Coronary artery diseaseUsefulness of a Complete Blood Count-Derived Risk Score to Predict Incident Mortality in Patients With Suspected Cardiovascular Disease
Section snippets
Study aims
Our primary aim was to develop, evaluate, and validate the utility of a cardiovascular risk model based on multiple CBC count parameters for prediction of incident all-cause mortality in a moderate- to high-risk cardiovascular population at 30 days (primary time point), 1 year (secondary time point), and 5 and 10 years (exploratory time points). A second aim was to compare the predictive ability of the total CBC risk models† with simple models based on age, gender, and other standard risk
Characteristics of the study population
Characteristics, clinical presentation, angiographic status, and outcome of the study population (n = 29,526) are presented in Table 2. The average age was 61 years, and 62% were men. Almost 50% of study subjects had clinical diagnoses of hypertension and hyperlipidemia, 17% were diabetic, and 7% had a previous myocardial infarction. Coronary angiography was normal in 35% and indicated mild/moderate coronary artery disease in 8% and severe disease in 57%, of which 46%, 26%, and 28% had 1-, 2-,
Discussion
In this large population cohort (almost 30,000 patients at moderately high overall cardiovascular risk), we successfully developed, tested, and validated CBC count–based predictive models for incident all-cause mortality. Results clearly demonstrated the excellent predictive ability (AUC 0.712) of concurrently considered WBC count, platelet count, and 4 red blood cell–related metrics. Further, the CBC count model was markedly superior to hematocrit alone, WBC count alone, and gender and age
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This study was supported by the Deseret Foundation, Salt Lake City, Utah.