Objective: To determine whether a new index for multiple chronic conditions (MCCs) predicts poststroke functional outcome (FO), we developed and internally validated the new MCC index in patients with ischemic stroke.
Methods: A prospective cohort of patients with ischemic stroke (2008-2017) was interviewed at baseline and 90 days in the Brain Attack Surveillance in Corpus Christi Project. An average of 22 activities of daily living (ADL)/instrumental ADL (IADL) items measured the FO score (range 1-4) at 90 days. A FO score >3 (representing a lot of difficulty with ADL/IADLs) was considered unfavorable FO. A new index was developed using machine learning techniques to select and weight conditions and prestroke impairments.
Results: Prestroke modified Rankin Scale (mRS) score, age, congestive heart failure (CHF), weight loss, diabetes, other neurologic disorders, and synergistic effects (dementia × age, CHF × renal failure, and prestroke mRS × prior stroke/TIA) were identified as important predictors in the MCC index. In the validation dataset, the index alone explained 31% of the variability in the FO score, was well-calibrated (p = 0.41), predicted unfavorable FO well (area under the receiver operating characteristic curve 0.81), and outperformed the modified Charlson Comorbidity Index in predicting the FO score and poststroke mRS.
Conclusions: A new MCC index was developed and internally validated to improve the prediction of poststroke FO. Novel predictors and synergistic interactions were identified.
Classification of evidence: This study provides Class II evidence that in patients with ischemic stroke, an index for MCC predicts FO at 90 days.
© 2020 American Academy of Neurology.