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Usefulness of a Complete Blood Count-Derived Risk Score to Predict Incident Mortality in Patients With Suspected Cardiovascular Disease

Authors
Journal
The American Journal of Cardiology
0002-9149
Publisher
Elsevier
Publication Date
Volume
99
Issue
2
Identifiers
DOI: 10.1016/j.amjcard.2006.08.015
Keywords
  • Regular Paper

Abstract

The complete blood cell (CBC) count is an inexpensive, frequently obtained blood test whose information content is potentially underused. We examined the predictive ability of the CBC count for incident death in 29,526 consecutive consenting patients who underwent coronary angiography. Subjects were randomly assigned to training (60%) and test (40%) groups and were followed for an average of 4.9 years. Computed and integer risk score models for all-cause death were developed for 30 days and 1, 5, and 10 years using multivariable logistic regressions applied to CBC metrics, age, and gender. The study cohort was an average age of 61 years, 62% were men, and had a 3.3% annual risk of mortality. An integer (scalar) risk score (range 0 to 18) successfully separated patient cohorts into subgroups at markedly different mortality risks (<1% to >14% at 30 days). Predictive fractions (area under risk curve) at 30 days for the CBC-only model and the age- and gender-adjusted CBC model were 0.76 and 0.78, respectively, in the training set and 0.71 and 0.75, respectively, in the test set (all p values <<0.001). The CBC model was markedly more informative than models based only on hematocrit, white blood cell count, or age and gender and was superior to models with all 7 traditional risk factors. In conclusion, in a large, prospectively assembled database, a CBC risk model had high predictive ability for risk of incident mortality. A total CBC score is an important new addition to risk prediction, and it can be easily generated by computer for clinical use at negligible incremental cost.

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