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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

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 transparen...

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Autores principales: Abdulaziz, Kasim E., Perry, Jeffrey J., Yadav, Krishan, Dowlatshahi, Dar, Stiell, Ian G., Wells, George A., Taljaard, Monica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118704/
https://www.ncbi.nlm.nih.gov/pubmed/35585563
http://dx.doi.org/10.1186/s41512-022-00123-z
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author Abdulaziz, Kasim E.
Perry, Jeffrey J.
Yadav, Krishan
Dowlatshahi, Dar
Stiell, Ian G.
Wells, George A.
Taljaard, Monica
author_facet Abdulaziz, Kasim E.
Perry, Jeffrey J.
Yadav, Krishan
Dowlatshahi, Dar
Stiell, Ian G.
Wells, George A.
Taljaard, Monica
author_sort Abdulaziz, Kasim E.
collection PubMed
description 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. 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. 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%). 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. TRIAL REGISTRATION: The protocol for this review was registered with PROSPERO (Registration number CRD42020201130). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41512-022-00123-z.
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spelling pubmed-91187042022-05-20 Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review Abdulaziz, Kasim E. Perry, Jeffrey J. Yadav, Krishan Dowlatshahi, Dar Stiell, Ian G. Wells, George A. Taljaard, Monica Diagn Progn Res Review 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. 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. 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%). 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. TRIAL REGISTRATION: The protocol for this review was registered with PROSPERO (Registration number CRD42020201130). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s41512-022-00123-z. BioMed Central 2022-05-19 /pmc/articles/PMC9118704/ /pubmed/35585563 http://dx.doi.org/10.1186/s41512-022-00123-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review
Abdulaziz, Kasim E.
Perry, Jeffrey J.
Yadav, Krishan
Dowlatshahi, Dar
Stiell, Ian G.
Wells, George A.
Taljaard, Monica
Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title_full Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title_fullStr Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title_full_unstemmed Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title_short Quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with TIA and minor stroke: a systematic review
title_sort quality and transparency of reporting derivation and validation prognostic studies of recurrent stroke in patients with tia and minor stroke: a systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118704/
https://www.ncbi.nlm.nih.gov/pubmed/35585563
http://dx.doi.org/10.1186/s41512-022-00123-z
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