The Cambridge Knee Injury Tool (CamKIT): a clinical prediction tool for acute soft tissue knee injuries - Stephen McDonnell; Simone Castagno; Thomas Molloy; Benjamin Gompels (BMJ Open Sport & Exercise Medicine)
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.