IJCS | Volume 33, Nº1, January / February 2019

51 studies, which indicates that the profile of supplemental health care patients is pretty much similar to those from international registries 10 and that it differs from Brazilian data when HFmrEF reaches the absolute majority. 18 The predominance in our study of older individuals with ischemic etiology is also compatible with data fromdeveloped countries. 19-21 In-hospital death, which occurred in 14% of the population studied, is in accordance with data from the Brazilian registry of acute HF patients admitted to public and private hospitals. 18 Twenty-six percent of the population presented HFmrEF, which corroborates the estimated range, from 10-20%, in recent studies. 22,23 These patients were aged over 65 years (80%), with a higher proportion of females, similarly to the HFpEF profile. As for ischemic etiology, HFmrEF had a prevalence of 56 % and was closer in value to the HFrEF group. Hypertensive etiology showed intermediate values in relation to the other two groups. DHF associated withACS was more prevalent among HFmrEF patients (46%) compared to those from the other two groups. In Brazil, recent data have shown that the main cause of DHF is poor medication adherence; 18 other studies presented different results. 23 Data from OPTIMIZE-HF, 24 a comprehensive European registry, were consistent with those reported in this study, which can be justified by differences between the profile and data of the population seen at supplemental health system and in the public health system. HFmrEF presented with high comorbidity rates, such as diabetes mellitus, hypertension, IC and MI, and showed intermediate values for valve disease, kidney disease and alcoholism. It is also interesting to stress that left ventricular end-diastolic diameter values were intermediate, which indicates a possible transition stage between the other two HF groups. The similarities between HFmrEF and HFpEF suggest that HFmrEF may represent recovered or early stages of HFrEF, 25,26 but other long-term echocardiographic follow-up studies in these patients are needed. Mortality and Prognostic Factors In-hospital mortality in HFmrEF was similar in absolute values to HFpEF but lower than HFrEF, although the study has no sufficient statistical power to prove this difference. The same pattern was observed in hospital readmission rates. The “benignity” of HFpEF has been documented in the literature. 27 Data from the OPTIMIZE registry have shown lower in-hospital mortality rates in HFpEF patients. Nevertheless, the criterion adopted in this study was HFpEF (EF ≥ 40%), 28 and thus included those patients currently classified as HFmrEF, which poses limitations to comparisons. A meta-analysis involving over 60,000 patients reported lower mortality inHFpEF (EF ≥ 50%) compared toHFrEF. However, the evaluation itself does not make a distinction between outpatients or patients with DHF, which may influence the outcomes. 29 Only a handful of published studies have focused on patients with HFmrEF which, comparable to the sample of this study, have shown an intermediate group with mortality rates similar to those in the other HF groups. 30 Consequently, the population data shown is this report are consistent with recently published studies that used data from hospitalized patients. 30 When the outcomes were analyzed, after the one-year follow-up evaluation, including death by any cause and admission due to HF, there were similarities between HFmrEF and HFpEF, with HFrEF patients presenting the worst prognosis. 31 It was not possible to establish comparisons with national data due to the scarcity of publications. In general, heart failure mortality prediction scores have limited accuracy. 10 The BIOSTAT–CHF 32 emerged as a comprehensive European programdesigned to develop and validate risk prediction models, in an attempt to minimize this problem. The authors highlighted the small percentage of models validated in a separate cohort and the fact these models performed only moderately (c-statistic values 0.71 and 0.63 for mortality and HF hospitalization, respectively). Using a multivariable model (249), they found that the strongest predictors of mortalitywere urea and serum sodium. It is interesting to highlight that there was no significant difference between patients with acute or chronic HF. An LVEF cut-off of 45% was used to distinguish HFrEF from HFpEF, and no similarities were found between the risk factors of the population studied and the validation cohort, which has also included a small percentage of patients with an LVEF greater than 45%. The LVEF cut-off adopted may be a limiting factor for extrapolation of any findings to the HFmrEF group. 32 A recent Swedish HF registry has reported that chronic kidney disease is a strong predictor of mortality in both HFmrEF and HFrEF patients. 33 However, in the population assessed here, renal involvement, whether due to previous kidney disease or to increased urea at admission, was the only mortality predictor that revealed similarities between the 3 HF Cavalcanti et al. Decompensated heart failure with intermediate ejection fraction Int J Cardiovasc Sci. 2020;33(1):45-54 Original Article