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Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis

OBJECTIVE: The objective of this study is to systematically evaluate prediction models for post-thrombectomy brain edema in acute ischemic stroke (AIS) patients. This analysis aims to equip clinicians with evidence-based guidance for the selection of appropriate prediction models, thereby facilitati...

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Autores principales: Liu, Lei, He, Chun-yu, Yang, Jia-xin, Zheng, Si-ting, Zhou, Jun, Kong, Ye, Chen, Wen-bo, Xie, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501604/
https://www.ncbi.nlm.nih.gov/pubmed/37719759
http://dx.doi.org/10.3389/fneur.2023.1254090
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author Liu, Lei
He, Chun-yu
Yang, Jia-xin
Zheng, Si-ting
Zhou, Jun
Kong, Ye
Chen, Wen-bo
Xie, Yan
author_facet Liu, Lei
He, Chun-yu
Yang, Jia-xin
Zheng, Si-ting
Zhou, Jun
Kong, Ye
Chen, Wen-bo
Xie, Yan
author_sort Liu, Lei
collection PubMed
description OBJECTIVE: The objective of this study is to systematically evaluate prediction models for post-thrombectomy brain edema in acute ischemic stroke (AIS) patients. This analysis aims to equip clinicians with evidence-based guidance for the selection of appropriate prediction models, thereby facilitating the early identification of patients at risk of developing brain edema post-surgery. METHODS: A comprehensive literature search was conducted across multiple databases, including PubMed, Web of Science, Embase, The Cochrane Library, CNKI, Wanfang, and Vip, aiming to identify studies on prediction models for post-thrombectomy brain edema in AIS patients up to January 2023. Reference lists of relevant articles were also inspected. Two reviewers independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines were employed to assess study bias and literature quality, respectively. We then used random-effects bivariate meta-analysis models to summarize the studies. RESULTS: The review included five articles, yielding 10 models. These models exhibited a relatively high risk of bias. Random effects model demonstrated that the AUC was 0.858 (95% CI 0.817–0.899). CONCLUSION: Despite the promising discriminative ability shown by studies on prediction models for post-thrombectomy brain edema in AIS patients, concerns related to a high risk of bias and limited external validation remain. Future research should prioritize the external validation and optimization of these models. There is an urgent need for large-scale, multicenter studies to develop robust, user-friendly models for real-world clinical application. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk, unique Identifier: CRD42022382790.
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spelling pubmed-105016042023-09-15 Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis Liu, Lei He, Chun-yu Yang, Jia-xin Zheng, Si-ting Zhou, Jun Kong, Ye Chen, Wen-bo Xie, Yan Front Neurol Neurology OBJECTIVE: The objective of this study is to systematically evaluate prediction models for post-thrombectomy brain edema in acute ischemic stroke (AIS) patients. This analysis aims to equip clinicians with evidence-based guidance for the selection of appropriate prediction models, thereby facilitating the early identification of patients at risk of developing brain edema post-surgery. METHODS: A comprehensive literature search was conducted across multiple databases, including PubMed, Web of Science, Embase, The Cochrane Library, CNKI, Wanfang, and Vip, aiming to identify studies on prediction models for post-thrombectomy brain edema in AIS patients up to January 2023. Reference lists of relevant articles were also inspected. Two reviewers independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines were employed to assess study bias and literature quality, respectively. We then used random-effects bivariate meta-analysis models to summarize the studies. RESULTS: The review included five articles, yielding 10 models. These models exhibited a relatively high risk of bias. Random effects model demonstrated that the AUC was 0.858 (95% CI 0.817–0.899). CONCLUSION: Despite the promising discriminative ability shown by studies on prediction models for post-thrombectomy brain edema in AIS patients, concerns related to a high risk of bias and limited external validation remain. Future research should prioritize the external validation and optimization of these models. There is an urgent need for large-scale, multicenter studies to develop robust, user-friendly models for real-world clinical application. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk, unique Identifier: CRD42022382790. Frontiers Media S.A. 2023-08-31 /pmc/articles/PMC10501604/ /pubmed/37719759 http://dx.doi.org/10.3389/fneur.2023.1254090 Text en Copyright © 2023 Liu, He, Yang, Zheng, Zhou, Kong, Chen and Xie. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
Liu, Lei
He, Chun-yu
Yang, Jia-xin
Zheng, Si-ting
Zhou, Jun
Kong, Ye
Chen, Wen-bo
Xie, Yan
Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title_full Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title_fullStr Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title_full_unstemmed Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title_short Prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
title_sort prediction models for post-thrombectomy brain edema in patients with acute ischemic stroke: a systematic review and meta-analysis
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10501604/
https://www.ncbi.nlm.nih.gov/pubmed/37719759
http://dx.doi.org/10.3389/fneur.2023.1254090
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