The reliability and validity of video analysis for the assessment of the clinical signs of concussion in Australian football. Issue 10 (October 2016)

• Record Type: Journal Article
• Authors: Makdissi, Michael; Davis, Gavin
• Is Part Of: Journal of science and medicine in sport. Volume 19:Issue 10(2016:Oct.)
• Page Start: 859
• Page End: 863
• Publication Date: 2016-10
• Subjects: Brain concussion -- Football -- Diagnosis -- Sensitivity and specificity -- Video analysis; Sports sciences -- Periodicals; Sports medicine -- Periodicals; Exercise -- Physiological aspects -- Periodicals; Sports -- physiology -- Periodicals; Sports Medicine -- Periodicals; Sportgeneeskunde; 617.102705
• DOI: 10.1016/j.jsams.2016.02.015
• Languages: English
• ISSNs: 1440-2440

Abstract

Abstract: Objectives: The objective of this study was to determine the reliability and validity of identifying clinical signs of concussion using video analysis in Australian football. Design: Prospective cohort study. Methods: All impacts and collisions potentially resulting in a concussion were identified during 2012 and 2013 Australian Football League seasons. Consensus definitions were developed for clinical signs associated with concussion. For intra- and inter-rater reliability analysis, two experienced clinicians independently assessed 102 randomly selected videos on two occasions. Sensitivity, specificity, positive and negative predictive values were calculated based on the diagnosis provided by team medical staff. Results: 212 incidents resulting in possible concussion were identified in 414 Australian Football League games. The intra-rater reliability of the video-based identification of signs associated with concussion was good to excellent. Inter-rater reliability was good to excellent for impact seizure, slow to get up, motor incoordination, ragdoll appearance (2 of 4 analyses), clutching at head and facial injury . Inter-rater reliability for loss of responsiveness and blank and vacant look was only fair and did not reach statistical significance. The feature with the highest sensitivity was slow to get up (87%), but this sign had a low specificity (19%). Other video signs had a high specificity but low sensitivity. Blank and vacant look (100%) and motor incoordination (81%) had the highest positive predictive value. Conclusions: Video analysis may be a useful adjunct to the side-line assessment of a possible concussion. Video analysis however should not replace the need for a thorough multimodal clinical assessment.