ORIGINAL RESEARCH article
Front. Stroke
Sec. Vascular Cognitive Impairment
NIH Stroke Scale and Age Predict Early Post-Stroke Cognitive Impairment
- FS
Faddi Saleh Velez 1
- CD
Cameron Dale Owens 1
- JH
Jennifer Hotson 2
- AL
Andrea Loggini 3
- AL
Ana Luyza Oliveira Santos 1
- DR
Demian Rudyk 1
- DM
Daniela Mercado 1
- MZ
Melba Zuniga-Gutierrez 1
- MC
Maria Cedeno-Bruzual 1
- LB
Laura Boada Robayo 1
- CG
Cheyenne Gutierrez 1
- KS
Kate Singleton 1
- ZS
Zyanna Stuart 1
- ES
Evgeny Sidorov 1
- AY
Andriy Yabluchanskiy 1
- CB
Camila Bonin Pinto 1
1. University of Oklahoma Health Sciences Center, Oklahoma City, United States
2. University of Michigan, Ann Arbor, United States
3. Southern Illinois Healthcare, Carbondale, United States
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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 five years. Deficits often emerge within two 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.
Summary
Keywords
age, Discharge disposition, Length of Stay, Multivariable modeling, NIH Stroke Scale, post-stroke cognitive impairment
Received
08 December 2025
Accepted
03 April 2026
Copyright
Âİ 2026 Velez, Owens, Hotson, Loggini, Oliveira Santos, Rudyk, Mercado, Zuniga-Gutierrez, Cedeno-Bruzual, Boada Robayo, Gutierrez, Singleton, Stuart, Sidorov, Yabluchanskiy and Pinto. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Camila Bonin Pinto
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