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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 Staphylococcus aureus (MSSA), methicillin-resistant S aureus (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. [ Orthopedics . 2024;47(1):e19-e25.].

Background: Recently social media use within healthcare has increased significantly. Today, it is common for patients to browse the Internet, including physicians' social media pages, to learn about their medical conditions and search for providers. The purpose of this study is to analyze the use of social media among hand surgeons, and to compare this use between academic and private surgeons., Methods: Using the American Society for Surgery of the Hand's (ASSH) online directory, all active members practicing within the ten most populated U.S. cities were identified. Social media presence was determined by an Internet search of platforms. Members were stratified by practice model (academic vs. private). Chi-square and t-tests were used to compare categorical and continuous variables, and a multivariable logistic regression was performed for the binary variable practice model., Results: Two hundred and fifty-six hand surgeons were identified with 150 (59%) in academic and 106 (41%) in private practice. For ResearchGate accounts, 51 (82%) were academic and 11 (18%) were private. Mean PubMed publications was 38 for academic and 9 for private. YouTube presence was 69 (70%) in academic and 29 (30%) in private. On multivariable analysis, the odds of having ResearchGate and YouTube presence were higher for academic practice. There was no statistically significant difference by practice type for Facebook, Twitter, LinkedIn, and Instagram., Conclusions: With the recent social media expansion, surgeons have adopted social media platforms to reach patients. While the literature has shown that private practices are more active in social media, our results show they are not more active than academic practices in the ten most populated U.S. cities., Level of Evidence: IV., Competing Interests: The authors have no conflict of interests to disclose

Objective: To quantify patient preferences towards time to return to driving relative to compromised reaction time and potential complication risks., Design: Cross-sectional discrete choice experiment., Setting: Academic trauma center., Patients: Ninety-six adult patients with an operative lower extremity fracture from December 2019 through December 2020., Intervention: None., Main Outcome Measurement: Patient completed a discrete choice experiment survey consisting of 12 hypothetical return to driving scenarios with varied attributes: time to return to driving (range: 1 to 6 months), risk of implant failure (range: 1% to 12%), pain upon driving return (range: none to severe), and driving safety measured by braking distance (range: 0 to 40 feet at 60 mph). The relative importance of each attribute is reported on a scale of 0% to 100%., Results: Patients most valued a reduced pain level when resuming driving (62%), followed by the risk of implant failure (17%), time to return to driving (13%), and braking safety (8%). Patients were indifferent to returning to driving at 1 month (median utility: 28, interquartile range [IQR] -31 to 80) or 2 months (median utility: 59, IQR: 41 to 91) postinjury., Conclusion: Patients with lower extremity injuries demonstrated a willingness to forego earlier return to driving if it might mean a decrease in their pain level. Patients are least concerned about their driving safety, instead placing higher value on their own pain level and chance of implant failure. The findings of this study are the first to rigorously quantify patient preferences toward a return to driving and heterogeneity in patient preferences., Level of Evidence: V., Competing Interests: The remaining authors have no conflicts of interest to disclose., (Copyright © 2022 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Orthopaedic Trauma Association.)