A systematic review of case-mix adjustment models for stroke

Abstract

Objective:

To identify any externally validated prognostic model for predicting outcome in unselected populations following acute stroke comprising variables feasible for collection in routine care.

Data sources:

Searches were run in MEDLINE, EMBASE, CINAHL, PsycInfo, AMED and ISI Web of Science with no limits on publication date or language.

Review methods:

Any study describing the development or external validation of a discernible prognostic model to predict any valid outcome following acute stroke was included. Papers were retained if they met pre-specified inclusion criteria identified from previous reviews and pertinent discussion papers. Data extraction focused on methodological quality of model development, generalizability and feasibility of variable collection. Model performance was examined through consideration of external validation studies.

Results:

Seventeen externally validated models were identified from 43 papers fulfilling inclusion criteria. Quality of studies describing model development was variable and model performance in external validation studies was generally poor. Models were generally constructed through secondary use of randomized trial or stroke database data. Prognostic variables broadly encompassed markers of stroke severity, pre-stroke function and comorbidities. One model that fulfilled the review criteria and had extensive external validation in a range of post-stroke populations was identified (the Six Simple Variables model).

Conclusion:

The Six Simple Variables model performed well in six external validation studies, although prediction of outcome in patients with milder strokes was less reliable. Other models identified in this review have been developed using robust methodology but comprise more complex clinical variables which may limit their utility in routine stroke care.