Background: The Coma Recovery Scale-Revised (CRS-R) is the most recommended instrument to examine the neurobehavioral condition of individuals with disorders of consciousness (DOCs). Different studies have investigated the prognostic value of the information provided by the conventional administration of the scale, while other measures derived from the scale have been proposed to improve the prognosis of DOCs. However, the heterogeneity of the data used in the different studies prevents a reliable comparison of the identified predictors and measures. Objectives: This study investigates which information derived from the CRS-R provides the most reliable prediction of both the neurobehavioral state and recovery of consciousness at the discharge of a long-term neurorehabilitation program. Methods: The clinical records of 171 individuals with DOCs admitted to an inpatient neurorehabilitation program for a minimum of 3 months were used to implement machine learning classifiers that were trained to predict the neurobehavioral state and recovery of consciousness at discharge.
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Recovery of consciousness
Timeframe: At discharge from the rehabilitation hospital (median of 365 days)
Neurobehavioral state
Timeframe: At discharge from the rehabilitation hospital (median of 365 days)