London International Consensus and Delphi study on hamstring injuries part 1: classification.

ABSTRACT

Muscle injury classification systems for hamstring injuries have evolved to use anatomy and imaging information to aid management and prognosis. However, classification systems lack reliability and validity data and are not specific to individual hamstring muscles, potentially missing parameters vital for sport-specific and activity-specific decision making. A narrative evidence review was conducted followed by a modified Delphi study to build an international consensus on best-practice decision-making for the classification of hamstring injuries. This comprised a digital information gathering survey to a cohort of 46 international hamstring experts (sports medicine physicians, physiotherapists, surgeons, trainers and sports scientists) who were also invited to a face-to-face consensus group meeting in London . Fifteen of these expert clinicians attended to synthesise and refine statements around the management of hamstring injury. A second digital survey was sent to a wider group of 112 international experts. Acceptance was set at 70% agreement. Rounds 1 and 2 survey response rates were 35/46 (76%) and 99/112 (88.4%) of experts responding. Most commonly, experts used the British Athletics Muscle Injury Classification (BAMIC) (58%), Munich (12%) and Barcelona (6%) classification systems for hamstring injury. Issues identified to advance imaging classifications systems include detailing individual hamstring muscles, establishing optimal use of imaging in diagnosis and classification, and testing the validity and reliability of classification systems. The most used hamstring injury classification system is the BAMIC. This consensus panel recommends hamstring injury classification systems evolve to integrate imaging and clinical parameters around individual muscles, injury mechanism, sporting demand, functional criteria and patient-reported outcome measures. More research is needed on surgical referral and effectiveness criteria, and validity and reliability of classification systems to guide management.