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Background: The red cell distribution width (RDW) predicts mortality among many populations. RDW is calculated as the standard deviation (SD) of the red blood cell (RBC) volume divided by mean corpuscular volume (MCV). Because higher MCV also predicts mortality, we hypothesized that the RDW numerator (one SD of RBC volume or 1SD-RDW) predicts mortality more strongly than the RDW., Material and Methods: Adult subjects hospitalized during a contemporary clinical era (10/2005-1/2014, N = 135,963) and a historical era (1/1999-9/2005, N = 119,530) were studied. The RDW was obtained from the complete blood count (CBC), while 1SD-RDW was calculated (RDW multiplied by MCV and divided by 100)., Results: In univariable Cox regression (2005-2014 cohort), 1SD-RDW (quintile 5 vs. 1: hazard ratio [HR] = 8.38, 95% confidence interval [CI] = 7.94, 8.85; P < 0.001) was a superior predictor of mortality compared to RDW (quintile 5 vs. 1: HR = 4.78, CI = 4.57, 5.00; P < 0.001). This superiority remained after adjustment for age, sex, basic metabolic profile components and other CBC factors excluding MCV (1SD-RDW: HR = 2.41, CI = 2.28, 2.55; RDW: HR = 2.01, CI = 1.92, 2.11). Further adjustment for MCV strengthened the RDW association (HR = 2.14, CI = 2.04, 2.24; P < 0.001), becoming indistinct from 1SD-RDW (HR = 2.20, CI = 2.08, 2.33; P < 0.001). Findings were similar for the 1999-2005 cohort., Conclusions: The 1SD-RDW predicted mortality more strongly than RDW, suggesting that 1SD-RDW is superior to RDW as an individual risk predictor. Further, these results indicate that the dispersion of RBC volume and its mean are independent risk markers. Further research is required to understand the clinical value and mechanistic basis of these associations., (© 2015 Stichting European Society for Clinical Investigation Journal Foundation.)

Background: The basic metabolic profile (BMP) is a common blood test containing information about standard blood electrolytes and metabolites. Although individual variables are checked for cardiovascular health and risk, combining them into a total BMP-derived score, as to maximize BMP predictive ability, has not been previously attempted., Methods: Patients (N = 279,337) that received a BMP and had long-term follow-up for death were studied. Risk models were created in a training group (60% of study population, n = 167,635), validated in a test group (40% of study population, n = 111,702), and confirmed in the NHANES III (Third National Health and Nutrition Examination Survey) participants (N = 17,752). The BMP models were developed for 30-day, 1-year, and 5-year death using logistic regression with adjustment for age and sex. The BMP parameters were categorized as low, normal, or high based on the standard range of normal. Glucose was categorized as normal, intermediate, and high. Creatinine >or=2 mg/dL was further categorized as very high., Results: Average age was 53.2 +/- 20.1 years, and 44.3% were male. The areas under the curve for the training and test groups for 30-day, 1-year, and 5-year death were 0.887 and 0.882, 0.850 and 0.848, and 0.858 and 0.847, respectively. The predictive ability of these risk scores was further confirmed in the NHANES III population and independent of the Framingham Risk Score., Conclusion: In large, prospectively followed populations, a highly significant predictive ability for death was found for a BMP risk model. We propose a total BMP score as an optimization of this routine baseline test to provide an important new addition to risk prediction.

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.