Heart failure is a global public health problem, affecting a large number of individuals from low-income and middle-income countries. REPORT-HF is, to our knowledge, the first prospective global ...registry collecting information on patient characteristics, management, and prognosis of acute heart failure using a single protocol. The aim of this study was to investigate differences in 1-year post-discharge mortality according to region, country income, and income inequality.
Patients were enrolled during hospitalisation for acute heart failure from 358 centres in 44 countries on six continents. We stratified countries according to a modified WHO regional classification (Latin America, North America, western Europe, eastern Europe, eastern Mediterranean and Africa, southeast Asia, and western Pacific), country income (low, middle, high) and income inequality (according to tertiles of Gini index). Risk factors were identified on the basis of expert opinion and knowledge of the literature.
Of 18 102 patients discharged, 3461 (20%) died within 1 year. Important predictors of 1-year mortality were old age, anaemia, chronic kidney disease, presence of valvular heart disease, left ventricular ejection fraction phenotype (heart failure with reduced ejection fraction HFrEF vs preserved ejection fraction HFpEF), and being on guideline-directed medical treatment (GDMT) at discharge (p<0·0001 for all). Patients from eastern Europe had the lowest 1-year mortality (16%) and patients from eastern Mediterranean and Africa (22%) and Latin America (22%) the highest. Patients from lower-income countries (ie, ≤US$3955 per capita; hazard ratio 1·58, 95% CI 1·41–1·77), or with greater income inequality (ie, from the highest Gini tertile; 1·25, 1·13–1·38) had a higher 1-year mortality compared with patients from regions with higher income (ie, >$12 235 per capita) or lower income inequality (ie, from the lowest Gini tertile). Compared with patients with HFrEF, patients with HFpEF had a lower 1-year mortality with little variation by income level (pinteraction for HFrEF vs HFpEF <0·0001).
Acute heart failure is associated with a high post-discharge mortality, particularly in patients with HFrEF from low-income regions with high income inequality. Regional differences exist in the proportion of eligible patients discharged on GDMT, which was strongly associated with mortality and might reflect lack of access to post-discharge care and prescribing of GDMT.
Novartis Pharma.
This study sought to evaluate the incidence, the predictors, and the associations with outcomes of changes in ejection fraction (EF) in heart failure (HF) patients.
EF determines therapy in HF, but ...information is scarce about incidence, determinants, and prognostic implications of EF change over time.
Patients with ≥2 EF measurements registered in the Swedish Heart Failure Registry were categorized as heart failure with preserved ejection fraction (HFpEF) (EF ≥50%), heart failure with midrange ejection fraction (HFmrEF) (EF 40% to 49%), or heart failure with reduced ejection fraction (HFrEF) (EF <40%). Changes among categories were recorded, and associations among EF changes, predictors, and all-cause mortality and/or HF hospitalizations were analyzed using logistic and Cox regressions.
Of 4,942 patients at baseline, 18% had HFpEF, 19% had HFmrEF, and 63% had HFrEF. During follow-up, 21% and 18% of HFpEF patients transitioned to HFmrEF and HFrEF, respectively; 37% and 25% of HFmrEF patients transitioned to HFrEF and HFpEF, respectively; and 16% and 10% of HFrEF patients transitioned to HFmrEF and HFpEF, respectively. Predictors of increased EF included female sex, cases of less severe HF, and comorbidities. Predictors of decreased EF included diabetes, ischemic heart disease, and cases of more severe HF. Use of renin-angiotensin-system inhibitors was associated with lower likelihood of EF increase, but not with EF decrease (i.e., stable EF). Increased EF was associated with a lower risk (hazard ratio HR: 0.62; 95% confidence interval CI: 0.55 to 0.69) and decreased EF with a higher risk (HR: 1.15; 95% CI: 1.01 to 1.30) of mortality and/or HF hospitalizations. Prognostic implications were most evident for transitions to and from HFrEF.
Increases in EF occurred in one-fourth of HFrEF and HFmrEF patients, and decreases occurred in more than one-third of patients with HFpEF and HFmrEF. EF change was associated with a wide range of important clinical and organizational factors as well as with outcomes, particularly transitions to and from HFrEF.
Display omitted
Aims
Heart failure (HF) quality registries report quality of care but it is unknown whether they improve outcomes. The aims were to assess predictors of enrolment in a HF registry, test the ...hypothesis that enrolment in a HF registry is associated with reduced mortality, and assess potential explanatory factors for this reduction in mortality, if present.
