Superior predictive ability for death of a basic metabolic profile risk score

Area of Science:

• Clinical Chemistry
• Biomarkers
• Predictive Analytics

Background:

• Basic metabolic profile (BMP) is a common blood test.
• BMPs assess electrolytes and metabolites for cardiovascular health.
• A comprehensive BMP-derived score for predicting mortality has not been developed.

Purpose of the Study:

• To develop and validate a predictive risk score using BMP parameters.
• To maximize the predictive ability of the BMP for mortality.
• To assess the BMP score's performance for predicting 30-day, 1-year, and 5-year mortality.

Main Methods:

• A large cohort (N=279,337) with BMP and mortality data was used.
• Risk models were trained, tested, and validated in independent populations, including NHANES III.
• Logistic regression was employed, categorizing BMP parameters (e.g., glucose, creatinine) to develop risk scores adjusted for age and sex.

Main Results:

• The BMP risk models demonstrated strong predictive ability for 30-day, 1-year, and 5-year mortality.
• Areas under the curve (AUC) ranged from 0.847 to 0.887 in training and test groups.
• The predictive performance was confirmed in NHANES III participants and was independent of the Framingham Risk Score.

Conclusions:

• A BMP-derived risk score possesses significant predictive power for mortality in large populations.
• The proposed total BMP score optimizes this routine test for enhanced risk prediction.
• This novel score represents a valuable addition to existing cardiovascular risk assessment tools.