Prediction of incident heart failure and/or re-hospitalization using different risk predictor models in Indian patients.

Abstract

Background and aims: Accurate prediction of incident heart failure (HF), risk of recurrent HF or hospitalization are essential for optimizing patient outcomes. Seeing the rising trends of HF in Indians, the present study assessed the applicability of 5 different HF risk scores in these patients.

Methods and results: Of the 280 patients recruited, 159 (55.7 %) had HF Stage A, B while 121 (44.3 %) had asymptomatic or symptomatic HF (HF Stage C, D). At 30 ± 7.5 months, new onset HF occurred in 32.07 % and in Stage C/D HF patients, rehospitalization was noted in 37.1 % and 8.9 % died. The incidence of new-onset HF increased incrementally with higher Health ABC scores (13.7, 31.4 and 52.9 % in score 5-10 %, 10-20 %, >20 % respectively). Amongst diabetic patients, TRS-HFDM score strongly predicted new-onset HF (16.7, 30 and 43.3 % in score 1,2 and ≥ 3 respectively). LACE index also accurately predicted events in those with Stage C/D HF: rehospitalization for recurrent HF was 6.6, 44.5 and 48.9 % while mortality was 4, 36 and 60 % in those with LACE index 0-4, 5-9, >9 respectively. Patients without any events had a lower MAGGIC score (19.25 ± 9.56) vs those who died (29.33 ± 8.32). H2FPEF score also performed well: re-hospitalization for HF was 22.2 vs 57.7 % and mortality was 20 vs 72 % in score <2 vs score >2.

Conclusion: These easily available risk scores can accurately predict events in Indian patients with HF and should be part of clinical workflow.