Methods and results
We conducted a nationwide prospective cohort study of patients with new‐onset HF registered in the Swedish National Patient Registry (NPR, a mandatory registry of ICD‐code diagnoses) with or without concurrent registration in the Swedish Heart Failure Registry (SwedeHF, a voluntary quality reporting registry) 2006–2013. The association between demographics, co‐morbidities and medications, and enrolment in the SwedeHF, was assessed using multivariable logistic regression. The association between enrolment in the SwedeHF and all‐cause mortality was assessed using multivariable Cox regression, with adjustment for demographics, co‐morbidities and medications. A total of 231 437 patients were included, of which 21 888 (9.5%) were in the SwedeHF age (mean ± standard deviation) 74 ± 13 years; 41% women; 68% inpatients and 209 549 (90.5%) were not (age 78 ± 12 years, 50% women; 79% inpatients). Selected variables independently associated with enrolment in the SwedeHF were male sex, younger age, higher education, absent co‐morbidities and co‐morbidity‐related medications, and use of HF and cardiovascular medications. Over a median (interquartile range) follow‐up of 874 (247–1667) days, there were 13.0 vs. 20.8 deaths per 100 patient‐years (P < 0.001). The hazard ratio (95% confidence interval) for death for the SwedeHF yes vs. no was 0.65 (0.63–0.66) crude, and increased to 0.80 (0.78–0.81) after adding demographics, to 0.82 (0.80–0.84) after adding co‐morbidities and co‐morbidity‐related medications, to 0.95 (0.93–0.97) after adding cardiovascular medications, and to 1.04 (1.02–1.07) after adding HF‐specific medications.
Conclusion
Heart failure patients of male sex, younger age, and higher education were more likely to be enrolled in a HF quality registry. Enrolment was associated with reduced all‐cause mortality that was explained by demographic differences and better utilization of cardiovascular and HF medications.
Background
Whereas heart failure (HF) is a complex clinical syndrome, conventional approaches to its management have treated it as a singular disease, leading to inadequate patient care and ...inefficient clinical trials. We hypothesized that applying advanced analytics to a large cohort of HF patients would improve prognostication of outcomes, identify distinct patient phenotypes, and detect heterogeneity in treatment response.
Methods and Results
The Swedish Heart Failure Registry is a nationwide registry collecting detailed demographic, clinical, laboratory, and medication data and linked to databases with outcome information. We applied random forest modeling to identify predictors of 1‐year survival. Cluster analysis was performed and validated using serial bootstrapping. Association between clusters and survival was assessed with Cox proportional hazards modeling and interaction testing was performed to assess for heterogeneity in response to HF pharmacotherapy across propensity‐matched clusters. Our study included 44 886 HF patients enrolled in the Swedish Heart Failure Registry between 2000 and 2012. Random forest modeling demonstrated excellent calibration and discrimination for survival (C‐statistic=0.83) whereas left ventricular ejection fraction did not (C‐statistic=0.52): there were no meaningful differences per strata of left ventricular ejection fraction (1‐year survival: 80%, 81%, 83%, and 84%). Cluster analysis using the 8 highest predictive variables identified 4 clinically relevant subgroups of HF with marked differences in 1‐year survival. There were significant interactions between propensity‐matched clusters (across age, sex, and left ventricular ejection fraction and the following medications: diuretics, angiotensin‐converting enzyme inhibitors, β‐blockers, and nitrates, P<0.001, all).
Conclusions
Machine learning algorithms accurately predicted outcomes in a large data set of HF patients. Cluster analysis identified 4 distinct phenotypes that differed significantly in outcomes and in response to therapeutics. Use of these novel analytic approaches has the potential to enhance effectiveness of current therapies and transform future HF clinical trials.
Aims
Clinical features and outcomes in the novel phenotype heart failure with mid‐range ejection fraction HFmrEF, ejection fraction (EF) 40–49% were compared with heart failure with reduced EF ...(HFrEF, EF <40%) and preserved EF (HFpEF, EF ≥50%).
