Assessing the risk of heart failure in type 2 diabetes: a prediction algorithm to sustain the evaluation of NT-proBNP in primary care.

PURPOSE

Heart failure (HF) is a disease that leads to approximately 300,000 fatalities annually in Europe and 250,000 deaths each year in the United States. Type 2 Diabetes Mellitus (T2DM) is a significant risk factor for HF, and testing for N-terminal (NT)-pro hormone BNP (NT-proBNP) can aid in early detection of HF in T2DM patients. We therefore developed and validated the HFriskT2DM-HScore, an algorithm to predict the risk of HF in T2DM patients, so guiding NT-proBNP investigation in a primary care setting.

METHODS

Using a primary care database, we formed a cohort of patients aged ≥18 years diagnosed with T2DM between 2002 and 2022. A multivariate Cox model was adopted to assess the determinants associated with the occurrence of HF to combine them to form an individual score.

RESULTS

Within a cohort of 167,618 patients (52.3% males; mean age 64.4 (SD: 14.4); HF rate equal to 6.7 cases per 1000 person-years), we developed the HFriskT2DM-HScore. When it was applied to the validation sub-cohort we found an explained variation and discrimination value of 43% (95% CI: 42-44) and 81% (95% CI: 0.80-0.83), respectively. Calibration slope was equal to 0.93 (95% CI: 0.81-1.1; p = 0.3123).

CONCLUSION

The HFriskT2DM-HScore might be implemented as a decision support system for primary care to appropriately ease the prescription of NT-proBNP and early identification of HF.