Improvement in Cardiovascular Risk Prediction with Electronic Health Records

被引:33
作者
Pike, Mindy M. [1 ]
Decker, Paul A. [1 ]
Larson, Nicholas B. [1 ]
St Sauver, Jennifer L. [1 ,2 ]
Takahashi, Paul Y. [3 ]
Roger, Veronique L. [1 ,4 ]
Rocca, Walter A. [1 ,5 ]
Miller, Virginia M. [6 ,7 ]
Olson, Janet E. [1 ]
Pathak, Jyotishman [8 ]
Bielinski, Suzette J. [1 ]
机构
[1] Mayo Clin, Dept Hlth Sci Res, 200 First St SW, Rochester, MN 55905 USA
[2] Mayo Clin, Robert D & Patricia E Kern Ctr Sci Hlth Care Deli, Rochester, MN 55905 USA
[3] Mayo Clin, Dept Med, Rochester, MN 55905 USA
[4] Mayo Clin, Dept Internal Med, Div Cardiovasc Dis, Rochester, MN 55905 USA
[5] Mayo Clin, Dept Neurol, Rochester, MN 55905 USA
[6] Mayo Clin, Dept Surg, Rochester, MN 55905 USA
[7] Mayo Clin, Dept Physiol & Biomed Engn, Rochester, MN 55905 USA
[8] Weill Cornell Med Coll, Dept Healthcare Policy & Res, New York, NY USA
基金
美国国家卫生研究院;
关键词
Cardiovascular; QRISK; Framingham risk score; ASCVD; Biobank; VALIDATION; DISEASE; DERIVATION; QRISK; COHORT; SCORE;
D O I
10.1007/s12265-016-9687-z
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen's kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification.
引用
收藏
页码:214 / 222
页数:9
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