NIH Stroke Scale and Age Predict Early Post-Stroke Cognitive Impairment

A retrospective study at the University of Oklahoma Medical Center reviewed 964 stroke patients, with 168 meeting inclusion criteria. The dataset likely contains patient-level data used to evaluate predictors of early post-stroke cognitive impairment, defined by a Montreal Cognitive Assessment score below 26 at discharge. The author is Faddi Saleh Velez, and the data was last updated on 2026-04-28.

Use Cases

• Predicting early post-stroke cognitive impairment based on NIH Stroke Scale scores and patient age.
• Analyzing the association between hospital length of stay and cognitive outcomes post-stroke.
• Investigating the relationship between discharge disposition and risk of cognitive impairment.
• Building logistic regression models to identify key clinical predictors of post-stroke cognitive function.

Strengths

• The dataset is derived from a study of 964 stroke patients, providing a substantial clinical cohort.
• The final predictive model demonstrated good discrimination with a Receiver Operating Characteristic-Area Under the Curve of 0.79.
• The analysis includes both univariable and multivariable logistic regression models, offering a detailed methodological approach.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The data is from a single medical center, which may limit generalizability.

Provenance

Source

University of Oklahoma Medical Center

Collection Method

Retrospective chart review of stroke patients.

Freshness

Last updated 2026-04-28 04:29:15; freshness should be verified.

Geography

Oklahoma, United States