ArticleShoulder & elbow2024
ChatGPT is capable of providing satisfactory responses to frequently asked questions regarding total shoulder arthroplasty.
Article in Shoulder & elbow, 2024. 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Do ChatGPT and Gemini provide accurate answers to patient questions about glenohumeral arthritis?JSES reviews, reports, and techniques · 2026Article
- ChatGPT models provide higher-quality but lower-readability responses than Google Gemini regarding anterior shoulder instability, with no added benefit of the orthopaedic expert plugin.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The rising prominence of artificial intelligence in healthcare has revolutionized patient access to medical information. This cross-sectional study sought to assess if ChatGPT could satisfactorily address common patient questions about total shoulder arthroplasty (TSA). Methods: Ten commonly encountered questions in TSA practice were selected and posed to ChatGPT. Each response was assessed for accuracy and clarity using the Mika et al. scoring system, which ranges from "excellent response not requiring clarification" to "unsatisfactory response requiring substantial clarification," and a modified DISCERN score. The readability was further evaluated using the Flesch Reading Ease Score and the Flesch-Kincaid Grade Level. Results: The mean Mika et al. score was 2.93, corresponding to an overall subjective rating of "satisfactory but requiring moderate clarification." The mean DISCERN score was 46.60, which is considered "fair." The readability analysis suggested that the responses were at a college-graduate level, higher than the recommended level for patient educational materials. Discussion: Our results suggest that ChatGPT has the potential to supplement the collaborative decision-making process between patients and experienced orthopedic surgeons for TSA-related inquiries. Ultimately, while tools like ChatGPT can enhance traditional patient education methods, they should not replace direct consultations with medical professionals.
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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.