Evidence map›Paper›PMID 36762026›Full record

ArticleDigital health

An automated, web-based triage tool may optimise referral pathways in elective orthopaedic surgery: A proof-of-concept study.

Alexandra L Stanley, Thomas C Edwards, Martin D Jaere, Johnathan R Lex, Gareth G Jones

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. MRI use leading up to total knee arthroplasty: a retrospective cohort study.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024
    Article
  5. 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

5 authors.

Alexandra L StanleyFaculty of Medicine, Imperial College London, London, UK.ORCID https://orcid.org/0000-0002-5476-5688
Thomas C EdwardsFaculty of Medicine, Imperial College London, London, UK.
Martin D JaereFaculty of Medicine, Imperial College London, London, UK.
Johnathan R LexDivision of Orthopaedic Surgery, Department of Surgery, University of Toronto, Toronto, Canada.
Gareth G JonesFaculty of Medicine, Imperial College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Knee pain is caused by various pathologies, making evaluation in primary-care challenging. Subsequently, an over-reliance on imaging, such as radiographs and MRI exists. Electronic-triage tools represent an innovative solution to this problem. The aims of this study were to establish the magnitude of unnecessary knee imaging prior to orthopaedic surgeon referral, and ascertain whether an e-triage tool outperforms existing clinical pathways to recommend correct imaging. Methods: Patients ≥18 years presenting with knee pain treated with arthroscopy or arthroplasty at a single academic hospital between 2015 and 2020 were retrospectively identified. The timing and appropriateness of imaging were assessed according to national guidelines, and classified as 'necessary', 'unnecessary' or 'required MRI'. Based on an eDelphi consensus study, a symptom-based e-triage tool was developed and piloted to preliminarily diagnose five common knee pathologies and suggest appropriate imaging. Results: 1462 patients were identified. 17.2% ( Conclusion: A substantial number of knee pain patients receive incorrect imaging, incurring delays and unnecessary costs. A symptom-based e-triage tool was developed, with promising performance and user feedback. With refinement using larger datasets, this tool has the potential to improve wait-times, referral quality and reduce cost.

Indexed as

chatbotcomputer-assisted diagnosisdigital healthe-triagekneemedical informaticsOrthopaedicscreeningsurgery

Identifiers

PMID36762026
PMCPMC9903022

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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.