Evidence map›Paper›PMID 38974054›Full record

ArticleJournal of experimental orthopaedics2024

Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery.

Marco-Christopher Rupp, Lukas B Moser, Silvan Hess, Peter Angele, Matthias Aurich, Felix Dyrna, Stefan Nehrer, Markus Neubauer, Johannes Pawelczyk, Kaywan Izadpanah and 3 more

Abstract read
In one paragraph

Article in Journal of experimental orthopaedics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. From patient notes to prognostication: The revolutionary potential of event-based foundation models in orthopaedics.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026
    Article
  2. Article
  3. Artificial intelligence in orthopaedics: Enhanced examinations, ambient intelligence and the future of clinical practice.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026
    Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
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

13 authors.

Marco-Christopher RuppSektion Sportorthopädie, Klinikum rechts der Isar Technische Universität München Munich Germany.ORCID 0000-0001-7899-6299
Lukas B MoserKlinische Abteilung für Orthopädie und Traumatologie Universitätsklinikum Krems Krems an der Donau Austria.
Silvan HessUniversitätsklinik für Orthopädische Chirurgie und Traumatologie, Inselspital Bern Switzerland.
Peter AngeleSporthopaedicum Regensburg Germany.
Matthias AurichUniversitätsklinikum Halle (Saale) Halle Germany.
Felix DyrnaGelenkzentrum Leipzig Leipzig Germany.
Stefan NehrerKlinische Abteilung für Orthopädie und Traumatologie Universitätsklinikum Krems Krems an der Donau Austria.
Markus NeubauerKlinische Abteilung für Orthopädie und Traumatologie Universitätsklinikum Krems Krems an der Donau Austria.
Johannes PawelczykSektion Sportorthopädie, Klinikum rechts der Isar Technische Universität München Munich Germany.ORCID 0009-0001-4128-5431
Kaywan IzadpanahKlinik für Orthopädie und Unfallchirurgie, Universitätsklinikum Freiburg, Medizinische Fakultät Albert-Ludwigs-Universität Freiburg Freiburg Germany.
Johannes ZellnerSporthopaedicum Regensburg Germany.
Philipp NiemeyerOCM - Orthopädische Chirurgie München Munich Germany.
AGA‐Komitee Innovation und Translation

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The purpose of this study was to evaluate the perspective of orthopaedic surgeons on the impact of artificial intelligence (AI) and to evaluate the influence of experience, workplace setting and familiarity with digital solutions on views on AI. Methods: Orthopaedic surgeons of the AGA Society for Arthroscopy and Joint Surgery were invited to participate in an online, cross-sectional survey designed to gather information on professional background, subjective AI knowledge, opinion on the future impact of AI, openness towards different applications of AI, and perceived advantages and disadvantages of AI. Subgroup analyses were performed to examine the influence of experience, workplace setting and openness towards digital solutions on perspectives towards AI. Results: Overall, 360 orthopaedic surgeons participated. The majority indicated average (43.6%) or rudimentary (38.1%) AI knowledge. Most (54.5%) expected AI to substantially influence orthopaedics within 5-10 years, predominantly as a complementary tool (91.1%). Preoperative planning (83.8%) was identified as the most likely clinical use case. A lack of consensus was observed regarding acceptable error levels. Time savings in preoperative planning (62.5%) and improved documentation (81%) were identified as notable advantages while declining skills of the next generation (64.5%) were rated as the most substantial drawback. There were significant differences in subjective AI knowledge depending on participants' experience ( Conclusion: The majority of orthopaedic surgeons in this survey anticipated a notable positive impact of AI on their field, primarily as an assistive technology. A lack of consensus on acceptable error levels of AI and concerns about declining skills among future surgeons were observed. Level of Evidence: Level IV, cross-sectional study.

Indexed as

artificial intelligenceattitude of health personnelmachine learningorthopaedicssurvey

Identifiers

PMID38974054
PMCPMC11227606

What OpenQuestion 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 OpenQuestion graph.