A Predictive Score for Determining Risk of Surgical Site Infection After Orthopaedic Trauma Surgery. Issue 10 (October 2019)

• Record Type: Journal Article
• Authors: Wise, Brent T.; Connelly, Daniel; Rocca, Michael; Mascarenhas, Daniel; Huang, Yanjie; Maceroli, Michael A.; Gage, Mark J.; Joshi, Manjari; Castillo, Renan C.; O'Toole, Robert V.
• Is Part Of: Journal of orthopaedic trauma. Volume 33:Issue 10(2019)
• Publication Date: 2019-10
• Subjects: postoperative infection -- risk score -- fracture fixation; Orthopedics -- Periodicals; Wounds and injuries -- Periodicals; Orthopedics -- Periodicals; Wounds and Injuries -- therapy -- Periodicals; Periodicals; 617.47044
• DOI: 10.1097/BOT.0000000000001513
• Languages: English
• ISSNs: 0890-5339

Abstract

Abstract : Objectives: To determine factors predictive of postoperative surgical site infection (SSI) after fracture fixation and create a prediction score for risk of infection at time of initial treatment. Design: Retrospective cohort study. Setting: Level I trauma center. Patients/Participants: Study group, 311 patients with deep SSI; control group, 608 patients. Intervention: We evaluated 27 factors theorized to be associated with postoperative infection. Bivariate and multiple logistic regression analyses were used to build a prediction model. A composite score reflecting risk of SSI was then created. Main Outcome Measures: Risk of postoperative infection. Results: The final model consisted of 8 independent predictors: (1) male sex, (2) obesity (body mass index ≥ 30) (3) diabetes, (4) alcohol abuse, (5) fracture region, (6) Gustilo–Anderson type III open fracture, (7) methicillin-resistant Staphylococcus aureus nasal swab testing (not tested or positive result), and (8) American Society of Anesthesiologists classification. Risk strata were well correlated with observed proportion of SSI and resulted in a percent risk of infection of 1% for ⩽3 points, 6% for 4–5 points, 11% for 6 to 8–9 points, and 41% for ≥10 points. Conclusion: The proposed postoperative infection prediction model might be able to determine which patients have fractures at higher risk of infection and provides an estimate of the percent risk of infection before fixation. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence. Abstract : Supplemental Digital Content is Available in the Text.