Methods and results
In the Swedish Heart Failure Registry, we assessed the association between baseline characteristics and EF group using multivariable logistic regressions, and the association between EF group and all‐cause mortality using multivariable Cox regressions. Of 42 061 patients, 56% had HFrEF, 21% had HFmrEF, and 23% had HFpEF. Characteristics were continuous for age (72 ± 12 vs. 74 ± 12 vs. 77 ± 11 years), proportion of women (29% vs. 39% vs. 55%), and 13 other characteristics. Coronary artery disease (CAD) was distinctly more common in HFrEF (54%) and HFmrEF (53%) vs. HFpEF (42%); adjusted odds ratio for CAD in HFmrEF vs. HFpEF was 1.52 95% confidence interval (CI) 1.41–1.63. For six additional characteristics HFmrEF resembled HFrEF, for seven characteristics HFmrEF resembled HFpEF, and for 10 characteristics there was no pattern. The adjusted hazard ratio (HR) for mortality in HFrEF vs. HFpEF was 1.35 (95% CI 1.14–1.60) at 30 days, 1.26 (95% CI 1.17–1.35) at 1 year, and 1.20 (95% CI 1.14–1.26) at 3 years. In contrast, HFmrEF and HFpEF had a similar prognosis (HR 1.06, 95% CI 0.86–1.30 at 30 days; HR 1.08, 95% CI 1.00–1.18 at 1 year; and HR 1.06, 95% CI 1.00–1.12 at 3 years). Three‐year mortality was higher in HFmrEF than in HFpEF in the presence of CAD (HR 1.11, 95% CI 1.02–1.21), but not in the absence of CAD (HR 1.02, 95% CI 0.94–1.12; P for interaction <0.001).
Conclusions
HFmrEF was an intermediate phenotype, except that CAD was more common in HFmrEF and HFrEF vs. HFpEF, crude all‐cause mortality was lower in HFmrEF and HFrEF, adjusted all‐cause mortality was lower in HFmrEF and HFpEF, and CAD portended a higher adjusted risk of death in HFmrEF and HFrEF.
Abstract Background Heart failure (HF) is a common and serious complication in type 2 diabetes mellitus (T2DM). The prognosis of ischemic HF and impact of revascularization in such patients have not ...been investigated fully in a patient population representing everyday practice. Objectives This study examined the impact of ischemic versus nonischemic HF and previous revascularization on long-term prognosis in an unselected population of patients with and without T2DM. Methods Patients stratified by diabetes status and ischemic or nonischemic HF and history of revascularization in the Swedish Heart Failure Registry (SwedeHF) from 2003 to 2011 were followed up for mortality predictors and longevity. A propensity score analysis was applied to evaluate the impact of previous revascularization. Results Among 35,163 HF patients, those with T2DM were younger, and 90% had 1 or more associated comorbidities. Ischemic heart disease (IHD) occurred in 62% of patients with T2DM and 47% of those without T2DM, of whom 53% and 48%, respectively, had previously undergone revascularization. T2DM predicted mortality regardless of the presence of IHD, with adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) of 1.40 (1.33 to 1.46) and 1.30 (1.22 to 1.39) in those with and without IHD, respectively. Patients with both T2DM and IHD had the highest mortality, which was further accentuated by the absence of previous revascularization (adjusted HR: 0.82 in favor of such treatment; 95% CI: 0.75 to 0.91). Propensity score adjustment did not change these results (HR: 0.87; 95% CI: 0.78 to 0.96). Revascularization did not abolish the impact of T2DM, which predicted mortality in those with (HR: 1.36; 95% CI: 1.24 to 1.48) and without (HR: 1.45; 95% CI: 1.33 to 1.56) a history of revascularization. Conclusions Ninety percent of HF patients with T2DM have preventable comorbidities. IHD in patients with T2DM had an especially negative influence on mortality, an impact that was beneficially influenced by previous revascularization.
Guidelines on heart failure (HF) stress the importance of lifestyle advice, although there is little evidence that such recommendations improve symptoms or prognosis. Patients experience symptoms of ...different intensities which impair their daily activities and reduce the quality‐of‐life. To cope with their clinical condition, many patients seek advice about lifestyle and self‐management strategies when in contact with medical care providers, particularly specialized HF services. Self‐care management is an important part of HF treatment, thus health professionals working with patients with HF have recognized the need for more specific recommendations on lifestyle advice. The present paper summarizes the available evidence, promotes self‐care management, and aims to provide practical advice for health professionals delivering care to HF patients. It also defines avenues of research to optimize self‐care strategies in a number of key areas to derive further benefits.
Natriuretic peptide-guided (NP-guided) treatment of heart failure has been tested against standard clinically guided care in multiple studies, but findings have been limited by study size. We sought ...to perform an individual patient data meta-analysis to evaluate the effect of NP-guided treatment of heart failure on all-cause mortality.
