Observational studyEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2026
Multi-criteria evaluation of clinical decision-making performance in spinal neurosurgery and physical therapy scenarios: A comparative analysis of artificial intelligence models.
Observational study in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Generative AI and Large Language Models in Rehabilitation: A Scoping Review.Life (Basel, Switzerland) · 2026Review
- Evaluation of AI language models in answering pregnancy-related questions assessed by obstetrics specialists.Scientific reports · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of AI in healthcare, particularly in clinical decision-making, has shown promising results. This study focuses on evaluating the performance of GPT-4 and GPT-3.5, two advanced AI models, in the context of spinal neurosurgery and physiotherapy, areas that require precise and dynamic decision-making.
methodsWe conducted a prospective, observational study with 64 participants, including neurosurgeons and physiotherapists, who evaluated AI-generated responses for 10 detailed clinical scenarios. The assessment criteria included diagnostic accuracy, treatment suitability, surgical technique detail, and rehabilitation planning. Each scenario was meticulously crafted to reflect common yet complex clinical situations.
resultsThe study revealed that the GPT-4 consistently outperformed the GPT-3.5 across all the evaluated criteria, with the most significant differences observed in treatment suitability and rehabilitation planning. Statistical analyses, including paired t tests and ANOVA, confirmed the superiority of the GPT-4, highlighting its advanced language processing capabilities and broader medical knowledge base. Reliability analyses further supported these findings. Cronbach’s alpha values indicated moderate internal consistency for GPT-4 (α = 0.344) and lower consistency for GPT-3.5 (α = 0.133). Additionally, Cohen’s Kappa values demonstrated moderate agreement for GPT-4 (κ = 0.65) and fair agreement for GPT-3.5 (κ = 0.48), further validating the reliability of the participants’ evaluations.
conclusionsWhile the GPT-4 has significant potential as a clinical decision support tool, especially in complex and multidisciplinary fields such as spinal neurosurgery and physiotherapy, its recommendations should be carefully integrated with clinical expertise. Further research is essential to enhance its application and ensure that AI can effectively support dynamic medical environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.