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Prediction of risk of prolonged post-concussion symptoms: Derivation and validation of the TRICORDRR (Toronto Rehabilitation Institute Concussion Outcome Determination and Rehab Recommendations) score

PLoS Medicine Aug 12, 2021

Langer LK, Alavinia SM, Lawrence DW, et al. - Findings suggested an association of premorbid psychiatric conditions, pre-injury health system usage, and older age with increased risk of prolonged recovery from concussion. This risk score helps clinicians to estimate a person's chances of needing treatment more than 6 months after a concussion.

  • In a retrospective analysis, data from a cohort study (Ontario Concussion Cohort study, 2008 to 2016; n = 1,330,336) were used, which included all adults with a concussion diagnosis by either a primary care physician or in the emergency department, as well as 2 years of healthcare tracking postinjury (2008 to 2014, n = 587,057).

  • Females made up approximately 42.4% of the cohort, with individuals aged 18 to 30 making up the largest age group (31.0%).

  • Nearly 13% (73,122) of the cohort had prolonged post-concussion symptoms (PPCS; defined as 2 or more specialist visits for concussion-related symptoms more than 6 months after injury index date).

  • Based upon injury index year, total cohort was divided into Derivation (2009 to 2013, n = 417,335) and Validation cohorts (2009 and 2014, n = 169,722).

  • In the Derivation Cohort, variables like psychiatric disorders, migraines, sleep disorders, demographic factors, and pre-injury healthcare patterns were entered into multivariable logistic regression and CART modeling to calculate PPCS estimates, and the Validation Cohort used a forward selection logistic regression model.

  • Age > 61 years, bipolar disorder, high pre-injury primary care visits per year, personality disorders, and anxiety and depression were the variables with the highest risk of PPCS derived in the Derivation Cohort.

  • The area under the curve for the derivation model was 0.79, 0.79 for the Derivation Cohort's bootstrap internal validation, and 0.64 for the Validation model.

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