Could tracking your cognitive health be important for personalized healthcare? Two recent publications suggest that the answer is yes.
The studies, published in Neurorehabilitation and Neural Repair (Jeffers et al.; 2018a, 2018b), used an algorithm to identify a combination of biomarkers that can successfully predict stroke recovery in rats. The researchers suggest that based on the initial level of impairment and the degree of brain injury, they can accurately prescribe an individualize dose of rehabilitation. Rats that meet their prescribed dose of rehabilitation show significant functional recovery, but rats that do not meet their prescribed dose of rehabilitation do not recover.
Similar algorithms have been developed for stroke patients with visual spatial neglect (Winters, 2016) and aphasia (Marchi et al., 2017). The researchers found that factors such as age, stroke severity, and motor and cognitive impairments can predict stroke recovery. In these studies, stroke recovery is defined as changes in cognition measured using standardized tests such as the Letter Cancellation Test (LCT). The LCT requires patients to cross out a specific letter on a single document. Patients who were predicted to recover performed significantly better on the LCT at baseline, missing less of the letters that were meant to be crossed out, compared to those who were predicted to not recover.
These studies suggest that a one-size-fits-all approach to medicine is not as effective as a personalized approach. Healthcare should be individually based on biomarkers of recovery to achieve a personalized medicine approach in order to optimize early triage and better inform patients and caregivers. Data on cognitive performance before and after treatment can inform the amount of rehabilitation that is necessary for recovery.
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