Mortality prediction in acute heart failure: scores or biomarkers?

Abstract

Acute heart failure (AHF) is a complex and heterogeneous syndrome not only associated with a concerning rise in incidence, but also with still unacceptably high rates of mortality and morbidity. As this dismal outcome is at least in part due to a mismatch between the severity of AHF and the intensity of its management, both in-hospital and immediately after discharge, early and accurate risk prediction could contribute to more effective, risk-adjusted management. Biomarkers are noninvasive and highly reproducible quantitative tools that have improved the understanding of AHF pathophysiology. They can help guide the intensity of AHF management. In addition, using a statistical model to estimate risk from a combination of several predictor variables such as vital signs or demographics has gained more and more attention over recent years. In this context, the aim of a statistical model, which gives a so-called risk score, is to help clinicians to make more standardised decisions. This review highlights recent advances and remaining uncertainties regarding risk stratification in AHF by characterising and comparing the potential of biomarkers and risk scores.

Quantifying inflammation using interleukin‐6 for improved phenotyping and risk stratification in acute heart failure

“…Despite the development of multivariate scores aiming to help physicians in the accurate risk prediction regarding mortality and AHF rehospitalization, 35 relevant uncertainties remain. Using interleukin‐6 in conjunction with either an established clinical score or established cardiovascular biomarkers representing other pathophysiological signals that characterize the AHF syndrome, such as NT‐proBNP and hs‐cTnT, might provide medical value 13,14 .…”

“…29,30 In our study NT-proBNP, a biomarker known to be produced in response to increased myocardial and haemodynamic stress, was an independent predictor of elevated interleukin-6 concentrations. [31][32][33][34] Despite the development of multivariate scores aiming to help physicians in the accurate risk prediction regarding mortality and AHF rehospitalization, 35 relevant uncertainties remain. Using interleukin-6 in conjunction with either an established clinical score or established cardiovascular biomarkers representing other pathophysiological signals that characterize the AHF syndrome, such as NT-proBNP and hs-cTnT, might provide medical value.…”

Risk Prediction Models for Patients With Acute Heart Failure: A Protocol for Systematic Review, Critical Appraisal, and Meta-Analysis

“…Risk prediction models usually encompass a combination of predictors such as vital signs, biomarkers, and demographics; they provide estimates of future outcomes of AHF [13]. These statistical models, which yield a so-called risk score for mortality, hospital readmission and other outcomes in AHF.…”

Acute heart failure after non‐cardiac surgery: incidence, phenotypes, determinants and outcomes

“…Acute heart failure (AHF) is the most common cause of urgent hospitalization, and is associated with high mortality and morbidity. [1][2][3][4][5][6][7] Over the last decades, major efforts by interdisciplinary academic consortia, professional societies, and the pharmaceutical industry have provided important evidence regarding this complex heterogeneous syndrome. 1,[7][8][9][10][11][12][13][14][15] Recently, it has become apparent that AHF may not only be a major health burden as the primary diagnosis leading to hospitalization, but also if developing as a complication in patients hospitalized for other medical or surgical causes.…”

“…Acute heart failure (AHF) is the most common cause of urgent hospitalization, and is associated with high mortality and morbidity 1–7 . Over the last decades, major efforts by interdisciplinary academic consortia, professional societies, and the pharmaceutical industry have provided important evidence regarding this complex heterogeneous syndrome 1,7–15 …”