Mateo Restrepo Mejia

Glucagon-like peptide-1 (GLP-1) receptor agonists, commonly used for glycemic control in patients with type 2 diabetes and for weight loss in obese patients, have been increasingly used due to their effectiveness in treating these conditions and in reducing cardiovascular events. Yet evidence is limited surrounding their impact on bone health and on patients undergoing orthopedic procedures. This narrative review explores the mechanisms of action of GLP-1 agonists, their effects on bone health, and the implications of their use in perioperative patents undergoing orthopedic surgery, with an emphasis on spine surgery. Basic science studies suggest that GLP-1 agonists may enhance bone mineral density and reduce bone resorption through various molecular pathways; clinical studies of their impact on fracture risk and bone health show mixed results. Also, the perioperative use of GLP-1 agonists poses challenges due to their effects on gastric motility and potential medication interactions. Nonetheless, achieving proper glycemic control with GLP-1 agonists may benefit patients with diabetes or obesity undergoing orthopedic procedures, particularly in preoperative weight management and glycemic control. Further research is needed to clarify their long-term effects on bone health and their perioperative use in orthopedic patients.

Study Design: Systematic Review of Randomized Controlled Trials. Objectives: To assess the statistical fragility of randomized controlled trials (RCTs) comparing lumbar fusion and lumbar disc arthroplasty (LDA). Methods: Following PRISMA guidelines, PubMed, Embase, and Medline databases were searched for RCTs on lumbar fusion and LDA published between January 1, 2000 and August 1, 2023. Eligible studies reported dichotomous, categorical outcomes. A two-tailed Fisher’s exact test was used to confirm reported P -values (α = 0.05) for each outcome. Results: 18 RCTs met the inclusion criteria for analysis. Across the 18 studies, 146 dichotomous outcomes were identified. The median fragility index (FI) for all outcomes was 5 (IQR: 2.0-9.0), while the median fragility quotient (FQ) was 0.022 (IQR: 0.008-0.046). Subgroup analysis revealed that adjacent segment disease outcomes had a median FI of 3 (IQR: 2.75-3) and an FQ of 0.013 (IQR: 0.013-0.014). Industry-funded studies had a significantly higher FI (6 vs 4, P = 0.036) and lower FQ (0.019 vs 0.040, P = 0.023) compared to non-industry-funded studies. Conclusions: This systematic review demonstrates that the statistically significant findings from RCTs comparing LF to LDA are susceptible to small changes in event outcomes. Of note, industry-funded studies were found to be significantly more statistically fragile compared to non-industry-funded studies.

Introduction: Recently, the role of a patient's primary spoken language (PSL) has emerged as a potential contributor to perioperative outcomes. This study aimed to identify the association between a patient's PSL and hip fracture perioperative outcomes, including hospital length of stay (LOS), in-hospital mortality, nonhome discharge, 30-day emergency department visits, 90-day readmissions, and 90-day complications. Methods: An institutional review board–approved retrospective cohort study was performed using institutional data. Two cohorts were created for patients who underwent either open reduction and internal fixation (ORIF) or arthroplasty (total or hemiarthroplasty) for a hip fracture in 2016 to 2023 in a multihospital academic health system. Within each cohort, patients with non-English and English PSL were matched 1:3 based on age, sex, insurance, American Society of Anesthesiologists Classification, dementia, and obesity. Generalized linear models measured associations between PSL and outcomes, adjusting for Charlson Comorbidity Index; adjusted odds ratios are reported for binary outcomes and adjusted mean differences are reported for continuous outcomes. Results: The matched cohorts included 729 patients undergoing ORIF and 473 undergoing arthroplasty. In multivariable analyses in the ORIF cohort, non-English PSL (versus English) was associated with a markedly longer LOS by an average of 0.95 days (95% confidence interval [CI], 0.28 to 1.62, P = 0.01) and decreased likelihood of discharge to a nonhome setting (odds ratio = 0.62, 95% confidence interval, 0.39 to 0.98, P = 0.04). For arthroplasty, non-English PSL (versus English) was markedly associated with shorter LOS by an average of 1.04 days (95% CI, −1.99 to −0.09, P = 0.03). No notable associations were identified between PSL and the other outcomes. Conclusion: These findings suggest language-based differences in perioperative outcomes for surgical management of hip fracture. Further research is needed to identify the mechanisms of these associations and evaluate the clinical significance on long-term outcomes.

