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Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study

BACKGROUND: Little is known about the risk factors for sudden cardiac death (SCD) in the overall hospitalized cardiac department population. This study was conducted to investigate the risk factors and develop a predictive model for SCD in a hospitalized cardiac department population. METHODS: We co...

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Autores principales: Shang, Lu-Xiang, Zhou, Xian-Hui, Zhang, Jiang-Hua, Zhang, Wen-Hui, TuEr-Hong, ZuKe-La, Zhao, Yang, Lyu, Wen-Kui, Li, Yao-Dong, Tang, Bao-Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629305/
https://www.ncbi.nlm.nih.gov/pubmed/30628955
http://dx.doi.org/10.1097/CM9.0000000000000010
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author Shang, Lu-Xiang
Zhou, Xian-Hui
Zhang, Jiang-Hua
Zhang, Wen-Hui
TuEr-Hong, ZuKe-La
Zhao, Yang
Lyu, Wen-Kui
Li, Yao-Dong
Tang, Bao-Peng
author_facet Shang, Lu-Xiang
Zhou, Xian-Hui
Zhang, Jiang-Hua
Zhang, Wen-Hui
TuEr-Hong, ZuKe-La
Zhao, Yang
Lyu, Wen-Kui
Li, Yao-Dong
Tang, Bao-Peng
author_sort Shang, Lu-Xiang
collection PubMed
description BACKGROUND: Little is known about the risk factors for sudden cardiac death (SCD) in the overall hospitalized cardiac department population. This study was conducted to investigate the risk factors and develop a predictive model for SCD in a hospitalized cardiac department population. METHODS: We conducted a retrospective study of patients admitted to the cardiac department of the First Affiliated Hospital of Xinjiang Medical University from June 2015 to February 2017. We collected the clinical data from medical records. Multiple stepwise logistic regression analysis was carried out to confirm the risk factors for SCD and develop a predictive risk model. The risk score was assessed by the area under receiver operating characteristic (AUROC) curve and the Hosmer-Lemeshow goodness-of-fit test. RESULTS: A total of 262 patients with SCD and 4485 controls were enrolled in our study. Logistic regression modeling identified eight significant risk factors for in-hospital SCD: age, main admitting diagnosis, diabetes, corrected QT interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate. A predictive risk score including these variables showed an AUROC curve of 0.774 (95% confidence interval: 0.744–0.805). The Hosmer-Lemeshow goodness-of-fit test showed the chi-square value was 2.527 (P = 0.640). The incidence of in-hospital SCD was 1.3%, 4.1%, and 18.6% for scores of 0 to 2, 3 to 5 and ≥6, respectively (P < 0.001). CONCLUSIONS: Age, main admitting diagnosis, diabetes, QTc interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate are factors related to in-hospital SCD in a hospitalized cardiac department population. We developed a predictive risk score including these factors that could identify patients who are predisposed to in-hospital SCD.
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spelling pubmed-66293052019-07-22 Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study Shang, Lu-Xiang Zhou, Xian-Hui Zhang, Jiang-Hua Zhang, Wen-Hui TuEr-Hong, ZuKe-La Zhao, Yang Lyu, Wen-Kui Li, Yao-Dong Tang, Bao-Peng Chin Med J (Engl) Original Articles BACKGROUND: Little is known about the risk factors for sudden cardiac death (SCD) in the overall hospitalized cardiac department population. This study was conducted to investigate the risk factors and develop a predictive model for SCD in a hospitalized cardiac department population. METHODS: We conducted a retrospective study of patients admitted to the cardiac department of the First Affiliated Hospital of Xinjiang Medical University from June 2015 to February 2017. We collected the clinical data from medical records. Multiple stepwise logistic regression analysis was carried out to confirm the risk factors for SCD and develop a predictive risk model. The risk score was assessed by the area under receiver operating characteristic (AUROC) curve and the Hosmer-Lemeshow goodness-of-fit test. RESULTS: A total of 262 patients with SCD and 4485 controls were enrolled in our study. Logistic regression modeling identified eight significant risk factors for in-hospital SCD: age, main admitting diagnosis, diabetes, corrected QT interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate. A predictive risk score including these variables showed an AUROC curve of 0.774 (95% confidence interval: 0.744–0.805). The Hosmer-Lemeshow goodness-of-fit test showed the chi-square value was 2.527 (P = 0.640). The incidence of in-hospital SCD was 1.3%, 4.1%, and 18.6% for scores of 0 to 2, 3 to 5 and ≥6, respectively (P < 0.001). CONCLUSIONS: Age, main admitting diagnosis, diabetes, QTc interval, QRS duration, ventricular premature beat burden, left ventricular ejection fraction, and estimated glomerular filtration rate are factors related to in-hospital SCD in a hospitalized cardiac department population. We developed a predictive risk score including these factors that could identify patients who are predisposed to in-hospital SCD. Wolters Kluwer Health 2019-01-05 2019-01-05 /pmc/articles/PMC6629305/ /pubmed/30628955 http://dx.doi.org/10.1097/CM9.0000000000000010 Text en Copyright © 2018 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle Original Articles
Shang, Lu-Xiang
Zhou, Xian-Hui
Zhang, Jiang-Hua
Zhang, Wen-Hui
TuEr-Hong, ZuKe-La
Zhao, Yang
Lyu, Wen-Kui
Li, Yao-Dong
Tang, Bao-Peng
Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title_full Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title_fullStr Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title_full_unstemmed Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title_short Establishment of a predictive model for inpatient sudden cardiac death in a Chinese cardiac department population: a retrospective study
title_sort establishment of a predictive model for inpatient sudden cardiac death in a chinese cardiac department population: a retrospective study
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6629305/
https://www.ncbi.nlm.nih.gov/pubmed/30628955
http://dx.doi.org/10.1097/CM9.0000000000000010
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