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OBJECTIVE: The National Football League (NFL) has seen increasing scrutiny regarding its management of concussions, especially following an on-field incident involving the Miami Dolphins' quarterback Tua Tagovailoa in the 2022 season. We hope to elucidate the recent trends in the diagnosis and management of concussions during the course of 5 NFL seasons from 2019 to 2023. METHODS: We queried the NFL injury reports from the 2019 through 2023 database recording players listed with concussions. The weeks missed were calculated using the NFL game logs. Players' concussions that did not occur in the games, those complicated by other injuries, and those affected by roster status were excluded. RESULTS: Searches of the NFL injury reports resulted in the identification of 664 of 692 concussions (96%) that occurred in regular season games across the 2019-2023 seasons. During the course of these 5 seasons, 31% of the players returned without missing a game, 39% of the players missed 1 game, and 30% of the players missed ≥2 games. No significant difference in the number of concussions per game or weeks missed was observed across the seasons observed. Players with concussions on teams that made the playoffs saw fewer weeks missed than those on non-playoff teams (0.86 vs. 1.37; P = 0.002). CONCLUSIONS: Since the start of the 2021 NFL season, an increasing incidence of concussions has been noted; however, there was no change observed in the number of weeks missed after the concussions. Trends in the rates of concussions across the seasons remain largely stable, despite increased scrutiny over concussions in the sport.
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Introduction The efficacy of integrating artificial intelligence (AI) models like ChatGPT into the medical field, specifically orthopedic surgery, has yet to be fully determined. The most recent adaptation of ChatGPT that has yet to be explored is its image analysis capabilities. This study assesses ChatGPT's performance in answering Orthopedic In-Training Examination (OITE) questions, including those that require image analysis. Methods Questions from the 2014, 2015, 2021, and 2022 AAOS OITE were screened for inclusion. All questions without images were entered into ChatGPT 3.5 and 4.0 twice. Questions that necessitated the use of images were only entered into ChatGPT 4.0 twice, as this is the only version of the system that can analyze images. The responses were recorded and compared to AAOS's correct answers, evaluating the AI's accuracy and precision. Results A total of 940 questions were included in the final analysis (457 questions with images and 483 questions without images). ChatGPT 4.0 performed significantly better on questions that did not require image analysis (67.81% vs 47.59%, p<0.001). Discussion While the use of AI in orthopedics is an intriguing possibility, this evaluation demonstrates how, even with the addition of image processing capabilities, ChatGPT still falls short in terms of its accuracy. As AI technology evolves, ongoing research is vital to harness AI's potential effectively, ensuring it complements rather than attempts to replace the nuanced skills of orthopedic surgeons.