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Background: Some components of the complete blood count and basic metabolic profile are commonly used risk predictors. Many of their components are not commonly used, but they might contain independent risk information. This study tested the ability of a risk score combining all components to predict all-cause mortality., Methods: Patients with baseline complete blood count and basic metabolic profile measurements were randomly assigned (60%/40%) to independent training (N = 71,921) and test (N = 47,458) populations. A third population (N = 16,372) from the Third National Health and Nutrition Examination Survey and a fourth population of patients who underwent coronary angiography (N = 2558) were used as additional validation groups. Risk scores were computed in the training population for 30-day, 1-year, and 5-year mortality using age- and sex-adjusted weights from multivariable modeling of all complete blood count and basic metabolic profile components., Results: Area under the curve c-statistics were exceptional in the training population for death at 30 days (c = 0.90 for women, 0.87 for men), 1 year (c = 0.87, 0.83), and 5-years (c = 0.90, 0.85) and in the test population for death at 30 days (c = 0.88 for women, 0.85 for men), 1 year (c = 0.86, 0.82), and 5 years (c = 0.89, 0.83). In the test, the Third National Health and Nutrition Examination Survey, and the angiography populations, risk scores were highly associated with death (P <.001), and thresholds of risk significantly stratified all 3 populations., Conclusion: In large patient and general populations, risk scores combining complete blood count and basic metabolic profile components were highly predictive of death. Easily computed in a clinical laboratory at negligible incremental cost, these risk scores aggregate baseline risk information from both the popular and the underused components of ubiquitous laboratory tests.

Aims The complete blood count (CBC) and basic metabolic profile are common, low-cost blood tests, which have previously been used to create and validate the Intermountain Risk Score (IMRS) for mortality prediction. Mortality is the most definitive clinical endpoint, but medical care is more easily applied to modify morbidity and thereby prevent death. This study tested whether IMRS is associated with clinical morbidity endpoints. Methods and results Patients seen for coronary angiography (n = 3927) were evaluated using a design similar to a genome-wide association study. The Bonferroni correction for 102 tests required a P-value of ≤ 4.9 × 10−4 for significance. A second set of angiography patients (n = 10 413) was used to validate significant findings from the first patient sample. In the first patient sample, IMRS predicted heart failure (HF) (Ptrend = 1.6 × 10−26), coronary disease (Ptrend = 2.6 × 10−11), myocardial infarction (MI) (Ptrend = 3.1 × 10−25), atrial fibrillation (Ptrend = 2.5 × 10−20), and chronic obstructive pulmonary disease (Ptrend = 4.7 × 10−4). Even more, IMRS predicted HF readmission [hazard ratio (HR) = 2.29/category, Ptrend = 1.2 × 10−6), incident HF (HR = 1.88/category, Ptrend = 0.02), and incident MI (HR = 1.56/category, Ptrend = 4.7 × 10−4). These findings were verified in the second patient sample. Conclusion Intermountain Risk Score, a predictor of mortality, was associated with morbidity endpoints that often lead to mortality. Further research is required to fully characterize its clinical utility, but its low-cost CBC and basic metabolic profile composition may make it ideal for initial risk estimation and prevention of morbidity and mortality. An IMRS web calculator is freely available at http://intermountainhealthcare.org/IMRS. [ABSTRACT FROM AUTHOR]