Development and Application of a Risk Prediction Model for In-Hospital Stroke After Transcatheter Aortic Valve Replacement: A Report From The Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry.
Aged
Aged, 80 and over
Aortic Valve Stenosis
/ diagnostic imaging
Female
Hospital Mortality
Humans
Male
Predictive Value of Tests
Prevalence
Registries
Reproducibility of Results
Risk Assessment
Risk Management
Societies, Medical
Stroke
/ epidemiology
Thoracic Surgery
Transcatheter Aortic Valve Replacement
/ adverse effects
United States
Journal
The Annals of thoracic surgery
ISSN: 1552-6259
Titre abrégé: Ann Thorac Surg
Pays: Netherlands
ID NLM: 15030100R
Informations de publication
Date de publication:
04 2019
04 2019
Historique:
received:
05
02
2018
revised:
30
09
2018
accepted:
01
11
2018
pubmed:
12
12
2018
medline:
19
12
2019
entrez:
12
12
2018
Statut:
ppublish
Résumé
Stroke is a serious complication after transcatheter aortic valve replacement (TAVR), yet predictive models are not available. A new risk model for in-hospital stroke after TAVR was developed and used to estimate site-specific performance. We included 97,600 TAVR procedures from 521 sites in The Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry from July 2014 to June 2017. Association between baseline covariates and in-hospital stroke was estimated by logistic regression. Discrimination was evaluated by C-statistic. Calibration was tested internally via cross-validation. Hierarchical modeling was used to estimate risk-adjusted site-specific performance. Median age was 82 years, 44,926 (46.0%) were women, and 1,839 (1.9%) had in-hospital stroke. Covariates associated with stroke (odds ratio) included transapical access (1.44), access excluding transapical and transfemoral (1.77), prior stroke (1.57), prior transient ischemic attack (1.50), preprocedural shock, inotropes or mechanical assist device (1.48), smoking (1.28), porcelain aorta (1.23), peripheral arterial disease (1.21), age per 5 years (1.11), glomerular filtration rate per 5 mL/min (0.97), body surface area per m A risk model for in-hospital stroke after TAVR was developed from The Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry and used to estimate site-specific stroke performance. This model can serve as a valuable resource for quality improvement, clinical decision making, and patient counseling.
Sections du résumé
BACKGROUND
Stroke is a serious complication after transcatheter aortic valve replacement (TAVR), yet predictive models are not available. A new risk model for in-hospital stroke after TAVR was developed and used to estimate site-specific performance.
METHODS
We included 97,600 TAVR procedures from 521 sites in The Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry from July 2014 to June 2017. Association between baseline covariates and in-hospital stroke was estimated by logistic regression. Discrimination was evaluated by C-statistic. Calibration was tested internally via cross-validation. Hierarchical modeling was used to estimate risk-adjusted site-specific performance.
RESULTS
Median age was 82 years, 44,926 (46.0%) were women, and 1,839 (1.9%) had in-hospital stroke. Covariates associated with stroke (odds ratio) included transapical access (1.44), access excluding transapical and transfemoral (1.77), prior stroke (1.57), prior transient ischemic attack (1.50), preprocedural shock, inotropes or mechanical assist device (1.48), smoking (1.28), porcelain aorta (1.23), peripheral arterial disease (1.21), age per 5 years (1.11), glomerular filtration rate per 5 mL/min (0.97), body surface area per m
CONCLUSIONS
A risk model for in-hospital stroke after TAVR was developed from The Society of Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy Registry and used to estimate site-specific stroke performance. This model can serve as a valuable resource for quality improvement, clinical decision making, and patient counseling.
Identifiants
pubmed: 30529671
pii: S0003-4975(18)31795-8
doi: 10.1016/j.athoracsur.2018.11.013
pmc: PMC6726434
mid: NIHMS1046849
pii:
doi:
Types de publication
Journal Article
Multicenter Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
1097-1103Subventions
Organisme : NHLBI NIH HHS
ID : K23 HL116799
Pays : United States
Informations de copyright
Copyright © 2019 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.
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