Clinically Feasible Stratification of 3-Year Chronic Disease Risk in Primary Care: The Mental Health Integration Risk Score

Prediction of Long-Term Incidence of Chronic Cardiovascular and Cardiopulmonary Diseases in Primary Care Patients for Population Health Monitoring: The Intermountain Chronic Disease Model (ICHRON)

OBJECTIVE

To apply the practical parsimonious modeling method of the Intermountain Mortality Risk Score in a primary care environment to predict chronic disease (ChrD) onset.

PATIENTS AND METHODS

Primary care patients free of ChrD (women: n=98,711; men: n=45,543) were evaluated to develop (70% [n=95,882] of patients) and validate (the other 30% [n=48,372]) the sex-specific Intermountain Chronic Disease Risk Score (ICHRON) if seen initially between January 1, 2003, and December 31, 2005. The sex-specific ICHRON was composed of comprehensive metabolic profile and complete blood count components and age. The primary outcome was the first diagnosis of coronary artery disease, myocardial infarction, heart failure, atrial fibrillation, stroke, diabetes, renal failure, chronic obstructive pulmonary disease, peripheral vascular disease, or dementia within 3 years of baseline.

RESULTS

At 3 years, 9.0% of men (mean age, 44±16 years) and 6.6% of women (mean age, 42±16 years) received a diagnosis of ChrD. In the derivation population, C-statistics were 0.783 (95% CI, 0.774-0.791) for men and 0.774 (95% CI, 0.767-0.781) for women. In the validation population, C-statistics were 0.774 (95% CI, 0.762-0.786) for men and 0.762 (95% CI, 0.752-0.772) for women. Evaluation of 10-year outcomes for ICHRON and analysis of its association with each outcome individually at 3 years revealed similar predictive ability.

CONCLUSION

An augmented intelligence clinical decision tool for primary care, ICHRON, is developed using common laboratory parameters, which provides good discrimination of ChrD risk at 3 and 10 years.

Practical laboratory-based clinical decision tools and associations with short-term bleeding and mortality outcomes

BACKGROUND

The red cell distribution width (RDW) predicts mortality in numerous populations. The Intermountain Risk Scores (IMRS) predict patient outcomes using laboratory measurements including RDW. Whether the RDW or IMRS predicts in-hospital outcomes is unknown.

METHODS

The predictive abilities of RDW and two IMRS formulations (the complete blood count [CBC] risk score [CBC-RS] or full IMRS using CBC plus the basic metabolic profile) were studied among percutaneous coronary intervention patients at Intermountain (males: N = 6007, females: N = 2165). Primary endpoints were a composite bleeding outcome and in-hospital mortality.

RESULTS

IMRS predicted the composite bleeding endpoint (females: χ² = 47.1, odds ratio [OR] = 1.13 per +1 score, p < 0.001; males: χ² = 108.7, OR = 1.13 per +1 score, p < 0.001) more strongly than RDW (females: χ² = 1.6, OR = 1.04 per +1%, p = 0.20; males: χ² = 11.2, OR = 1.09 per +1%, p < 0.001). For in-hospital mortality, RDW was predictive in females (χ² = 4.3, OR = 1.13 per +1%, p = 0.037) and males (χ² = 4.4, OR = 1.11 per +1%, p = 0.037), but IMRS was profoundly more predictive (females: χ² = 35.5, OR = 1.36 per +1 score, p < 0.001; males: χ² = 72.9, OR = 1.40 per+1 score, p < 0.001). CBC-RS was more predictive than RDW but not as powerful as IMRS.

CONCLUSIONS

The IMRS, the CBC-RS, and RDW predict in-hospital outcomes. Risk score-directed personalization of in-hospital clinical care should be studied.