Objectives: Video analysis can provide critical information to improve diagnostic accuracy and speed of clinical decision-making in potential cases of concussion. The objective of this study was to validate a hierarchical flowchart for the assessment of video signs of concussion, and to determine whether its implementation could improve the process of game day video assessment. Methods: All impacts and collisions potentially resulting in a concussion were identified during 2012 and 2013 Australian Football League (AFL) seasons. Consensus definitions were developed for clinical signs associated with concussion. A hierarchical flowchart was developed based on the reliability and validity of the video signs of concussion. Ninety videos were assessed, with 45 incidents of clinically confirmed concussion, and 45 cases where no concussion was sustained. Each video was examined using the hierarchical flowchart, and a single response was given for each video based on the highest-ranking element in the flowchart. Results: No protective action, impact seizure, motor incoordination or blank/vacant look were the highest ranked video signs in almost half of the clinically confirmed concussions, but in only 8.8% of non-concussed individuals. The presence of facial injury, clutching at the head and slow to get up were the highest ranked sign in 77.7% of non-concussed individuals. Conclusions: This study suggests that the implementation of a flowchart model could improve timely assessment of concussion, and it identifies the video signs that should trigger automatic removal from play. (C) 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Objectives: The objectives of the study were to assess the relationship between various player and game factors and risk of concussion; and to assess the reliability of video analysis for mechanistic assessment of concussion in Australian football. Methods: All impacts and collisions resulting in concussion were identified during the 2011 Australian Football League season. An extensive list of factors for assessment was created based upon previous analysis of concussion in Australian Football League and expert opinions. The authors independently reviewed the video clips and correlation for each factor was examined. Results: A total of 82 concussions were reported in 194 games (rate: 8.7 concussions per 1000 match hours; 95% confidence interval: 6.9-10.5). Player demographics and game variables such as venue, timing of the game (day, night or twilight), quarter, travel status (home or interstate) or score margin did not demonstrate a significant relationship with risk of concussion; although a higher percentage of concussions occurred in the first 5 min of game time of the quarter (36.6%), when compared to the last 5 min (20.7%). Variables with good inter-rater agreement included position on the ground, circumstances of the injury and cause of the impact. The remainder of the variables assessed had fair-poor inter-rater agreement. Common problems included insufficient or poor quality video and interpretation issues related to the definitions used. Conclusions: Clear definitions and good quality video from multiple camera angles are required to improve the utility of video analysis for concussion surveillance in Australian football. (C) 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.