A Clinical Risk Model for Surgical Site Infection Following Pediatric Spine Deformity Surgery.

Area of Science:

• Orthopedics
• Pediatric Surgery
• Infectious Disease Epidemiology

Background:

• Surgical site infection (SSI) remains a significant concern in pediatric spinal deformity surgery.
• Previous studies had limitations in analyzing multiple risk factors simultaneously.
• This study aimed to identify and model key predictors of SSI in this patient population.

Purpose of the Study:

• To evaluate a wide range of preoperative and intraoperative factors for predicting SSI.
• To develop and validate a predictive model for individual SSI risk assessment.
• To create a practical tool for clinical use in pediatric spinal deformity surgery.

Main Methods:

• Analysis of 3,092 pediatric spinal deformity surgeries from seven institutions.
• Utilized logistic regression and cross-validation to develop and validate a predictive model.
• Included patient, surgical, and hospital factors, defining SSI as per CDC criteria within 90 days.

Main Results:

• Identified key predictors: nonambulatory status, neuromuscular etiology, pelvic instrumentation, long procedure time (≥7 hours), high ASA grade (>2), revision surgery, low hospital volume (<100 spine cases/year), abnormal hemoglobin, and BMI (overweight/obese).
• The final model demonstrated good discrimination (AUC 0.76) and calibration.
• Developed a risk probability calculator and mobile application.

Conclusions:

• The validated risk calculator accurately predicts 90-day SSI probability in pediatric spinal deformity surgery.
• The tool enhances informed consent and shared decision-making processes.
• Facilitates selective deployment of resources for high-risk individuals.