Evidence map›Paper›PMID 41625387›Full record

ArticleJB & JS open access

ChatGPT-4o Mini Fabricates and Miscites Evidence for American Academy of Orthopaedic Surgeons Hip Fracture Clinical Practice Guidelines.

David McCavitt, Soroush Shabani, Ashley Mulakaluri, Sahil Dhandi, Andrew Duong, Joseph T Patterson

Abstract read
In one paragraph

Article in JB & JS open access. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

David McCavittDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID https://orcid.org/0009-0001-0217-7649
Soroush ShabaniDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID https://orcid.org/0000-0001-5006-3577
Ashley MulakaluriDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID https://orcid.org/0009-0002-7771-3327
Sahil DhandiDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Andrew DuongDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Joseph T PattersonDepartment of Orthopaedic Surgery, Keck School of Medicine of the University of Southern California, Los Angeles, California.ORCID https://orcid.org/0000-0002-7494-7366

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Generative artificial intelligence (AI) large language model (LLM) chatbots, such as ChatGPT, are increasingly used to answer medical questions. This study sought to assess the accuracy and quality of evidence cited in ChatGPT-4o mini responses to questions pertaining to hip fracture care. Methods: Prompt questions regarding hip fracture management that aligned with each of the 19 recommendations published in the American Academy of Orthopaedic Surgeons (AAOS) Clinical Practice Guideline (CPG) for Management of Hip Fractures in Older Adults were posed to the ChatGPT-4o mini LLM asynchronously by 4 independent medical student graders. Three prompt variations were applied for each recommendation, reflecting the perspectives of a physician, a patient, and a general information seeker. Graders then requested from the LLM a reference list with PubMed Identifier (PMID) numbers supporting each recommendation. Accuracy and clarity of responses were assessed using a standard rubric for overlap with CPG citations, fabrications, and inaccurate citations. Results: ChatGPT-4o mini returned 228 responses to prompts seeking advice on AAOS CPG hip management recommendations. 76.3% of responses were "accurate" to the CPG recommendation. 88.2% of responses received a clarity rating of "excellent". ChatGPT-4o mini provided 228 responses citing 2,556 publications when prompted for supporting evidence, of which 1.1% overlapped with AAOS CPG references, and 7.9% were fabricated. Of the publications cited by the LLM which exist in the PubMed index, 91.7% were given with incorrect authors, 91.5% incorrect titles, 91.4% incorrect pages, 91.0% incorrect PMIDs, 90.9% incorrect journals, 90.3% incorrect journal volumes, and 20.0% incorrect publication years. Responses for an AAOS CPG strong recommendation strength were significantly more likely to be "accurate" (p < 0.001), and responses for an AAOS CPG limited strength recommendation were significantly more likely to be "unsupported" (p < 0.001). Conclusions: ChatGPT-4o mini provided clear, moderately accurate responses with rampantly erroneous and occasionally fabricated citations to queries about hip fracture care derived from the AAOS Clinical Practice Guideline on Management of Hip Fractures in Older Adults. Level of Evidence: Level V Therapeutic. See Instructions for Authors for a complete description of levels of evidence.

Identifiers

PMID41625387
PMCPMC12854652

What OpenQuestion holds

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Registered trials

None linked

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.