➢ Natural language processing with large language models is a subdivision of artificial intelligence (AI) that extracts meaning from text with use of linguistic rules, statistics, and machine learning to generate appropriate text responses. Its utilization in medicine and in the field of orthopaedic surgery is rapidly growing. ➢ Large language models can be utilized in generating scientific manuscript texts of a publishable quality; however, they suffer from AI hallucinations, in which untruths or half-truths are stated with misleading confidence. Their use raises considerable concerns regarding the potential for research misconduct and for hallucinations to insert misinformation into the clinical literature. ➢ Current editorial processes are insufficient for identifying the involvement of large language models in manuscripts. Academic publishing must adapt to encourage safe use of these tools by establishing clear guidelines for their use, which should be adopted across the orthopaedic literature, and by implementing additional steps in the editorial screening process to identify the use of these tools in submitted manuscripts.

Background: Little is known about the effect of orthopaedic trauma on the financial health of patients. We hypothesized that some patients who sustain musculoskeletal trauma experience considerable financial hardship during treatment, and we also assessed for factors associated with increased personal financial burden. Methods: We surveyed 236 of 393 consecutive patients who were approached at 1 of 2 American College of Surgeons level-I trauma centers between 2016 and 2017 following the completion of treatment for a musculoskeletal injury (60% response rate). Two validated measures (financial burden composite score and dichotomized worry score) were used to assess the financial hardship that patients experienced with the injury. Results: There were 236 participants in the study, the mean age was 56.3 years (range, 19 to 94 years), and 48.7% of patients were male. Of the 236 patients, 97.9% had medical insurance, yet the mean financial burden composite score (and standard deviation) was 2.4 ± 2.2 (0 indicated low and 6 indicated high). In this study, 25.0% of patients had high levels of worry about financial problems that resulted from the injury. Fifty-four percent of patients used their savings to pay for their care, and 23% of patients borrowed money or took out a loan. Twenty-three percent of patients missed payment on other bills. Fifty-seven percent of patients were required to cut expenses in general. Patients with higher composite financial burden scores had a significantly increased likelihood of high financial worry (odds ratio [OR], 1.8 [95% confidence interval (CI), 1.5 to 2.2]; p < 0.001). Factors associated with increased financial hardship were high-deductible health plan insurance (coefficient, 0.3 [95% CI, 0.002 to 0.528]; p = 0.048), Medicaid insurance (coefficient, 0.6 [95% CI, 0.342 to 0.863]; p < 0.001), failure to complete high school (coefficient, 0.475 [95% CI, 0.033 to 0.918]; p = 0.035), increased number of surgical procedures (coefficient, 0.067 [95% CI, 0.005 to 0.129]; p = 0.035), and prior medical or student loans (coefficient, 0.769 [95% CI, 0.523 to 1.016]; p < 0.001). Conclusions: Despite a high rate of insurance, patients with orthopaedic trauma in our study had high rates of worry and financial distress. Asking about financial hardship may help to identify those patients with a higher personal financial burden and may promote allocation of additional social support and services.

Objectives: To evaluate the incidence of nonunion and wound complications following open, complete articular pilon fractures. Second, to study the effect that both timing of fixation and timing of flap coverage have on deep infection rates. Design: Retrospective case series Setting: Three Academic Level One Trauma Centers. Patients: 161 patients with open AO/OTA type 43C distal tibia fractures treated with open reduction internal fixation (ORIF) between 2002-2018. Mean (SD) age of 46 (14) years, 70% male, with median (IQR) follow up of 2.1 (1.3-5.0) years (minimum 1 year). There were 133 (83%) type 3A and 28 (17%) type 3B open fractures. Intervention: Fracture fixation: Acute, primary (24 hours). Soft tissue coverage: rotational or free flap. Main Outcome Measurement: Primary outcomes included deep infection and nonunion. Secondary outcomes included rates of soft tissue coverage and reoperation. Results: Acute fixation (<24 hours) was performed in 36 (22%) patients; 125 (78%) underwent delayed, staged fixation. Deep infection occurred in 27% patients and was associated with males (33% vs. 16%, p=0.029), smoking (38% vs. 23%, p=0.047), type 3B fractures (39% vs. 25%, p=0.046). Acute fixation of type 3A fractures demonstrated higher rate of infection (38% vs. 20% p=0.036) than delayed, staged fixation. In type 3B fractures, early flap coverage (< 1 week) demonstrated lower rate of infection (18% vs. 53%, p=0.066) and 20% (vs. 43%) with a single-staged “fix and flap” procedure (p=0.408). Nonunion occurred in 36 (22%) and was associated with deep infection (43% vs. 15%, p<0.001). Fifteen (42%) were septic nonunions. Twenty-nine of the 36 (81%) nonunions achieved radiographic union after median (IQR) 27 (20-41) weeks and median (range) 1 (1-3) revision ORIF procedures. There was no difference in rate of secondary union between septic and aseptic nonunions (85% vs 86%, p=1.00). There was a high rate of secondary procedures (47%): revision ORIF (17%), I&D, (15%), and removal hardware (11%). Conclusions: Complete articular, open pilon fractures are associated with high rate of complications following ORIF. Early fixation carries a high risk of deep infection, however early flap coverage for 3B fractures appears to play a protective role. We advocate for aggressive management including urgent surgical debridement and very early soft tissue cover combined with definitive fixation during single procedure if possible. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.