NIH Stroke Scale and age predict early post-stroke cognitive impairment

Introduction Acute post-stroke cognitive deficits, which may precede formal post-stroke cognitive impairment (PSCI), lacks evidence-based interventions or guidelines. Up to one-third of PSCI patients progress to dementia within 5 years. Deficits often emerge within 2 weeks, underscoring the need for early recognition of risk factors to guide prevention and management. However, predictive value of demographic, clinical, and stroke-specific factors remains inconsistent. We evaluated cognitive outcomes (Montreal Cognitive Assessment) at discharge and identified predictors of low function. Methods In this retrospective study at the University of Oklahoma Medical Center, we reviewed 964 stroke patients, with 168 meeting inclusion criteria. Early PSCI was defined as Montreal Cognitive Assessment < 26 at hospital discharge post-stroke. We calculated prevalence, performed univariable logistic regression, and developed multivariable logistic regression models with and without interaction terms. Results Patients with Montreal Cognitive Assessment < 26 were older, had longer hospital stays, higher NIH Stroke Scale, and more often discharged to non-home settings. Prevalence of early PSCI was higher with age, longer stays, non-white race, higher NIH Stroke Scale, and non-home discharge. Univariable analyses revealed length of stay, discharge disposition, NIH Stroke Scale, and race as strongest associations. Final multivariable model (NIH Stroke Scale, age, length of stay, discharge disposition) demonstrated NIH Stroke Scale and age as significant predictors, with good discrimination [Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) = 0.79]. Models including interaction terms performed similarly (ROC-AUC = 0.78). Conclusion Consistent with prior work, NIH Stroke Scale and age emerged as the most robust predictors of early PSCI. Length of stay, discharge disposition, and race were associated with early PSCI in univariable analyses and warrant further evaluation in larger prospective studies.

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Journal
Frontiers in Stroke
Published
2026-04-28
DOI
https://doi.org/10.3389/fstro.2026.1762758
Primary Topic
Acute Ischemic Stroke Management
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article
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article

NIH Stroke Scale and age predict early post-stroke cognitive impairment

Camila Bonin Pinto, Cameron D. Owens, Melba Zúniga Gutiérrez, Faddi Saleh Velez et al.
Frontiers in Stroke
Acute Ischemic Stroke Management
article

NIH Stroke Scale and age predict early post-stroke cognitive impairment

Camila Bonin Pinto, Cameron D. Owens, Melba Zúniga Gutiérrez, Faddi Saleh Velez, Andrea Loggini, Evgeny Sidorov, Andriy Yabluchanskiy, Zyanna Stuart, Cheyenne Gutierrez, Ana Luyza Oliveira Santos, Laura Boada Robayo, Demian Rudyk, Maria Cedeno-Bruzual, Daniela Mercado Pena, Jennifer Hotson, Kate Singleton
article en

Abstract

Introduction Acute post-stroke cognitive deficits, which may precede formal post-stroke cognitive impairment (PSCI), lacks evidence-based interventions or guidelines. Up to one-third of PSCI patients progress to dementia within 5 years. Deficits often emerge within 2 weeks, underscoring the need for early recognition of risk factors to guide prevention and management. However, predictive value of demographic, clinical, and stroke-specific factors remains inconsistent. We evaluated cognitive outcomes (Montreal Cognitive Assessment) at discharge and identified predictors of low function. Methods In this retrospective study at the University of Oklahoma Medical Center, we reviewed 964 stroke patients, with 168 meeting inclusion criteria. Early PSCI was defined as Montreal Cognitive Assessment < 26 at hospital discharge post-stroke. We calculated prevalence, performed univariable logistic regression, and developed multivariable logistic regression models with and without interaction terms. Results Patients with Montreal Cognitive Assessment < 26 were older, had longer hospital stays, higher NIH Stroke Scale, and more often discharged to non-home settings. Prevalence of early PSCI was higher with age, longer stays, non-white race, higher NIH Stroke Scale, and non-home discharge. Univariable analyses revealed length of stay, discharge disposition, NIH Stroke Scale, and race as strongest associations. Final multivariable model (NIH Stroke Scale, age, length of stay, discharge disposition) demonstrated NIH Stroke Scale and age as significant predictors, with good discrimination [Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) = 0.79]. Models including interaction terms performed similarly (ROC-AUC = 0.78). Conclusion Consistent with prior work, NIH Stroke Scale and age emerged as the most robust predictors of early PSCI. Length of stay, discharge disposition, and race were associated with early PSCI in univariable analyses and warrant further evaluation in larger prospective studies.

Frontiers in StrokeVol. 5
University of Michigan (US), Southern Illinois Healthcare (US), University of Oklahoma Health Sciences Center (US)
Reduced inequalities
Openalex Percentile: Top 12%
Acute Ischemic Stroke Management
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