Study Design: An experimental study.Purpose: To explore the concordance of ChatGPT responses with established national guidelines for the management of cervical spine and spinal cord injuries.Overview of Literature: ChatGPT-4.0 is an artificial intelligence model that can synthesize large volumes of data and may provide surgeons with recommendations for the management of spinal cord injuries. However, no available literature has quantified ChatGPT’s capacity to provide accurate recommendations for the management of cervical spine and spinal cord injuries.Methods: Referencing the “Management of acute cervical spine and spinal cord injuries” guidelines published by the Congress of Neurological Surgeons (CNS), a total of 36 questions were formulated. Questions were stratified into therapeutic, diagnostic, or clinical assessment categories as seen in the guidelines. Questions were secondarily grouped according to whether the corresponding recommendation contained level I evidence (highest quality) versus only level II/III evidence (moderate and low quality). ChatGPT-4.0 was prompted with each question, and its responses were assessed by two independent reviewers as “concordant” or “nonconcordant” with the CNS clinical guidelines. “Nonconcordant” responses were rationalized into “insufficient” and “contradictory” categories.Results: In this study, 22/36 (61.1%) of ChatGPT’s responses were concordant with the CNS guidelines. ChatGPT’s responses aligned with 17/24 (70.8%) therapeutic questions and 4/7 (57.1%) diagnostic questions. ChatGPT’s response aligned with only one of the five clinical assessment questions. Notably, the recommendations supported by level I evidence were the least likely to be replicated by ChatGPT. ChatGPT’s responses agreed with 80.8% of the recommendations supported exclusively by level II/III evidence.Conclusions: ChatGPT-4 was moderately accurate when generating recommendations that aligned with the clinical guidelines. The model frequently aligned with low evidence and therapeutic recommendations but exhibited inferior performance on topics that contained high-quality evidence or pertained to diagnostic and clinical assessment strategies. Medical practitioners should monitor its usage until further models can be rigorously trained on medical data.

Background: Acute hip fractures are a public health problem affecting primarily older adults. Chat Generative Pretrained Transformer may be useful in providing appropriate clinical recommendations for beneficial treatment. Objective: To evaluate the accuracy of Chat Generative Pretrained Transformer (ChatGPT)-4.0 by comparing its appropriateness scores for acute hip fractures with the American Academy of Orthopaedic Surgeons (AAOS) Appropriate Use Criteria given 30 patient scenarios. “Appropriateness” indicates the unexpected health benefits of treatment exceed the expected negative consequences by a wide margin. Methods: Using the AAOS Appropriate Use Criteria as the benchmark, numerical scores from 1 to 9 assessed appropriateness. For each patient scenario, ChatGPT-4.0 was asked to assign an appropriate score for six treatments to manage acute hip fractures. Results: Thirty patient scenarios were evaluated for 180 paired scores. Comparing ChatGPT-4.0 with AAOS scores, there was a positive correlation for multiple cannulated screw fixation, total hip arthroplasty, hemiarthroplasty, and long cephalomedullary nails. Statistically significant differences were observed only between scores for long cephalomedullary nails. Conclusion: ChatGPT-4.0 scores were not concordant with AAOS scores, overestimating the appropriateness of total hip arthroplasty, hemiarthroplasty, and long cephalomedullary nails, and underestimating the other three. ChatGPT-4.0 was inadequate in selecting an appropriate treatment deemed acceptable, most reasonable, and most likely to improve patient outcomes.

Background: Approximately 25 million people in the United States have limited English proficiency. Current developments in orthopaedic surgery, such as the expansion of preoperative education classes or patient-reported outcome collection in response to bundled payment models, may exacerbate language-related barriers. Currently, there are mixed findings of the associations between limited English proficiency and care processes and outcomes, warranting a cross-study synthesis to identify patterns of associations. Questions/purposes: In this systematic review, we asked: Is limited English proficiency associated with (1) differences in clinical care processes, (2) differences in care processes related to patient engagement, and (3) poorer treatment outcomes in patients undergoing orthopaedic surgery in English-speaking countries? Methods: On June 9, 2023, a systematic search of four databases from inception through the search date (PubMed, Ovid Embase, Web of Science, and Scopus) was performed by a medical librarian. Potentially eligible articles were observational studies that examined the association between limited English proficiency and the prespecified categories of outcomes among pediatric and adult patients undergoing orthopaedic surgery or receiving care in an orthopaedic surgery setting. We identified 10,563 records, of which we screened 6966 titles and abstracts after removing duplicates. We reviewed 56 full-text articles and included 29 peer-reviewed studies (outcome categories: eight for clinical care processes, 10 for care processes related to patient engagement, and 15 for treatment outcomes), with a total of 362,746 patients or encounters. We extracted data elements including study characteristics, definition of language exposure, specific outcomes, and study results. The quality of each study was evaluated using adapted Newcastle-Ottawa scales for cohort or cross-sectional studies. Most studies had a low (48%) or moderate (45%) risk of bias, but two cross-sectional studies had a high risk of bias. To answer our questions, we synthesized associations and no-difference findings, further stratified by adjusted versus unadjusted estimates, for each category of outcomes. No meta-analysis was performed. Results: There were mixed findings regarding whether limited English proficiency is associated with differences in clinical care processes, with the strongest adjusted associations between non-English versus English as the preferred language and delayed ACL reconstruction surgery and receipt of neuraxial versus general anesthesia for other non-Spanish versus English primary language in patients undergoing THA or TKA. Limited English proficiency was also associated with increased hospitalization costs for THA or TKA but not opioid prescribing in pediatric patients undergoing surgery for fractures. For care processes related to patient engagement, limited English proficiency was consistently associated with decreased patient portal use and decreased completion of patient-reported outcome measures per adjusted estimates. The exposure was also associated with decreased virtual visit completion for other non-Spanish versus English language and decreased postoperative opioid refill requests after TKA but not differences in attendance-related outcomes. For treatment outcomes, limited English proficiency was consistently associated with increased hospital length of stay and nonhome discharge per adjusted estimates, but not hospital returns. There were mixed findings regarding associations with increased complications and worse postoperative patient-reported outcome measure scores. Conclusion: Findings specifically suggest the need to remove language-based barriers for patients to engage in care, including for patient portal use and patient-reported outcome measure completion, and to identify mechanisms and solutions for increased postoperative healthcare use. However, interpretations are limited by the heterogeneity of study parameters, including the language exposure. Future research should include more-precise and transparent definitions of limited English proficiency and contextual details on available language-based resources to support quantitative syntheses. Level of Evidence: Level III, therapeutic study

