Biomarker-driven prognostic model for risk prediction in heart failure: ready for Prime time?
Abstract
This editorial refers to ‘Novel biomarker-driven prognostic models to predict morbidity and mortality in chronic heart failure: the EMPEROR-Reduced trial’, by S.J. Pocock et al., https://doi.org/10.1093/eurheartj/ehab579. Graphical presentation of the eight key predictors of the primary composing endpoint in EMPEROR-Reduced. HF, heart failure; NT-proBNP, N-terminal probrain natriuretic peptide; hs-cTnT, high-sensitivity cardiac troponin T. Do you routinely use a risk score to quantify the risk of death and the risk of heart failure (HF) readmission in your patients? Probably, most of us have not done so until now. Some of the arguments that we had been using for years to excuse our medical inertia are no longer valid given the new evidence reported in the current issue of the European Heart Journal by Pocock et al.1 HF is a heterogeneous syndrome with an ongoing rise in prevalence driven at least partly by the ageing society.2 Equally, HF is a growing social and economic burden in terms of high mortality and morbidity, and excessive healthcare costs.3 However, the prognosis of HF has become variable, depending on HF aetiology, healthcare determinants, and disease-modifying therapies.4 In order to better allocate healthcare resources and to overcome uncertainties about the intensity of management, several prognostic models have been developed.1 These should assist physicians in order to implement more standardized and individualized decision-making and to improve the current…
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