The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries

Background/aim This study focuses on the development of the Cambridge Knee Injury Tool (CamKIT), a clinical prediction tool developed as a 12-point scoring tool based on a modified e-Delphi study.Methods A retrospective cohort evaluation was conducted involving 229 patients presenting to a Major Tra...

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Main Authors: Stephen McDonnell, Simone Castagno, Thomas Molloy, Benjamin Gompels
Format: Article
Language:English
Published: BMJ Publishing Group 2025-01-01
Series:BMJ Open Sport & Exercise Medicine
Online Access:https://bmjopensem.bmj.com/content/11/1/e002357.full
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author Stephen McDonnell
Simone Castagno
Thomas Molloy
Benjamin Gompels
author_facet Stephen McDonnell
Simone Castagno
Thomas Molloy
Benjamin Gompels
author_sort Stephen McDonnell
collection DOAJ
description Background/aim This study focuses on the development of the Cambridge Knee Injury Tool (CamKIT), a clinical prediction tool developed as a 12-point scoring tool based on a modified e-Delphi study.Methods A retrospective cohort evaluation was conducted involving 229 patients presenting to a Major Trauma Centre with acute knee pain over 3 months. The evaluation extracted data on the 12 scoring tool variables as well as diagnostic and management pathway outcomes. CamKIT scores for the injured and non-injured cohorts were then calculated and evaluated.Results The CamKIT yielded a median score of 7.5 (IQR: 6–9) in the injured cohort, compared with a median score of 2 (IQR: 1–4) in the non-injured cohort, with a statistically significant difference (p<0.0001). When constructed as a three-tier risk stratification tool, the CamKIT produces a sensitivity of 100%, a specificity of 94.3%, a positive predictive value of 89% and a negative predictive value of 100% for diagnosing clinically significant soft tissue knee injuries.Conclusion The CamKIT provides a non-invasive tool that has the potential to streamline the diagnostic process and empower healthcare workers in resource-stretched settings by instilling confidence and promoting accuracy in clinical decision-making. The CamKIT also has the potential to support efficiency in the secondary healthcare setting by enabling more targeted and timely use of specialist resources. This research contributes to the ongoing efforts to enhance patient outcomes and the overall quality of care in managing acute knee injuries.
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spelling doaj-art-97a150f7a2214ded98ef60877340ba252025-01-27T20:35:09ZengBMJ Publishing GroupBMJ Open Sport & Exercise Medicine2055-76472025-01-0111110.1136/bmjsem-2024-002357The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuriesStephen McDonnell0Simone Castagno1Thomas Molloy2Benjamin Gompels3Division of Trauma and Orthopaedic Surgery, University of Cambridge, Cambridge, UK1 Department of Surgery, University of Cambridge, Cambridge, UKDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Cambridge, UKDivision of Trauma and Orthopaedic Surgery, University of Cambridge, Cambridge, UKBackground/aim This study focuses on the development of the Cambridge Knee Injury Tool (CamKIT), a clinical prediction tool developed as a 12-point scoring tool based on a modified e-Delphi study.Methods A retrospective cohort evaluation was conducted involving 229 patients presenting to a Major Trauma Centre with acute knee pain over 3 months. The evaluation extracted data on the 12 scoring tool variables as well as diagnostic and management pathway outcomes. CamKIT scores for the injured and non-injured cohorts were then calculated and evaluated.Results The CamKIT yielded a median score of 7.5 (IQR: 6–9) in the injured cohort, compared with a median score of 2 (IQR: 1–4) in the non-injured cohort, with a statistically significant difference (p<0.0001). When constructed as a three-tier risk stratification tool, the CamKIT produces a sensitivity of 100%, a specificity of 94.3%, a positive predictive value of 89% and a negative predictive value of 100% for diagnosing clinically significant soft tissue knee injuries.Conclusion The CamKIT provides a non-invasive tool that has the potential to streamline the diagnostic process and empower healthcare workers in resource-stretched settings by instilling confidence and promoting accuracy in clinical decision-making. The CamKIT also has the potential to support efficiency in the secondary healthcare setting by enabling more targeted and timely use of specialist resources. This research contributes to the ongoing efforts to enhance patient outcomes and the overall quality of care in managing acute knee injuries.https://bmjopensem.bmj.com/content/11/1/e002357.full
spellingShingle Stephen McDonnell
Simone Castagno
Thomas Molloy
Benjamin Gompels
The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
BMJ Open Sport & Exercise Medicine
title The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
title_full The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
title_fullStr The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
title_full_unstemmed The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
title_short The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries
title_sort cambridge knee injury tool camkit a clinical prediction tool for acute soft tissue knee injuries
url https://bmjopensem.bmj.com/content/11/1/e002357.full
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