Biomarkers of autonomic regulation for predicting psychological distress and functional recovery following road traffic injuries: protocol for a prospective cohort study.

Biomarkers of autonomic regulation for predicting psychological distress and functional recovery following road traffic injuries: protocol for a prospective cohort study.

Pozzato, Ilaria;Craig, Ashley;Gopinath, Bamini;Tran, Yvonne;Dinh, Michael;Gillett, Mark;Cameron, Ian;
BMJ open 2019 Vol. 9 pp. e024391
265
pozzato2019biomarkersbmj

Abstract

Psychological distress is a prevalent condition often overlooked following a motor vehicle crash (MVC), particularly when injuries are not severe. The aim of this study is to examine whether biomarkers of autonomic regulation alone or in combination with other factors assessed shortly after MVC could predict risk of elevated psychological distress and poor functional recovery in the long term, and clarify links between mental and physical health consequences of traffic injury.This is a controlled longitudinal cohort study, with follow-up occurring at 3, 6 and 12 months. Participants include up to 120 mild to moderately injured MVC survivors who consecutively present to the emergency departments of two hospitals in Sydney and who agree to participate, and a group of up to 120 non-MVC controls, recruited with matched demographic characteristics, for comparison. WHO International Classification of Functioning is used as the framework for study assessment. The primary outcomes are the development of psychological distress (depressive mood and anxiety, post-traumatic stress symptoms, driving phobia, adjustment disorder) and biomarkers of autonomic regulation. Secondary outcomes include indicators of physical health (presence of pain/fatigue, physical functioning) and functional recovery (quality of life, return to function, participation) as well as measures of emotional and cognitive functioning. For each outcome, risk will be described by the frequency of occurrence over the 12 months, and pathways determined via latent class mixture growth modelling. Regression models will be used to identify best predictors/biomarkers and to study associations between mental and physical health.Ethical approvals were obtained from the Sydney Local Health District and the research sites Ethics Committees. Study findings will be disseminated to health professionals, related policy makers and the community through peer-reviewed journals, conference presentations and health forums.ACTRN12616001445460.

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