Predicting deep infection in pilon and tibial plateau fractures: a secondary analysis of the VANCO and OXYGEN trials.

Autor:	Overmann AL; R Adams Cowley Shock Trauma Center, Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD.; Department of Orthopaedics, Eisenhower Army Medical Center, Fort Eisenhower, GA., Carlini AR; Department of Health Policy and Management, Center for Health Services and Outcomes Research and Johns Hopkins Center for Injury and Research Policy, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD., O'Toole RV; R Adams Cowley Shock Trauma Center, Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD., Castillo RC; Department of Health Policy and Management, Center for Health Services and Outcomes Research and Johns Hopkins Center for Injury and Research Policy, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD., O'Hara NN; R Adams Cowley Shock Trauma Center, Department of Orthopaedics, University of Maryland School of Medicine, Baltimore, MD.
Jazyk:	angličtina
Zdroj:	OTA international : the open access journal of orthopaedic trauma [OTA Int] 2024 Nov 25; Vol. 7 (4), pp. e348. Date of Electronic Publication: 2024 Nov 25 (Print Publication: 2024).
DOI:	10.1097/OI9.0000000000000348
Abstrakt:	Objectives: To develop and validate a prediction model for a deep surgical site infection (SSI) after fixation of a tibial plateau or pilon fracture. Design: Pooled data from 2 randomized trials (VANCO and OXYGEN). Setting: Fifty-two US trauma centers. Patients: In total, 1847 adult patients with operatively treated tibial plateau or pilon fractures who met criteria for a high risk of infection. Intervention: We considered 13 baseline patient characteristics and developed and externally validated prediction models using 3 approaches (logistic regression, stepwise elimination, and machine learning). Main Outcomes and Measures: The primary prediction model outcome was a deep SSI requiring operative debridement within 182 days of definitive fixation. Our primary prognostic performance metric for evaluating the models was area under the receiver operating characteristic curve (AUC) with clinical utility set at 0.7. Results: Deep SSI occurred in 75 VANCO patients (8%) and in 56 OXYGEN patients (6%). The machine learning model for VANCO (AUC = 0.65) and stepwise elimination model for OXYGEN (AUC = 0.62) had the highest internal validation AUCs. However, none of the external validation AUCs exceeded 0.64 (range, 0.58 to 0.64). Conclusions: The predictive models did not reach the prespecified clinical utility threshold. Our models' inability to distinguish high-risk from low-risk patients is likely due to strict eligibility criteria and, therefore, homogeneous patient populations. Competing Interests: N. N. O'Hara receives stock options from Arbutus Medical, Inc. unrelated to this research. R.V. O'Toole is a paid consultant for Stryker, receives stock options from Imagen, and receives royalties from Lincotek, all unrelated to this research. Paul Tornetta III, MD reports intellectual property with Smith & Nephew. The remaining authors report no conflict of interest. (Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu