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BACKGROUND CONTEXT: Clinical guidelines, developed in concordance with the literature, are often used to guide surgeons' clinical decision making. Recent advancements of large language models and artificial intelligence (AI) in the medical field come with exciting potential. OpenAI's generative AI model, known as ChatGPT, can quickly synthesize information and generate responses grounded in medical literature, which may prove to be a useful tool in clinical decision-making for spine care. The current literature has yet to investigate the ability of ChatGPT to assist clinical decision making with regard to degenerative spondylolisthesis. PURPOSE: The study aimed to compare ChatGPT's concordance with the recommendations set forth by The North American Spine Society (NASS) Clinical Guideline for the Diagnosis and Treatment of Degenerative Spondylolisthesis and assess ChatGPT's accuracy within the context of the most recent literature. METHODS: ChatGPT-3.5 and 4.0 was prompted with questions from the NASS Clinical Guideline for the Diagnosis and Treatment of Degenerative Spondylolisthesis and graded its recommendations as "concordant" or "nonconcordant" relative to those put forth by NASS. A response was considered "concordant" when ChatGPT generated a recommendation that accurately reproduced all major points made in the NASS recommendation. Any responses with a grading of "nonconcordant" were further stratified into two subcategories: "Insufficient" or "Over-conclusive," to provide further insight into grading rationale. Responses between GPT-3.5 and 4.0 were compared using Chi-squared tests. RESULTS: ChatGPT-3.5 answered 13 of NASS's 28 total clinical questions in concordance with NASS's guidelines (46.4%). Categorical breakdown is as follows: Definitions and Natural History (1/1, 100%), Diagnosis and Imaging (1/4, 25%), Outcome Measures for Medical Intervention and Surgical Treatment (0/1, 0%), Medical and Interventional Treatment (4/6, 66.7%), Surgical Treatment (7/14, 50%), and Value of Spine Care (0/2, 0%). When NASS indicated there was sufficient evidence to offer a clear recommendation, ChatGPT-3.5 generated a concordant response 66.7% of the time (6/9). However, ChatGPT-3.5's concordance dropped to 36.8% when asked clinical questions that NASS did not provide a clear recommendation on (7/19). A further breakdown of ChatGPT-3.5's nonconcordance with the guidelines revealed that a vast majority of its inaccurate recommendations were due to them being "over-conclusive" (12/15, 80%), rather than "insufficient" (3/15, 20%). ChatGPT-4.0 answered 19 (67.9%) of the 28 total questions in concordance with NASS guidelines (P = 0.177). When NASS indicated there was sufficient evidence to offer a clear recommendation, ChatGPT-4.0 generated a concordant response 66.7% of the time (6/9). ChatGPT-4.0's concordance held up at 68.4% when asked clinical questions that NASS did not provide a clear recommendation on (13/19, P = 0.104). CONCLUSIONS: This study sheds light on the duality of LLM applications within clinical settings: one of accuracy and utility in some contexts versus inaccuracy and risk in others. ChatGPT was concordant for most clinical questions NASS offered recommendations for. However, for questions NASS did not offer best practices, ChatGPT generated answers that were either too general or inconsistent with the literature, and even fabricated data/citations. Thus, clinicians should exercise extreme caution when attempting to consult ChatGPT for clinical recommendations, taking care to ensure its reliability within the context of recent literature.
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BACKGROUND CONTEXT: Venous thromboembolism is a negative outcome of elective spine surgery. However, the use of thromboembolic chemoprophylaxis in this patient population is controversial due to the possible increased risk of epidural hematoma. ChatGPT is an artificial intelligence model which may be able to generate recommendations for thromboembolic prophylaxis in spine surgery. PURPOSE: To evaluate the accuracy of ChatGPT recommendations for thromboembolic prophylaxis in spine surgery. STUDY DESIGN/SETTING: Comparative analysis. PATIENT SAMPLE: None. OUTCOME MEASURES: Accuracy, over-conclusiveness, supplemental, and incompleteness of ChatGPT responses compared to the North American Spine Society (NASS) clinical guidelines. METHODS: ChatGPT was prompted with questions from the 2009 NASS clinical guidelines for antithrombotic therapies and evaluated for concordance with the clinical guidelines. ChatGPT-3.5 responses were obtained on March 5, 2023, and ChatGPT-4.0 responses were obtained on April 7, 2023. A ChatGPT response was classified as accurate if it did not contradict the clinical guideline. Three additional categories were created to further evaluate the ChatGPT responses in comparison to the NASS guidelines: over-conclusiveness, supplementary, and incompleteness. ChatGPT was classified as over-conclusive if it made a recommendation where the NASS guideline did not provide one. ChatGPT was classified as supplementary if it included additional relevant information not specified by the NASS guideline. ChatGPT was classified as incomplete if it failed to provide relevant information included in the NASS guideline. RESULTS: Twelve clinical guidelines were evaluated in total. Compared to the NASS clinical guidelines, ChatGPT-3.5 was accurate in 4 (33%) of its responses while ChatGPT-4.0 was accurate in 11 (92%) responses. ChatGPT-3.5 was over-conclusive in 6 (50%) of its responses while ChatGPT-4.0 was over-conclusive in 1 (8%) response. ChatGPT-3.5 provided supplemental information in 8 (67%) of its responses, and ChatGPT-4.0 provided supplemental information in 11 (92%) responses. Four (33%) responses from ChatGPT-3.5 were incomplete, and 4 (33%) responses from ChatGPT-4.0 were incomplete. CONCLUSIONS: ChatGPT was able to provide recommendations for thromboembolic prophylaxis with reasonable accuracy. ChatGPT-3.5 tended to cite nonexistent sources and was more likely to give specific recommendations while ChatGPT-4.0 was more conservative in its answers. As ChatGPT is continuously updated, further validation is needed before it can be used as a guideline for clinical practice.
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Background: Back and neck pain are leading causes of global disability that are associated with intervertebral disc (IVD) degeneration. Causes of IVD degeneration are multifactorial, and diet, age, and diabetes have all been linked to IVD degeneration. Advanced glycation endproducts (AGEs) accumulate in the IVD as a result of aging, diet, and diabetes, and AGE accumulation in the IVD has been shown to induce oxidative stress and catabolic activity that result in collagen damage. An association between AGE accumulation and IVD degeneration is emerging, yet mechanism behind this association remains unclear. The Receptor for AGEs (RAGE) is thought to induce catabolic responses in the IVD, and the AGE receptor Galectin 3 (Gal3) had a protective effect in other tissue systems but has not been evaluated in the IVD. Methods: This study used an IVD organ culture model with genetically modified mice to analyze the roles of RAGE and Gal3 in an AGE challenge. Results: Gal3 was protective against an AGE challenge in the murine IVD ex vivo, limiting collagen damage and biomechanical property changes. Gal3 receptor levels in the AF significantly decreased upon an AGE challenge. RAGE was necessary for AGE-induced collagen damage in the IVD, and RAGE receptor levels in the AF significantly increased upon AGE challenge. Discussion: These findings suggest both RAGE and Gal3 are important in the IVD response to AGEs and highlight Gal3 as an important receptor with protective effects on collagen damage. This research improves understanding the mechanisms of AGE-induced IVD degeneration and suggests Gal3 receptor modulation as a potential target for preventative and therapeutic treatment for IVD degeneration.
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Collagen plays a key structural role in both the annulus fibrosus (AF) and nucleus pulposus (NP) of intervertebral disks (IVDs). Changes in collagen content with degeneration suggest a shift from collagen type II to type I within the NP, and the activation of pro-inflammatory factors is indicative of fibrosis throughout. While IVD degeneration is considered a fibrotic process, an increase in collagen content with degeneration, reflective of fibrosis, has not been demonstrated. Additionally, changes in collagen content and structure in human IVDs with degeneration have not been characterized with high spatial resolution. The collagen content of 23 human lumbar L2/3 or L3/4 IVDs was quantified using second harmonic generation imaging (SHG) and multiple image processing algorithms, and these parameters were correlated with the Rutges histological degeneration grade. In the NP, SHG intensity increased with degeneration grade, suggesting fibrotic collagen deposition. In the AF, the entropy of SHG intensity was reduced with degeneration indicating increased collagen uniformity and suggesting less-organized lamellar structure. Collagen orientation entropy decreased throughout most IVD regions with increasing degeneration grade, further supporting a loss in collagen structural complexity. Overall, SHG imaging enabled visualization and quantification of IVD collagen content and organization with degeneration. There was an observed shift from an initially complex structure to more uniform structure with loss of microstructural elements and increased NP collagen polarity, suggesting fibrotic remodeling.
