value of the model, and the relative importance of features in the model was analyzed.

RESULTS

A total of 351 patients who underwent ORIF of tibia fractures were included in this study, among whom 51 (14.53%) had SSI and 300 (85.47%) did not. Of the patients with SSI, 15 cases were of deep infection, and 36 cases were of superficial infection. Given the initial parameters, the ET, LR and RF are the top three algorithms with excellent performance. Ten-fold cross-validation on the training set and ROC curves on the test set revealed that the ET model had the best performance, with AUC values of 0.853 and 0.866, respectively. The decision curve analysis and calibration curves also showed that the ET model had the best clinical utility. Finally, the performance of the ET model was further tested, and the relative importance of features in the model was analyzed.

CONCLUSION

In this study, we constructed a multivariate prediction model for SSI after ORIF of tibial fracture through ML, and the strength of this study was the use of multiple indicators to establish an infection prediction model, which can better reflect the real situation of patients, and the model show great clinical prediction performance.

Neutrophil-lymphocyte ratio as a predictive marker for postoperative infectious complications: A systematic review and meta-analysis

Objective

Postoperative infection is a common but costly complication. The neutrophil-lymphocyte ratio is a promising marker for the identification of postsurgical infectious events. We aimed to perform this meta-analysis to assessed the accuracy of the neutrophil-lymphocyte ratio for the prediction of postsurgical infection.

Methods

We searched PubMed, Embase, Web of Science, and Cochrane Library without language restriction from their inceptions to April 2022, and checked reference lists of included studies. Studies were included if they assessed predictive accuracy of neutrophil-lymphocyte ratio for postsurgical infection. We estimated its predictive value and explored the source of heterogeneity. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess methodological quality and the Deeks' test to evaluate publication bias. The bivariate model and hierarchical summary receiver operating characteristic (HSROC) curve were used for meta-analysis and generated a summary receiver operating characteristic space (ROC) curve.

Results

Our search returned 379 reports, of which 12 fulfilled the inclusion criteria, accounting for 4375 cases. The bivariate analysis yielded a pooled sensitivity of 0.77 (95%C.I.: 0.65-0.85) and specificity of 0.78 (95%C.I.: 0.67-0.86). Pooled positive LR and negative LR were 3.48 (95%C.I.: 2.26-5.36) and 0.30 (95%C.I.: 0.20-0.46), respectively. A negative LR of 0.30 reduces the post-test probability to 2% for a negative test result. The area under of receiver operating characteristic curve was 0.84 (95%C.I.: 0.80-0.87). Subgroups comparisons revealed difference by study design, surgical site, presentence of implant, time of sampling, type of infection event and prevalence of infection. The Deeks' test showed no publication bias. The sensitivity analysis showed no study affected the robustness of combined results.

Conclusions

Low-certainty evidence suggests that the neutrophil-lymphocyte ratio is a helpful marker for predicting postoperative infectious complication. The negative predictive value of the neutrophil-lymphocyte ratio enables for reliable exclusion of postoperative infection.Trial registrationPROSPERO registration number CRD42022321197. Registered on 27 April 2022.