Cargando…
Prediction models for clinical outcome after a carotid revascularisation procedure: A systematic review
INTRODUCTION: Prediction models for clinical outcome after carotid artery stenting or carotid endarterectomy could aid physicians in estimating peri- and postprocedural risks in individual patients. We aimed to identify existing prediction models for short- and long-term outcome after carotid artery...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992733/ https://www.ncbi.nlm.nih.gov/pubmed/29900410 http://dx.doi.org/10.1177/2396987317739122 |
_version_ | 1783330089264480256 |
---|---|
author | Volkers, Eline J Algra, Ale Kappelle, L Jaap Greving, Jacoba P |
author_facet | Volkers, Eline J Algra, Ale Kappelle, L Jaap Greving, Jacoba P |
author_sort | Volkers, Eline J |
collection | PubMed |
description | INTRODUCTION: Prediction models for clinical outcome after carotid artery stenting or carotid endarterectomy could aid physicians in estimating peri- and postprocedural risks in individual patients. We aimed to identify existing prediction models for short- and long-term outcome after carotid artery stenting or carotid endarterectomy in patients with symptomatic or asymptomatic carotid stenosis, and to summarise their most important predictors and predictive performance. PATIENTS AND METHODS: We performed a systematic literature search for studies that developed a prediction model or risk score published until 22 December 2016. Eligible prediction models had to predict the risk of vascular events with at least one patient characteristic. RESULTS: We identified 37 studies that developed 46 prediction models. Thirty-four (74%) models were developed in carotid endarterectomy patients; 27 of these (59%) predicted short-term (in-hospital or within 30 days) risk. Most commonly predicted outcome was stroke or death (n = 12; 26%). Age (n = 31; 67%), diabetes mellitus (n = 21; 46%), heart failure (n = 16; 35%), and contralateral carotid stenosis ≥50% or occlusion (n = 16; 35%) were most commonly used as predictors. For 25 models (54%), it was unclear how missing data were handled; a complete case analysis was performed in 15 (33%) of the remaining 21 models. Twenty-eight (61%) models reported the full regression formula or risk score with risk classification. Twenty-one (46%) models were validated internally and 12 (26%) externally. Discriminative performance (c-statistic) ranged from 0.66 to 0.94 for models after carotid artery stenting and from 0.58 to 0.74 for models after carotid endarterectomy. The c-statistic ranged from 0.55 to 0.72 for the external validations. DISCUSSION: Age, diabetes mellitus, heart failure, and contralateral carotid stenosis ≥50% or occlusion were most often used as predictors in all models. Discriminative performance (c-statistic) was higher for prediction models after carotid artery stenting than after carotid endarterectomy. CONCLUSION: The clinical usefulness of most prediction models for short- or long-term outcome after carotid artery stenting or carotid endarterectomy remains unclear because of incomplete reporting, methodological limitations, and lack of external validation. |
format | Online Article Text |
id | pubmed-5992733 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-59927332018-06-11 Prediction models for clinical outcome after a carotid revascularisation procedure: A systematic review Volkers, Eline J Algra, Ale Kappelle, L Jaap Greving, Jacoba P Eur Stroke J Original Research Articles INTRODUCTION: Prediction models for clinical outcome after carotid artery stenting or carotid endarterectomy could aid physicians in estimating peri- and postprocedural risks in individual patients. We aimed to identify existing prediction models for short- and long-term outcome after carotid artery stenting or carotid endarterectomy in patients with symptomatic or asymptomatic carotid stenosis, and to summarise their most important predictors and predictive performance. PATIENTS AND METHODS: We performed a systematic literature search for studies that developed a prediction model or risk score published until 22 December 2016. Eligible prediction models had to predict the risk of vascular events with at least one patient characteristic. RESULTS: We identified 37 studies that developed 46 prediction models. Thirty-four (74%) models were developed in carotid endarterectomy patients; 27 of these (59%) predicted short-term (in-hospital or within 30 days) risk. Most commonly predicted outcome was stroke or death (n = 12; 26%). Age (n = 31; 67%), diabetes mellitus (n = 21; 46%), heart failure (n = 16; 35%), and contralateral carotid stenosis ≥50% or occlusion (n = 16; 35%) were most commonly used as predictors. For 25 models (54%), it was unclear how missing data were handled; a complete case analysis was performed in 15 (33%) of the remaining 21 models. Twenty-eight (61%) models reported the full regression formula or risk score with risk classification. Twenty-one (46%) models were validated internally and 12 (26%) externally. Discriminative performance (c-statistic) ranged from 0.66 to 0.94 for models after carotid artery stenting and from 0.58 to 0.74 for models after carotid endarterectomy. The c-statistic ranged from 0.55 to 0.72 for the external validations. DISCUSSION: Age, diabetes mellitus, heart failure, and contralateral carotid stenosis ≥50% or occlusion were most often used as predictors in all models. Discriminative performance (c-statistic) was higher for prediction models after carotid artery stenting than after carotid endarterectomy. CONCLUSION: The clinical usefulness of most prediction models for short- or long-term outcome after carotid artery stenting or carotid endarterectomy remains unclear because of incomplete reporting, methodological limitations, and lack of external validation. SAGE Publications 2017-10-24 2018-03 /pmc/articles/PMC5992733/ /pubmed/29900410 http://dx.doi.org/10.1177/2396987317739122 Text en © European Stroke Organisation 2017 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Articles Volkers, Eline J Algra, Ale Kappelle, L Jaap Greving, Jacoba P Prediction models for clinical outcome after a carotid revascularisation procedure: A systematic review |
title | Prediction models for clinical outcome after a carotid
revascularisation procedure: A systematic review |
title_full | Prediction models for clinical outcome after a carotid
revascularisation procedure: A systematic review |
title_fullStr | Prediction models for clinical outcome after a carotid
revascularisation procedure: A systematic review |
title_full_unstemmed | Prediction models for clinical outcome after a carotid
revascularisation procedure: A systematic review |
title_short | Prediction models for clinical outcome after a carotid
revascularisation procedure: A systematic review |
title_sort | prediction models for clinical outcome after a carotid
revascularisation procedure: a systematic review |
topic | Original Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992733/ https://www.ncbi.nlm.nih.gov/pubmed/29900410 http://dx.doi.org/10.1177/2396987317739122 |
work_keys_str_mv | AT volkerselinej predictionmodelsforclinicaloutcomeafteracarotidrevascularisationprocedureasystematicreview AT algraale predictionmodelsforclinicaloutcomeafteracarotidrevascularisationprocedureasystematicreview AT kappelleljaap predictionmodelsforclinicaloutcomeafteracarotidrevascularisationprocedureasystematicreview AT grevingjacobap predictionmodelsforclinicaloutcomeafteracarotidrevascularisationprocedureasystematicreview |