Prognostic rules for predicting cognitive syndromes following stroke: a systematic review

Drozdowska, B. A. , McGill, K., McKay, M., Bartlam, R., Langhorne, P. and Quinn, T. J. (2021) Prognostic rules for predicting cognitive syndromes following stroke: a systematic review. European Stroke Journal, 6(1), pp. 18-27. (doi: 10.1177/2396987321997045) (PMID:33817331) (PMCID:PMC7995322)

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Purpose: Stroke survivors are at high risk of developing cognitive syndromes, such as delirium and dementia. Accurate prediction of future cognitive outcomes may aid timely diagnosis, intervention planning, and stratification in clinical trials. We aimed to identify, describe and appraise existing multivariable prognostic rules for prediction of post-stroke cognitive status. Method: We systematically searched four electronic databases from inception to November 2019 for publications describing a method to estimate individual probability of developing a cognitive syndrome following stroke. We extracted data from selected studies using a pre-specified proforma and applied the Prediction model Risk Of Bias Assessment Tool (PROBAST) for critical appraisal. Findings: Of 17,390 titles, we included 10 studies (3143 participants), presenting the development of 11 prognostic rules – 7 for post-stroke cognitive impairment and 4 for delirium. Most commonly incorporated predictors were: demographics, imaging findings, stroke type and symptom severity. Among studies assessing predictive discrimination, the area under the receiver operating characteristic (AUROC) in apparent validation ranged from 0.80 to 0.91. The overall risk of bias for each study was high. Only one prognostic rule had been externally validated. Discussion/conclusion: Research into the prognosis of cognitive outcomes following stroke is an expanding field, still at its early stages. Recommending use of specific prognostic rules is limited by the high risk of bias in all identified studies, and lack of supporting evidence from external validation. To ensure the quality of future research, investigators should adhere to current, endorsed best practice guidelines for conduct of prediction model studies.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Langhorne, Professor Peter and McGill, Dr Kris and Drozdowska, Bogna and Quinn, Dr Terry
Authors: Drozdowska, B. A., McGill, K., McKay, M., Bartlam, R., Langhorne, P., and Quinn, T. J.
College/School:College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health
Journal Name:European Stroke Journal
Publisher:SAGE Publications
ISSN (Online):2396-9881
Published Online:23 February 2021
Copyright Holders:Copyright © 2021 European Stroke Organisation
First Published:First published in European Stroke Journal 6(1): 18-27
Publisher Policy:Reproduced under a Creative Commons license

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
172806Improving assessment, prediction and understanding of the short, medium and longer term neuropsychological consequences of strokeTerence QuinnStroke Association (STROKEAS)PPA2015/01_CSOInstitute of Cardiovascular & Medical Sciences
171459Joint Stroke Association/Chief Scientist Office Senior Clinical Lectureship - STOKE ASSOCIATION REF TSA LECT 2015/05Terence QuinnStroke Association (STROKEAS)TSA LECT 2015/05,Institute of Cardiovascular & Medical Sciences