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Published on: December 16, 2022
NIH Stroke Scale and age predict early post-stroke cognitive impairment.
Faddi Saleh Velez1,2, Cameron D Owens1,2, Jennifer Hotson3
1Brain Stimulation and Neurorehabilitation Laboratory, Department of Neurology and Department of Neurosurgery, University of Oklahoma Health Sciences, Oklahoma City, OK, United States.
Frontiers in Stroke
|May 14, 2026
Summary
Acute post-stroke cognitive impairment (PSCI) affects many patients, with age and NIH Stroke Scale being key predictors. Early identification of these factors is crucial for managing cognitive deficits after stroke.
Area of Science:
- Neurology
- Cognitive Science
- Public Health
Background:
- Acute post-stroke cognitive deficits lack evidence-based interventions.
- Up to one-third of patients with post-stroke cognitive impairment (PSCI) may progress to dementia within five years.
- Early recognition of risk factors is crucial for prevention and management of PSCI.
Purpose of the Study:
- To evaluate cognitive outcomes at hospital discharge after stroke.
- To identify predictors of low cognitive function in early post-stroke patients.
Main Methods:
- Retrospective study of 168 stroke patients at the University of Oklahoma Medical Center.
- Early PSCI defined as Montreal Cognitive Assessment (MoCA) < 26 at discharge.
- Univariable and multivariable logistic regression models were used to identify predictors.
Main Results:
- Prevalence of early PSCI was associated with older age, longer hospital stays, higher NIH Stroke Scale scores, and non-home discharge.
- The NIH Stroke Scale and age were significant predictors of early PSCI (ROC-AUC = 0.79).
- Length of stay, discharge disposition, and race showed associations in univariable analyses.
Conclusions:
- NIH Stroke Scale and age are robust predictors of early PSCI.
- Further prospective studies are needed to evaluate the role of length of stay, discharge disposition, and race.
- Early identification of PSCI predictors can guide future interventions.
