RT Journal Article
SR 00
ID 10.1177/2396987321997045
A1 Drozdowska, Bogna A.
A1 McGill, Kris
A1 McKay, Michael
A1 Bartlam, Roisin
A1 Langhorne, Peter
A1 Quinn, Terence J.
T1 Prognostic rules for predicting cognitive syndromes following stroke: a systematic review
JF European Stroke Journal
YR 2021
FD 2021-03
VO 6
IS 1
SP 18
OP 27
AB 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.
PB SAGE Publications
SN 2396-9873
LK https://eprints.gla.ac.uk/233272/