Evidence map›Paper›PMID 41245704›Full record

ReviewJournal of experimental orthopaedics2025

Artificial intelligence fails to outperform orthopaedic surgeons: A systematic review.

Jemima Russell, Jamie Rosen, Martinique Vella-Baldacchino

Abstract readReview
In one paragraph

Review in Journal of experimental orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Jemima RussellDepartment of Surgery and Cancer MSk Lab-Imperial College London London UK.ORCID https://orcid.org/0009-0009-0014-4390
Jamie RosenDepartment of Surgery and Cancer MSk Lab-Imperial College London London UK.ORCID https://orcid.org/0009-0005-7505-6871
Martinique Vella-BaldacchinoDepartment of Surgery and Cancer MSk Lab-Imperial College London London UK.ORCID https://orcid.org/0000-0002-3284-7236

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Artificial intelligence (AI) in orthopaedic surgery is increasingly applied to analyse clinical data, triage patients and interpret imaging with high accuracy. Orthopaedics surgery faces unique challenges, including high patient volumes, complex cases and prolonged waiting lists, highlighting the need for efficiency and decision support. To justify implementation, AI must demonstrate performance comparable to surgeons. This systematic review evaluates AI's performance relative to surgeons to determine its value as a complementary tool in orthopaedic practice. Methods: This systematic review was conducted using OVID Medline. Relevant studies published up to 13 August 2025 were identified. Included studies were categorised into decision making, management plans, clinical knowledge, quality control, and answering patients' frequently asked questions (FAQs). Results: Of 419 identified studies, 16 were eligible. ChatGPT showed high sensitivity in identifying patients achieving clinically meaningful improvements (97% vs. 90% for surgeons) but lower specificity (33% vs. 63%) and accuracy (65% vs. 76%). AI demonstrates comparable or superior performance to surgeons in emergency scenarios and answering patient FAQs, scoring higher across empathy, accuracy, completeness and overall quality (4.4 vs. 3.5-3.7). Residents outperformed AI in examinations (74.2% vs. 47.2%). AI showed limited accuracy in knee osteoarthritis radiographic staging (35% vs. >80%). Conclusions: AI demonstrates the potential to support clinical efficiency and patient communication in orthopaedics. However, concerns about bias, quality risks, overconfidence and reliance on outdated information prevent it from replacing human expertise. Clinician-led design and validation are required to ensure safe and effective integration into clinical practice. Level of Evidence: Level IV.

Indexed as

artificial intelligenceChatGPTmachine learningorthopaedicsorthopaedic surgery

Identifiers

PMID41245704
PMCPMC12616488

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.