Comprehensive Peroxidase-Based Hematologic Profiling for the Prediction of 1-Year Myocardial Infarction and Death

Author:

Brennan Marie-Luise1,Reddy Anupama1,Tang W. H. Wilson1,Wu Yuping1,Brennan Danielle M.1,Hsu Amy1,Mann Shirley A.1,Hammer Peter L.1,Hazen Stanley L.1

Affiliation:

1. From the Department of Cell Biology (M.-L.B., S.A.M., S.L.H.), Center for Cardiovascular Diagnostics and Prevention (M.-L.B., A.R., W.H.W.T., S.A.M., S.L.H.), and Department of Cardiovascular Medicine (W.H.W.T., D.M.B., A.H., S.L.H.), Cleveland Clinic, Cleveland, Ohio; Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio (M.-L.B., W.H.W.T., S.L.H.); Rutgers Center for Operations Research, Rutgers University, Piscataway, NJ (A.R., P.L.H.); and Department of...

Abstract

Background— Recognition of biological patterns holds promise for improved identification of patients at risk for myocardial infarction (MI) and death. We hypothesized that identifying high- and low-risk patterns from a broad spectrum of hematologic phenotypic data related to leukocyte peroxidase-, erythrocyte- and platelet-related parameters may better predict future cardiovascular risk in stable cardiac patients than traditional risk factors alone. Methods and Results— Stable patients (n=7369) undergoing elective cardiac evaluation at a tertiary care center were enrolled. A model (PEROX) that predicts incident 1-year death and MI was derived from standard clinical data combined with information captured by a high-throughput peroxidase-based hematology analyzer during performance of a complete blood count with differential. The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=5895) and then independently validated in a nonoverlapping validation cohort (n=1474). Twenty-three high-risk (observed in ≥10% of subjects with events) and 24 low-risk (observed in ≥10% of subjects without events) patterns were identified in the derivation cohort. Erythrocyte- and leukocyte (peroxidase)-derived parameters dominated the variables predicting risk of death, whereas variables in MI risk patterns included traditional cardiac risk factors and elements from all blood cell lineages. Within the validation cohort, the PEROX model demonstrated superior prognostic accuracy (78%) for 1-year risk of death or MI compared with traditional risk factors alone (67%). Furthermore, the PEROX model reclassified 23.5% ( P <0.001) of patients to different risk categories for death/MI when added to traditional risk factors. Conclusion— Comprehensive pattern recognition of high- and low-risk clusters of clinical, biochemical, and hematologic parameters provided incremental prognostic value in stable patients having elective diagnostic cardiac catheterization for 1-year risks of death and MI.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3