Predicting Which Species of Bacteria Will Cause an Infection After Fracture Surgery.

The aim of this study was to develop and validate risk prediction models for deep surgical site infection (SSI) caused by specific bacterial pathogens after fracture fixation. A retrospective case-control study was conducted at a level I trauma center. Fifteen candidate predictors of the bacterial pathogens in deep SSI were evaluated to develop models of bacterial risk. The study included 441 patients with orthopedic trauma with deep SSI after fracture fixation and 576 control patients. The main outcome measurement was deep SSI cultures positive for methicillin-sensitive (MSSA), methicillin-resistant (MRSA), gram-negative rods (GNRs), anaerobes, or polymicrobial infection within 1 year of injury. Prognostic models were developed for five bacterial pathogen outcomes. Mean area under the curve ranged from 0.70 (GNRs) to 0.74 (polymicrobial). Strong predictors of MRSA were American Society of Anesthesiologists (ASA) classification of III or greater (odds ratio [OR], 3.4; 95% CI, 1.6-8.0) and time to fixation greater than 7 days (OR, 3.4; 95% CI, 1.9-5.9). Gustilo type III fracture was the strongest predictor of MSSA (OR, 2.5; 95% CI, 1.6-3.9) and GNRs (OR, 3.4; 95% CI, 2.3-5.0). ASA classification of III or greater was the strongest predictor of polymicrobial infection (OR, 5.9; 95% CI, 2.7-15.5) and was associated with increased odds of GNRs (OR, 2.7; 95% CI, 1.5-5.5). Our models predict the risk of MRSA, MSSA, GNR, anaerobe, and polymicrobial infections in patients with fractures. The models might allow for modification of preoperative antibiotic selection based on the particular pathogen posing greatest risk for this patient population. [. 2024;47(1):e19-e25.].