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Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis
BACKGROUND: Prognostic tools for intracerebral hemorrhage (ICH) patients are potentially useful for ascertaining prognosis and recommended in guidelines to facilitate streamline assessment and communication between providers. In this systematic review with meta-analysis we identified and characteriz...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247734/ https://www.ncbi.nlm.nih.gov/pubmed/30458727 http://dx.doi.org/10.1186/s12874-018-0613-8 |
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author | Gregório, Tiago Pipa, Sara Cavaleiro, Pedro Atanásio, Gabriel Albuquerque, Inês Chaves, Paulo Castro Azevedo, Luís |
author_facet | Gregório, Tiago Pipa, Sara Cavaleiro, Pedro Atanásio, Gabriel Albuquerque, Inês Chaves, Paulo Castro Azevedo, Luís |
author_sort | Gregório, Tiago |
collection | PubMed |
description | BACKGROUND: Prognostic tools for intracerebral hemorrhage (ICH) patients are potentially useful for ascertaining prognosis and recommended in guidelines to facilitate streamline assessment and communication between providers. In this systematic review with meta-analysis we identified and characterized all existing prognostic tools for this population, performed a methodological evaluation of the conducting and reporting of such studies and compared different methods of prognostic tool derivation in terms of discrimination for mortality and functional outcome prediction. METHODS: PubMed, ISI, Scopus and CENTRAL were searched up to 15th September 2016, with additional studies identified using reference check. Two reviewers independently extracted data regarding the population studied, process of tool derivation, included predictors and discrimination (c statistic) using a predesignated spreadsheet based in the CHARMS checklist. Disagreements were solved by consensus. C statistics were pooled using robust variance estimation and meta-regression was applied for group comparisons using random effect models. RESULTS: Fifty nine studies were retrieved, including 48,133 patients and reporting on the derivation of 72 prognostic tools. Data on discrimination (c statistic) was available for 53 tools, 38 focusing on mortality and 15 focusing on functional outcome. Discrimination was high for both outcomes, with a pooled c statistic of 0.88 for mortality and 0.87 for functional outcome. Forty three tools were regression based and nine tools were derived using machine learning algorithms, with no differences found between the two methods in terms of discrimination (p = 0.490). Several methodological issues however were identified, relating to handling of missing data, low number of events per variable, insufficient length of follow-up, absence of blinding, infrequent use of internal validation, and underreporting of important model performance measures. CONCLUSIONS: Prognostic tools for ICH discriminated well for mortality and functional outcome in derivation studies but methodological issues require confirmation of these findings in validation studies. Logistic regression based risk scores are particularly promising given their good performance and ease of application. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-018-0613-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6247734 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-62477342018-11-26 Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis Gregório, Tiago Pipa, Sara Cavaleiro, Pedro Atanásio, Gabriel Albuquerque, Inês Chaves, Paulo Castro Azevedo, Luís BMC Med Res Methodol Research Article BACKGROUND: Prognostic tools for intracerebral hemorrhage (ICH) patients are potentially useful for ascertaining prognosis and recommended in guidelines to facilitate streamline assessment and communication between providers. In this systematic review with meta-analysis we identified and characterized all existing prognostic tools for this population, performed a methodological evaluation of the conducting and reporting of such studies and compared different methods of prognostic tool derivation in terms of discrimination for mortality and functional outcome prediction. METHODS: PubMed, ISI, Scopus and CENTRAL were searched up to 15th September 2016, with additional studies identified using reference check. Two reviewers independently extracted data regarding the population studied, process of tool derivation, included predictors and discrimination (c statistic) using a predesignated spreadsheet based in the CHARMS checklist. Disagreements were solved by consensus. C statistics were pooled using robust variance estimation and meta-regression was applied for group comparisons using random effect models. RESULTS: Fifty nine studies were retrieved, including 48,133 patients and reporting on the derivation of 72 prognostic tools. Data on discrimination (c statistic) was available for 53 tools, 38 focusing on mortality and 15 focusing on functional outcome. Discrimination was high for both outcomes, with a pooled c statistic of 0.88 for mortality and 0.87 for functional outcome. Forty three tools were regression based and nine tools were derived using machine learning algorithms, with no differences found between the two methods in terms of discrimination (p = 0.490). Several methodological issues however were identified, relating to handling of missing data, low number of events per variable, insufficient length of follow-up, absence of blinding, infrequent use of internal validation, and underreporting of important model performance measures. CONCLUSIONS: Prognostic tools for ICH discriminated well for mortality and functional outcome in derivation studies but methodological issues require confirmation of these findings in validation studies. Logistic regression based risk scores are particularly promising given their good performance and ease of application. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12874-018-0613-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-11-20 /pmc/articles/PMC6247734/ /pubmed/30458727 http://dx.doi.org/10.1186/s12874-018-0613-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Gregório, Tiago Pipa, Sara Cavaleiro, Pedro Atanásio, Gabriel Albuquerque, Inês Chaves, Paulo Castro Azevedo, Luís Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title | Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title_full | Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title_fullStr | Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title_full_unstemmed | Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title_short | Prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
title_sort | prognostic models for intracerebral hemorrhage: systematic review and meta-analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247734/ https://www.ncbi.nlm.nih.gov/pubmed/30458727 http://dx.doi.org/10.1186/s12874-018-0613-8 |
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