External validation of a percutaneous coronary intervention mortality prediction model in patients with acute coronary syndromes

被引:9
作者
Hubacek, J
Galbraith, PD
Gao, M
Humphries, K
Graham, MM
Knudtson, ML
Ghali, WA
机构
[1] Univ Calgary, Fac Med, Dept Med, Calgary, AB T2N 4N1, Canada
[2] APPROACH, Calgary, AB, Canada
[3] APPROACH, Edmonton, AB, Canada
[4] Univ Alberta, Dept Med, Edmonton, AB T6G 2M7, Canada
[5] British Columbia Cardiac Registries, Vancouver, BC, Canada
[6] Univ British Columbia, Dept Med, Vancouver, BC V5Z 1M9, Canada
基金
加拿大健康研究院;
关键词
D O I
10.1016/j.ahj.2005.04.032
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background The recently published Michigan outcome prediction model (MM) for inhospital mortality was developed and validated on a series of consecutive patients undergoing percutaneous coronary intervention (PCI). Our purpose was to externally validate the performance of the MM in 2 separate cohorts of patients with acute coronary syndrome (ACS) undergoing PCI in Canada. Methods A validation of the MM and development of an extended MM were performed on data describing 10050 patients from the APPROACH prospective cohort study between January 1995 and December 2000. Performance of both models was assessed on an external data set of 3259 PCI cases from the British Columbia Cardiac Registries. Only patients with a diagnosis of ACS were included in the study. Results The original MM predicted death rates ranging from 0.1% to 60.6%, but lacked accuracy to predict inhospital mortality as severity increased. The extended MM predicted death rates more widely from 0.0% to a high of 91.0% with better accuracy to predict inhospital death in patients with ACS undergoing PCI. The areas under the receiver operating characteristic curve for the MM and the extended MM on the external validation data set were 0.93. and 0.95, respectively. Conclusion The MM predicts death after PCI in patients with ACS and identifies a clear gradient of risk. However, the enhanced MM developed specifically for the subset of patients with ACS demonstrated better prediction and cross-validated performance. These prediction rules can be useful for risk-adjustment analyses and for prognostication for individual patients.
引用
收藏
页码:308 / 315
页数:8
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