Literature DB >> 28818316

Predicting In-Hospital Mortality in Patients With Acute Coronary Syndrome in China.

Yong Peng1, Xin Du2, Kris D Rogers3, Yangfeng Wu4, Runlin Gao5, Anushka Patel6.   

Abstract

Currently available risk scores (RSs) were derived from populations with very few participants from China. We aimed to develop an RS based on data from patients with acute coronary syndrome in China and to compare its performance with the commonly promoted Global Registry of Acute Coronary Events (GRACE) RS. Clinical Pathways for Acute Coronary Syndromes-Phase 2 was a trial of a quality improvement intervention in China. Patients recruited from 75 hospitals from October 2007 to August 2010 were divided into training and validation sets based on immediate or delayed implementation. A Clinical Pathways for Acute Coronary Syndromes (CPACS) RS for in-hospital mortality was developed separately by gender, using the training set (6,790 patients). Discrimination and calibration of the CPACS RS and GRACE RS were compared on the validation set (3,801 patients). Although discrimination of the GRACE RS was acceptable, this was improved with the CPACS RS (c-statistic 0.82 vs 0.87, p = 0.012 for men; c-statistic 0.78 vs 0.85, p = 0.006 for women). The absolute bias was significantly lower with CPACS RS for both genders (7.6% vs 97.5% in men and 21.5% vs 77.2% in women), compared with the GRACE RS, which systematically overestimated risk. The CPACS RS underestimated risk in women, but only in those already above threshold levels currently used to define a clinical high-risk population. In conclusion, the GRACE RS substantially overestimates the risk of in-hospital death in patients presenting to the hospital with a suspected acute coronary syndrome in China. We have developed and independently validated a new RS utilizing data from Chinese patients.
Copyright © 2017 Elsevier Inc. All rights reserved.

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Year:  2017        PMID: 28818316     DOI: 10.1016/j.amjcard.2017.06.044

Source DB:  PubMed          Journal:  Am J Cardiol        ISSN: 0002-9149            Impact factor:   2.778


  5 in total

1.  In-hospital risk stratification algorithm of Asian elderly patients.

Authors:  Sazzli Kasim; Sorayya Malek; Song Cheen; Muhammad Shahreeza Safiruz; Wan Azman Wan Ahmad; Khairul Shafiq Ibrahim; Firdaus Aziz; Kazuaki Negishi; Nurulain Ibrahim
Journal:  Sci Rep       Date:  2022-10-20       Impact factor: 4.996

2.  A LASSO-derived risk model for long-term mortality in Chinese patients with acute coronary syndrome.

Authors:  Yi-Ming Li; Zhuo-Lun Li; Fei Chen; Qi Liu; Yong Peng; Mao Chen
Journal:  J Transl Med       Date:  2020-04-06       Impact factor: 5.531

3.  Relationship between Braden Scale scores and acute kidney injury among patients with acute coronary syndrome: a multicentre retrospective cohort study.

Authors:  Zhichao Li; Bofu Liu; Dongze Li; Yu Jia; Lei Ye; Xiaoyang Liao; Zhi Zeng; Zhi Wan
Journal:  BMJ Open       Date:  2022-01-05       Impact factor: 2.692

4.  Readily accessible risk model to predict in-hospital major adverse cardiac events in patients with acute myocardial infarction: a retrospective study of Chinese patients.

Authors:  Xiaoxia Hou; Xin Du; Guohong Wang; Xiaoyan Zhao; Yang Zheng; Yingxue Li; Eryu Xia; Yong Qin; Jianzeng Dong; Chang-Sheng Ma
Journal:  BMJ Open       Date:  2021-07-01       Impact factor: 2.692

5.  Short- and long-term mortality prediction after an acute ST-elevation myocardial infarction (STEMI) in Asians: A machine learning approach.

Authors:  Firdaus Aziz; Sorayya Malek; Khairul Shafiq Ibrahim; Raja Ezman Raja Shariff; Wan Azman Wan Ahmad; Rosli Mohd Ali; Kien Ting Liu; Gunavathy Selvaraj; Sazzli Kasim
Journal:  PLoS One       Date:  2021-08-02       Impact factor: 3.240

  5 in total

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