Davis, G; Makdissi, M
Use of video to facilitate sideline concussion diagnosis and management decision-making Journal Article
In: Journal of Science & Medicine in Sport, vol. 19, no. 11, pp. 898–902, 2016.
Abstract | Links | BibTeX | Tags: brain concussion, Clinical management, Flowchart, football, Video analysis
@article{Davis2016,
title = {Use of video to facilitate sideline concussion diagnosis and management decision-making},
author = {Davis, G and Makdissi, M},
doi = {10.1016/j.jsams.2016.02.005},
year = {2016},
date = {2016-01-01},
journal = {Journal of Science \& Medicine in Sport},
volume = {19},
number = {11},
pages = {898--902},
abstract = {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. Design Prospective cohort study. 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. © 2016 Sports Medicine Australia},
keywords = {brain concussion, Clinical management, Flowchart, football, Video analysis},
pubstate = {published},
tppubtype = {article}
}
Davis, G; Makdissi, M
Use of video to facilitate sideline concussion diagnosis and management decision-making Journal Article
In: Journal of Science & Medicine in Sport, vol. 19, no. 11, pp. 898–902, 2016.
@article{Davis2016,
title = {Use of video to facilitate sideline concussion diagnosis and management decision-making},
author = {Davis, G and Makdissi, M},
doi = {10.1016/j.jsams.2016.02.005},
year = {2016},
date = {2016-01-01},
journal = {Journal of Science \& Medicine in Sport},
volume = {19},
number = {11},
pages = {898--902},
abstract = {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. Design Prospective cohort study. 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. © 2016 Sports Medicine Australia},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Davis, G; Makdissi, M
Use of video to facilitate sideline concussion diagnosis and management decision-making Journal Article
In: Journal of Science & Medicine in Sport, vol. 19, no. 11, pp. 898–902, 2016.
Abstract | Links | BibTeX | Tags: brain concussion, Clinical management, Flowchart, football, Video analysis
@article{Davis2016,
title = {Use of video to facilitate sideline concussion diagnosis and management decision-making},
author = {Davis, G and Makdissi, M},
doi = {10.1016/j.jsams.2016.02.005},
year = {2016},
date = {2016-01-01},
journal = {Journal of Science \& Medicine in Sport},
volume = {19},
number = {11},
pages = {898--902},
abstract = {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. Design Prospective cohort study. 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. © 2016 Sports Medicine Australia},
keywords = {brain concussion, Clinical management, Flowchart, football, Video analysis},
pubstate = {published},
tppubtype = {article}
}