ArticleAdvances in orthopedics2025
When Should I Be Associating a Lateral Extra-Articular Procedure to My Anterior Cruciate Ligament Reconstruction? AI vs. Surgeon Decision-Making.
Article in Advances in orthopedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- When Should I Be Associating a Lateral Extra-Articular Procedure to My Anterior Cruciate Ligament Reconstruction? AI vs. Surgeon Decision-Making.Advances in orthopedics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Residual rotational instability following anterior cruciate ligament reconstruction (ACLR) remains a clinical challenge, leading to renewed interest in adjunctive lateral extra-articular procedures (LEAP). This study aimed to compare clinical decision-making between experienced orthopaedic surgeons and an artificial intelligence (AI) model regarding indications for LEAP in ACLR, to assess concordance, and to explore the potential role of AI in surgical planning. Methods: A cross-sectional comparative study was conducted using 40 hypothetical ACLR case profiles, reflecting a range of patient demographics, injury characteristics, and activity levels. An AI model trained on literature-based criteria and expert input generated binary recommendations ("perform LEAP" or "do not perform LEAP") for each case. Twenty-two high-volume knee surgeons independently reviewed all cases, blinded to AI recommendations, and indicated whether they would recommend a LEAP. Agreement between surgeon decisions and AI recommendations was calculated, and factors influencing concordance were analysed using chi-square tests, Results: Overall, surgeon agreement with AI recommendations was high but varied by clinical factors. A positive pivot shift test was the strongest predictor of concordance (93.9% ± 4.8 vs. 71.8% ± 25.7; Conclusion: Surgeons demonstrated strong alignment with AI recommendations in clear-cut scenarios, particularly when traditional clinical signs such as a positive pivot shift were present. Discordance emerged in borderline cases, notably when AI recommended against LEAP or in female patients. These findings suggest AI could support orthopaedic decision-making by standardising criteria for LEAP, enhancing consistency in ambiguous cases, and prompting the development of evidence-based scoring systems to refine indications. Trial Registration: IRB cleared, no need for trial registration as all cases hypothetical and no patient data included in the study.
Identifiers
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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.