Association of predictive factors and neurosurgical postoperative infections: A retrospective analysis

Objective: To identify the factors that predispose neurosurgical patients to surgical site infections (SSI) as well as assess the risk factors attached to infection by a specific microorganism. Methodology: A retrospective case-control study was conducted at University College of Medical Sciences and G.T. B. Hospital, Delhi. Adult patients (>18 years) undergoing a neurosurgical procedure with a diagnosis of SSI in the year 2021 having a minimum follow up of 30 days postoperatively or until death if they survived less than 30 days were included. Statistical analysis was performed using the SPSS 16 software with level of significance at 0.05.Results: An incidence of 3.15% was observed at our center. Mean age of the study population was 39.2 & PLUSMN; 13.07 years (range 22-70 years) with a male: female ratio of 3:1. Having an underlying infection (p = 0.024), ASA score> 2 (p = 0.041), duration of surgery> 4 h (p = 0.025), diabetes (p = 0.027) and preoperative stay at the hospital (p = 0.036) were found to be statistically significant risk factors in the prediction of SSI in neurosurgical patients which were utilised to create a regression model with an accuracy of 70% and AUC of 0.833. Deep infections were found to have a significant association with positive culture on the collected samples (p = 0.035).Conclusions: This study is a starting point to identify which factors could predict the presence of a particular organism isolated from the site of infection in neurosurgical patients, thereby minimizing AMR.

Automated summary

This study aimed to identify the risk factors for surgical site infections (SSI) in neurosurgical patients and assess the factors associated with infection by a specific microorganism. A retrospective case-control study was conducted, and the results showed that underlying infection, ASA score>2, duration of surgery>4 h, diabetes, and preoperative stay at the hospital were significant risk factors for SSI in neurosurgical patients. By creating a regression model, the presence of a particular organism isolated from the site of infection in neurosurgical patients can be predicted.