Volume 124, Issue 7

The emergence of generative large language model (LLM) artificial intelligence (AI) represents one of the most profound developments in healthcare in decades, with the potential to create revolutionary and seismic changes in the practice of medicine as we know it. However, significant concerns have arisen over questions of liability for bad outcomes associated with LLM AI-influenced medical decision making. Although the authors were not able to identify a case in the United States that has been adjudicated on medical malpractice in the context of LLM AI at this time, sufficient precedent exists to interpret how analogous situations might be applied to these cases when they inevitably come to trial in the future. This commentary will discuss areas of potential legal vulnerability for clinicians utilizing LLM AI through review of past case law pertaining to third-party medical guidance and review the patchwork of current regulations relating to medical malpractice liability in AI. Finally, we will propose proactive policy recommendations including creating an enforcement duty at the US Food and Drug Administration (FDA) to require algorithmic transparency, recommend reliance on peer-reviewed data and rigorous validation testing when LLMs are utilized in clinical settings, and encourage tort reform to share liability between physicians and LLM developers.

Context The landscape of medical education in the United States has undergone significant changes, particularly with the rise of osteopathic medical students, constituting a substantial portion of medical school entrants. The merger of the Accreditation Council for Graduate Medical Education (ACGME) and the American Osteopathic Association (AOA) in 2020 opened residency slots to allopathic graduates that were previously historically allocated to osteopathic (Doctor of Osteopathic Medicine [DO]) physicians. This has impacted various medical specialties, notably orthopedic surgery. Despite an increase in orthopedic surgery applicants, the match rates for DO candidates have faced challenges, raising concerns about the impact of this merger on the future of orthopedic training for DO students. Objectives This research aims to analyze the trends in orthopedic surgery match rates for DO vs MD applicants since the single accreditation merger, which began in 2015 with a 5-year transition period that was finalized by 2020. By examining factors such as application numbers, research output, standardized test scores, and program director preferences, the study seeks to identify disparities and challenges faced by DO applicants in securing orthopedic surgery residencies. Methods This study utilized publicly available data from the National Residency Match Program (NRMP) 2018, 2020, and 2022 reports. Data encompassed applicant characteristics, including standardized test scores, research experiences, and match outcomes. The study also incorporated insights from NRMP program director surveys, focusing on interview and ranking practices. The analysis involved comparisons of application numbers, match rates, research productivity, and test scores between DO and MD applicants. Statistical analysis was employed to identify any statistically significant differences among the examined variables for the 3 years included in the study. Results The research revealed a consistent increase in orthopedic surgery applicants from both DO and MD backgrounds. However, MD applicants consistently had higher match rates compared to their DO counterparts, with the gap narrowing over the years. Notably, disparities persisted in research output, with MD applicants demonstrating a significant advantage in publications and presentations. Standardized test scores, although slightly higher for MD applicants, did not significantly impact the differences in match rates. MD applicants had statistically significantly higher numbers of applicants ( P = .0010), number of publications ( P = .0091), and number of research experiences ( P = .0216) over the years examined. However, there was no statistically significant difference in the scores on Step 1 ( P = .5038) or Step 2 ( P = .4714) between MD and DO candidates. Conclusions Despite progress in the acceptance and ranking of DO applicants by program directors, the study highlights enduring challenges in orthopedic surgery match rates between DO and MD candidates. The lack of research opportunities for DO students stands out as a crucial area for improvement, necessitating systemic changes within medical education. Addressing this disparity and ensuring equal access to research experiences could mitigate the gap in match rates, promoting a more equitable environment for all aspiring orthopedic surgeons, regardless of their medical background. Such efforts are vital to fostering inclusivity and enhancing opportunities for osteopathic medical students pursuing competitive specialties like orthopedic surgery.

Context It is unknown if US residency applicants of different educational backgrounds (US allopathic [MD], Doctor of Osteopathic Medicine [DO], and international medical graduates [IMG]) but comparable academic performance have similar match success. Objectives Our objective was to compare match probabilities between applicant types after adjusting for specialty choice and United States Medical Licensing Examination (USMLE) Step 1 scores. Methods We performed a secondary analysis of published data in National Resident Matching Program (NRMP) reports from 2016, 2018, 2020, and 2022 for US MD seniors, DO seniors, and IMGs (US citizens and non-US citizens). We examined the 10 specialties with the most available spots in 2022. Average marginal effects from a multiple variable logistic regression model were utilized to estimate each non-MD senior applicant type’s probability of matching into their preferred specialty compared to MD seniors adjusting for specialty choice, Step 1 score, and match year. Results Each non-MD applicant type had a lower adjusted percent difference in matching to their preferred specialty than MD seniors, −7.1 % (95 % confidence interval [CI], −11.3 to −2.9) for DO seniors, −45.6 % (−50.6 to −40.5) for US IMGs, and −56.6 % (−61.5 to −51.6) for non-US IMGs. Similarly, each non-MD applicant type had a lower adjusted percent difference in matching than MD seniors across almost all Step 1 score ranges, except for DO seniors with Step 1 scores <200 (−2.0 % [−9.5 to 5.5]). Conclusions After adjusting for specialty choice, Step 1 score, and match year, non-US MD applicants had lower probabilities of matching into their preferred specialties than their US MD colleagues.

