Acute heart failure congestion and perfusion status – impact of the clinical classification on in-hospital and long-term outcomes; insights from the ESC-EORP-HFA Heart Failure Long-Term Registry

Aims: Classification of acute heart failure (AHF) patients into four clinical profiles defined by evidence of congestion and perfusion is advocated by the 2016 European Society of Cardiology (ESC)guidelines. Based on the ESC-EORP-HFA Heart Failure Long-Term Registry, we compared differences in baseline characteristics, in-hospital management and outcomes among congestion/perfusion profiles using this classification. Methods and results: We included 7865 AHF patients classified at admission as: ‘dry-warm’ (9.9%), ‘wet-warm’ (69.9%), ‘wet-cold’ (19.8%) and ‘dry-cold’ (0.4%). These groups differed significantly in terms of baseline characteristics, in-hospital management and outcomes. In-hospital mortality was 2.0% in ‘dry-warm’, 3.8% in ‘wet-warm’, 9.1% in ‘dry-cold’ and 12.1% in ‘wet-cold’ patients. Based on clinical classification at admission, the adjusted hazard ratios (95% confidence interval) for 1-year mortality were: ‘wet-warm’ vs. ‘dry-warm’ 1.78 (1.43–2.21) and ‘wet-cold’ vs. ‘wet-warm’ 1.33 (1.19–1.48). For profiles resulting from discharge classification, the adjusted hazard ratios (95% confidence interval) for 1-year mortality were: ‘wet-warm’ vs. ‘dry-warm’ 1.46 (1.31–1.63) and ‘wet-cold’ vs. ‘wet-warm’ 2.20 (1.89–2.56). Among patients discharged alive, 30.9% had residual congestion, and these patients had higher 1-year mortality compared to patients discharged without congestion (28.0 vs. 18.5%). Tricuspid regurgitation, diabetes, anaemia and high New York Heart Association class were independently associated with higher risk of congestion at discharge, while beta-blockers at admission, de novo heart failure, or any cardiovascular procedure during hospitalization were associated with lower risk of residual congestion. Conclusion: Classification based on congestion/perfusion status provides clinically relevant information at hospital admission and discharge. A better understanding of the clinical course of the two entities could play an important role towards the implementation of targeted strategies that may improve outcomes. © 2019 The Authors. European Journal of Heart Failure © 2019 European Society of Cardiolog

Performance of Prognostic Risk Scores in Chronic Heart Failure Patients Enrolled in the European Society of Cardiology Heart Failure Long-Term Registry

Objectives: This study compared the performance of major heart failure (HF) risk models in predicting mortality and examined their utilization using data from a contemporary multinational registry. Background: Several prognostic risk scores have been developed for ambulatory HF patients, but their precision is still inadequate and their use limited. Methods: This registry enrolled patients with HF seen in participating European centers between May 2011 and April 2013. The following scores designed to estimate 1- to 2-year all-cause mortality were calculated in each participant: CHARM (Candesartan in Heart Failure-Assessment of Reduction in Mortality), GISSI-HF (Gruppo Italiano per lo Studio della Streptochinasi nell'Infarto Miocardico-Heart Failure), MAGGIC (Meta-analysis Global Group in Chronic Heart Failure), and SHFM (Seattle Heart Failure Model). Patients with hospitalized HF (n = 6,920) and ambulatory HF patients missing any variable needed to estimate each score (n = 3,267) were excluded, leaving a final sample of 6,161 patients. Results: At 1-year follow-up, 5,653 of 6,161 patients (91.8%) were alive. The observed-to-predicted survival ratios (CHARM: 1.10, GISSI-HF: 1.08, MAGGIC: 1.03, and SHFM: 0.98) suggested some overestimation of mortality by all scores except the SHFM. Overprediction occurred steadily across levels of risk using both the CHARM and the GISSI-HF, whereas the SHFM underpredicted mortality in all risk groups except the highest. The MAGGIC showed the best overall accuracy (area under the curve [AUC] = 0.743), similar to the GISSI-HF (AUC = 0.739; p = 0.419) but better than the CHARM (AUC = 0.729; p = 0.068) and particularly better than the SHFM (AUC = 0.714; p = 0.018). Less than 1% of patients received a prognostic estimate from their enrolling physician. Conclusions: Performance of prognostic risk scores is still limited and physicians are reluctant to use them in daily practice. The need for contemporary, more precise prognostic tools should be considered