Evidence map›Paper›PMID 41220409›Full record

ArticleJournal of clinical orthopaedics and trauma2025

Feasibility study of the Cambridge knee injury tool (CamKIT): 18-month analysis of acute knee injuries at an urgent treatment centre.

Thomas Molloy, Benjamin Gompels, Simone Castagno, Andrew McCaskie, Stephen McDonnell

Abstract read
In one paragraph

Article in Journal of clinical orthopaedics and trauma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Thomas MolloyDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
Benjamin GompelsDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
Simone CastagnoDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
Andrew McCaskieDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.
Stephen McDonnellDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Soft tissue knee injuries are associated with many short- and long-term consequences. Currently, obstacles in the diagnostic pathway lead to inefficiencies in the management process, resulting in suboptimal patient outcomes. Early stratification of knee injury severity is essential for guiding timely investigations and management decisions. This study aimed to prospectively evaluate how the Cambridge Knee Injury Tool (CamKIT) performs in stratifying knee injuries at initial presentation. Methods: This prospective observational study involved eighty-five participants presenting with acute knee injuries in a Major Regional Urgent Treatment Centre (UTC) over 18 months. Patients recorded information regarding patient factors, external factors, injury mechanisms and signs and symptoms at index presentation. CamKIT scores were then calculated. Patients then continued the management stream determined by the treating healthcare team. Management decisions were not influenced by the results of the CamKIT score. Patient outcomes were analysed by extracting time-to-event outcomes, injury classification, and management information. Statistical analysis involved sensitivity and specificity calculations, descriptive statistics, and Mann-Whitney Test calculations between injured and non-injured cohorts, and surgical and conservative cohorts. Results: The tool achieved a sensitivity of 100 % and specificity of 31.7 %, with a negative predictive value (NPV) of 100 % and a positive predictive value (PPV) of 34.9 %. CamKIT scores were higher in patients with injuries (median 8; IQR: 7-9) than in non-injured patients (median 6; IQR: 4-7) (p < 0.0001). Similarly, patients who proceeded to surgical intervention (n = 9) had higher scores (median 8; IQR: 7.5-10) compared to those managed conservatively (median 6; IQR: 4.25-7) (p = 0.0001). Conclusion: The CamKIT continues to show promise in guiding early triage and management of acute knee injuries. Future research involves a multicenter study as well as the integration of machine learning to develop a more robust prediction tool and create a risk-stratified management protocol.

Indexed as

ClinicalInjuryKneePredictionRisk

Identifiers

PMID41220409
PMCPMC12598319

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.