Context Stigmatizing language or non-person-centered language (non-PCL) has been shown to impact patients negatively, especially in the case of obesity. This has led many associations, such as the American Medical Association (AMA) and the International Committee of Medical Journal Editors (ICMJE), to enact guidelines prohibiting the use of stigmatizing language in medical research. In 2018, the AMA adopted person-centered language (PCL) guidelines, including a specific obesity amendment to which all researchers should adhere. However, little research has been conducted to determine if these guidelines are being followed. Objectives Our primary objective was to determine if PCL guidelines specific to obesity have been properly followed in the sports medicine journals that are interacted with most frequently. Methods We searched within PubMed for obesity-related articles between 2019 and 2022 published in the top 10 most-interacted sports medicine journals based on Google Metrics data. A predetermined list of stigmatizing and non-PCL terms/language was searched within each article. Results A total of 198 articles were sampled, of which 58.6 % were found to be not compliant with PCL guidelines. The most common non-PCL terms were “obese” utilized in 49.5 % of articles, followed by “overweight” as the next most common stigmatizing term at 40.4 %. Stigmatizing labels such as “heavy, heavier, heaviness,” “fat” as an adjective, and “morbid” appeared in articles but at a lower rate. Conclusions Our study shows that there is a severe lack of adherence to PCL guidelines in the most-interacted sports medicine journals. Negative associations between stigmatizing language and individuals with obesity will only persist if a greater effort is not made to change this. All journals, including the most prestigious ones, should adopt and execute PCL guidelines to prevent the spread of demeaning language in the medical community.

Context Chronic low back pain (CLBP) has long plagued mankind, but little progress has been made in finding a rational and effective treatment, let alone a common cause. This study is an attempt to fill that void by measuring short- and long-term effects of osteopathic manipulative treatment (OMT), including psychosocial and pain reduction in CLBP patients. Objectives The objectives of this study were to investigate the effectiveness of neuromusculoskeletal medicine/osteopathic manipulative medicine (OMM) in treating CLBP, with a focus on biopsychosocial (pain sensitivity questionnaire [PSQ]) and pain control in chronic conditions. Methods The study involved a large, single cohort observational design of 101 patients. The inclusion criteria for selecting patients targeted those with “nonspecific” CLBP. The National Institutes of Health (NIH) Minimum Dataset for Chronic Low Back Pain (NMD) was the measurement tool and was administered at consent (baseline), 2, 4, and 8 weeks and at 6 and 12 months. Time trends were analyzed as overall mean. Pairwise differences were compared between time points. Mixed-effects models were utilized to test the association of time with pain and biopsychosocial scores. Results Pain and PSQ scores decreased over the study timeline. The most significant change for both pain and biopsychosocial scores occurred at 6 months compared to baseline, with a further reduction at 12 months. Conclusions OMT has been demonstrated to significantly reduce pain and psychosocial factors related to CLBP in both the short and long term.

Context Interoceptive bodily awareness (IBA) is one's attentional focus on and relationship with comfortable and uncomfortable (e.g., pain) internal body sensations. Integrating IBA into research on osteopathic manipulative treatment (OMT) is growing, both as an outcome and predictor of treatment outcomes; however, it has yet to be studied in a clinical setting. Objectives We aimed to conduct a pilot study to measure IBA, with the Multidimensional Assessment of Interoceptive Awareness (MAIA), in patients seeking OMT for pain, and to test if OMT exposure may be associated with higher IBA as measured by the MAIA. The primary outcome was the change in MAIA scores, and the secondary outcomes were reduction in pain intensity, reduction in pain interference, and increase in participants’ perception of change post-OMT. Methods A convenience sample was recruited from individuals presenting for OMT appointments at a College of Osteopathic Medicine OMT teaching clinic. Participants were recruited into our single-arm observational cohort study (n=36), and categorized into one of two groups, OMT-naïve (n=19) or OMT-experienced (n=17), based on prior exposure to OMT. We measured MAIA scores and clinical pain-related outcomes prior to, immediately after, and at 1 and 3 weeks after a usual-care OMT session in the clinic. Covariates including experience with mind–body activities, non-OMT body work, and physical and emotional trauma were also collected to explore potential relationships. We utilized t tests to compare MAIA scores and pain outcomes between groups and across time points. Stepwise regression models were utilized to explore potential relationships with covariates. Results The OMT-experienced group scored higher on the MAIA scales “Not-worrying” (p=0.002) and “Trusting” (p=0.028) at baseline. There were no significant changes in the MAIA scores before and after the single OMT session. Analysis of secondary outcomes revealed that all pain outcomes significantly decreased post-OMT (p<0.05), with the largest relative improvements in the acute pain and OMT-naïve subgroups, with diminishing effects over time. Conclusions Assessing IBA with MAIA in a clinical OMT setting is feasible. There were significant positive correlations between OMT exposure and two of the eight MAIA scales. Future studies are justified to further explore this relationship.