Katalog Plus
Bibliothek der Frankfurt UAS
Bald neuer Katalog: sichern Sie sich schon vorab Ihre persönlichen Merklisten im Nutzerkonto: Anleitung.
Dieses Ergebnis aus BASE kann Gästen nicht angezeigt werden.  Login für vollen Zugriff.

Development of a Prognostic Model for Poststroke Dementia Using Multiple International Cohorts

Title: Development of a Prognostic Model for Poststroke Dementia Using Multiple International Cohorts
Authors: Lo, Jessica W.; Crawford, John D.; Desmond, David W.; Godefroy, Olivier; Roussel, Martine; Bordet, Regis; Dondaine, Thibaut; Mendyk, Anne-Marie; Bae, Hee-Joon; Lim, Jae-Sung; Ojagbemi, Akin; Bello, Toyin; Chen, Christopher P. L. H.; Chong, Eddie J.; Venketasubramanian, Narayanaswamy; Klimkowicz-Mrowiec, Aleksandra; Traykov, Latchezar; Mehrabian, Shima; Chung, Chih-Ping; Chi, Nai-Fang; Lau, Gary Kui Kai; Liu, Dillys Xiaodi; Welberry, Heidi; Brodaty, Henry; Sachdev, Perminder S.
Contributors: Bae, Hee-Joon
Publisher Information: Lippincott Williams & Wilkins Ltd.
Publication Year: 2026
Collection: Seoul National University: S-Space
Subject Terms: VASCULAR COGNITIVE IMPAIRMENT; PREDICTION MODELS; MILD STROKE; VALIDATION; PROFILE
Description: Background and ObjectivesDementia risk prediction models developed for the general population perform poorly in stroke cohorts. Existing stroke-specific models are few and limited by short prediction horizons or reliance on neuroimaging. The aim of this study was to develop a clinically practical model for predicting 5-year dementia risk after stroke using commonly available variables and individual participant data from the Stroke and Cognition Consortium (STROKOG).MethodsData were pooled from 12 studies across 10 countries. Dementia was diagnosed mainly by expert panel consensus and algorithmic classification. Fine-Gray subdistribution hazard models estimated dementia probability, accounting for death as a competing event. Candidate predictors included routinely collected baseline clinical and stroke-related variables, selected through backward stepwise elimination. Model performance was evaluated using discrimination (C-index) and calibration for prediction up to 5 years after stroke. Internal-external cross-validation (IECV) assessed generalizability across studies, regions, and study periods.ResultsA total of 2,663 participants (mean age 67.0 years [SD 11.1]; 40% female) were followed for a median of 2.0 years (IQR 1.0-5.0), during which 655 developed dementia (8.7 per 100 person-years). The final model included age, sex, education, history of previous stroke, diabetes, stroke severity, 2 interactions (age x sex; age x stroke severity), and study-level variables including national current health expenditure. An Excel-based risk calculator is available in the Supplement (eAppendix 1). The model demonstrated strong discrimination (C-index: 0.81; 95% CI 0.75-0.87) and excellent calibration in the full data set used for development. In IECV, discrimination was acceptable across individual studies (pooled C-index: 0.70 [0.67-0.73]) and higher in recent (post-2010; 0.79 [0.76-0.82]) and European (0.74 [0.71-0.78]) cohorts. Risks were slightly overestimated in Asian cohorts. Case numbers were too small for ...
Document Type: article in journal/newspaper
Language: unknown
Relation: Neurology, Vol.106 No.3, p. e214574; https://hdl.handle.net/10371/231035; 001661301300001; 249716
DOI: 10.1212/WNL.0000000000214574
Availability: https://hdl.handle.net/10371/231035; https://doi.org/10.1212/WNL.0000000000214574
Accession Number: edsbas.6B4640A2
Database: BASE