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Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review.

Authors :
Abdulaziz KE
Perry JJ
Yadav K
Dowlatshahi D
Stiell IG
Wells GA
Taljaard M
Source :
Diagnostic and prognostic research [Diagn Progn Res] 2022 May 19; Vol. 6 (1), pp. 9. Date of Electronic Publication: 2022 May 19.
Publication Year :
2022

Abstract

Background: Clinical prediction models/scores help clinicians make optimal evidence-based decisions when caring for their patients. To critically appraise such prediction models for use in a clinical setting, essential information on the derivation and validation of the models needs to be transparently reported. In this systematic review, we assessed the quality of reporting of derivation and validation studies of prediction models for the prognosis of recurrent stroke in patients with transient ischemic attack or minor stroke.<br />Methods: MEDLINE and EMBASE databases were searched up to February 04, 2020. Studies reporting development or validation of multivariable prognostic models predicting recurrent stroke within 90 days in patients with TIA or minor stroke were included. Included studies were appraised for reporting quality and conduct using a select list of items from the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) Statement.<br />Results: After screening 7026 articles, 60 eligible articles were retained, consisting of 100 derivation and validation studies of 27 unique prediction models. Four models were newly derived while 23 were developed by validating and updating existing models. Of the 60 articles, 15 (25%) reported an informative title. Among the 100 derivation and validation studies, few reported whether assessment of the outcome (24%) and predictors (12%) was blinded. Similarly, sample size justifications (49%), description of methods for handling missing data (16.1%), and model calibration (5%) were seldom reported. Among the 96 validation studies, 17 (17.7%) clearly reported on similarity (in terms of setting, eligibility criteria, predictors, and outcomes) between the validation and the derivation datasets. Items with the highest prevalence of adherence were the source of data (99%), eligibility criteria (93%), measures of discrimination (81%) and study setting (65%).<br />Conclusions: The majority of derivation and validation studies for the prognosis of recurrent stroke in TIA and minor stroke patients suffer from poor reporting quality. We recommend that all prediction model derivation and validation studies follow the TRIPOD statement to improve transparency and promote uptake of more reliable prediction models in practice.<br />Trial Registration: The protocol for this review was registered with PROSPERO (Registration number CRD42020201130 ).<br /> (© 2022. The Author(s).)

Details

Language :
English
ISSN :
2397-7523
Volume :
6
Issue :
1
Database :
MEDLINE
Journal :
Diagnostic and prognostic research
Publication Type :
Academic Journal
Accession number :
35585563
Full Text :
https://doi.org/10.1186/s41512-022-00123-z