Objective: Large language models like chat generative pre-trained transformer (ChatGPT) have found success in various sectors, but their application in the medical field remains limited. This study aimed to assess the feasibility of using ChatGPT to provide accurate medical information to patients, specifically evaluating how well ChatGPT versions 3.5 and 4 aligned with the 2012 North American Spine Society (NASS) guidelines for lumbar disk herniation with radiculopathy.Methods: ChatGPT's responses to questions based on the NASS guidelines were analyzed for accuracy. Three new categories—overconclusiveness, supplementary information, and incompleteness—were introduced to deepen the analysis. Overconclusiveness referred to recommendations not mentioned in the NASS guidelines, supplementary information denoted additional relevant details, and incompleteness indicated omitted crucial information from the NASS guidelines.Results: Out of 29 clinical guidelines evaluated, ChatGPT-3.5 demonstrated accuracy in 15 responses (52%), while ChatGPT-4 achieved accuracy in 17 responses (59%). ChatGPT-3.5 was overconclusive in 14 responses (48%), while ChatGPT-4 exhibited overconclusiveness in 13 responses (45%). Additionally, ChatGPT-3.5 provided supplementary information in 24 responses (83%), and ChatGPT-4 provided supplemental information in 27 responses (93%). In terms of incompleteness, ChatGPT-3.5 displayed this in 11 responses (38%), while ChatGPT-4 showed incompleteness in 8 responses (23%).Conclusion: ChatGPT shows promise for clinical decision-making, but both patients and healthcare providers should exercise caution to ensure safety and quality of care. While these results are encouraging, further research is necessary to validate the use of large language models in clinical settings.

Objective: Large language models, such as chat generative pre-trained transformer (ChatGPT), have great potential for streamlining medical processes and assisting physicians in clinical decision-making. This study aimed to assess the potential of ChatGPT’s 2 models (GPT-3.5 and GPT-4.0) to support clinical decision-making by comparing its responses for antibiotic prophylaxis in spine surgery to accepted clinical guidelines.Methods: ChatGPT models were prompted with questions from the North American Spine Society (NASS) Evidence-based Clinical Guidelines for Multidisciplinary Spine Care for Antibiotic Prophylaxis in Spine Surgery (2013). Its responses were then compared and assessed for accuracy.Results: Of the 16 NASS guideline questions concerning antibiotic prophylaxis, 10 responses (62.5%) were accurate in ChatGPT’s GPT-3.5 model and 13 (81%) were accurate in GPT-4.0. Twenty-five percent of GPT-3.5 answers were deemed as overly confident while 62.5% of GPT-4.0 answers directly used the NASS guideline as evidence for its response.Conclusion: ChatGPT demonstrated an impressive ability to accurately answer clinical questions. GPT-3.5 model’s performance was limited by its tendency to give overly confident responses and its inability to identify the most significant elements in its responses. GPT-4.0 model’s responses had higher accuracy and cited the NASS guideline as direct evidence many times. While GPT-4.0 is still far from perfect, it has shown an exceptional ability to extract the most relevant research available compared to GPT-3.5. Thus, while ChatGPT has shown far-reaching potential, scrutiny should still be exercised regarding its clinical use at this time.

Study Design: Comparative Analysis and Narrative Review. Objective: To assess and compare ChatGPT’s responses to the clinical questions and recommendations proposed by The 2011 North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Lumbar Spinal Stenosis (LSS). We explore the advantages and disadvantages of ChatGPT’s responses through an updated literature review on spinal stenosis. Methods: We prompted ChatGPT with questions from the NASS Evidence-based Clinical Guidelines for LSS and compared its generated responses with the recommendations provided by the guidelines. A review of the literature was performed via PubMed, OVID, and Cochrane on the diagnosis and treatment of lumbar spinal stenosis between January 2012 and April 2023. Results: 14 questions proposed by the NASS guidelines for LSS were uploaded into ChatGPT and directly compared to the responses offered by NASS. Three questions were on the definition and history of LSS, one on diagnostic tests, seven on non-surgical interventions and three on surgical interventions. The review process found 40 articles that were selected for inclusion that helped corroborate or contradict the responses that were generated by ChatGPT. Conclusions: ChatGPT’s responses were similar to findings in the current literature on LSS. These results demonstrate the potential for implementing ChatGPT into the spine surgeon’s workplace as a means of supporting the decision-making process for LSS diagnosis and treatment. However, our narrative summary only provides a limited literature review and additional research is needed to standardize our findings as means of validating ChatGPT’s use in the clinical space.