Eligible randomized clinical trials were identified from searches of Medline and EMBASE databases and the Cochrane Clinical Trials Register. The primary pre-specified outcome, all-cause mortality was tested using a Cox proportional hazards regression model that included study of origin, age (<75 or ≥75 years), and left ventricular ejection fraction (LVEF, ≤45 or >45%) as covariates. Secondary endpoints included heart failure or cardiovascular hospitalization. Of 11 eligible studies, 9 provided individual patient data and 2 aggregate data. For the primary endpoint individual data from 2000 patients were included, 994 randomized to clinically guided care and 1006 to NP-guided care. All-cause mortality was significantly reduced by NP-guided treatment hazard ratio = 0.62 (0.45-0.86); P = 0.004 with no heterogeneity between studies or interaction with LVEF. The survival benefit from NP-guided therapy was seen in younger (<75 years) patients 0.62 (0.45-0.85); P = 0.004 but not older (≥75 years) patients 0.98 (0.75-1.27); P = 0.96. Hospitalization due to heart failure 0.80 (0.67-0.94); P = 0.009 or cardiovascular disease 0.82 (0.67-0.99); P = 0.048 was significantly lower in NP-guided patients with no heterogeneity between studies and no interaction with age or LVEF.
Natriuretic peptide-guided treatment of heart failure reduces all-cause mortality in patients aged <75 years and overall reduces heart failure and cardiovascular hospitalization.
The pathogenic role of ischemic heart disease (IHD) in heart failure (HF) with reduced ejection fraction (HFrEF; EF <40%) is well established, but its pathogenic and prognostic significance in HF ...with midrange (HFmrEF; EF 40%-50%) and preserved EF (HFpEF; EF ≥50%) has been much less explored.
We evaluated 42 987 patients from the Swedish Heart Failure Registry with respect to baseline IHD, outcomes (IHD, HF, cardiovascular events, and all-cause death), and EF change during a median follow-up of 2.2 years. Overall, 23% had HFpEF (52% IHD), 21% had HFmrEF (61% IHD), and 55% had HFrEF (60% IHD). After multivariable adjustment, associations with baseline IHD were similar for HFmrEF and HFrEF and lower in HFpEF (risk ratio, 0.91 0.89-0.93 versus HFmrEF and risk ratio, 0.90 0.88-0.92 versus HFrEF). The adjusted risk of IHD events was similar for HFmrEF versus HFrEF and lower in HFpEF (hazard ratio, 0.89 0.84-0.95 versus HFmrEF and hazard ratio, 0.84 0.80-0.90 versus HFrEF). After adjustment, prevalent IHD was associated with increased risk of IHD events and all other outcomes in all EF categories except all-cause mortality in HFpEF. Those with IHD, particularly new IHD events, were also more likely to change to a lower EF category and less likely to change to a higher EF category over time.
HFmrEF resembled HFrEF rather than HFpEF with regard to both a higher prevalence of IHD and a greater risk of new IHD events. Established IHD was an important prognostic factor across all HF types.
Aims
We aimed to derive and validate clinically useful clusters of patients with heart failure with preserved ejection fraction (HFpEF; left ventricular ejection fraction ≥50%).
Methods and results
...We derived a cluster model from 6909 HFpEF patients from the Swedish Heart Failure Registry (SwedeHF) and externally validated this in 2153 patients from the Chronic Heart Failure ESC‐guideline based Cardiology practice Quality project (CHECK‐HF) registry. In SwedeHF, the median age was 80 interquartile range 72–86 years, 52% of patients were female and most frequent comorbidities were hypertension (82%), atrial fibrillation (68%), and ischaemic heart disease (48%). Latent class analysis identified five distinct clusters: cluster 1 (10% of patients) were young patients with a low comorbidity burden and the highest proportion of implantable devices; cluster 2 (30%) patients had atrial fibrillation, hypertension without diabetes; cluster 3 (25%) patients were the oldest with many cardiovascular comorbidities and hypertension; cluster 4 (15%) patients had obesity, diabetes and hypertension; and cluster 5 (20%) patients were older with ischaemic heart disease, hypertension and renal failure and were most frequently prescribed diuretics. The clusters were reproduced in the CHECK‐HF cohort. Patients in cluster 1 had the best prognosis, while patients in clusters 3 and 5 had the worst age‐ and sex‐adjusted prognosis.
Conclusions
Five distinct clusters of HFpEF patients were identified that differed in clinical characteristics, heart failure drug therapy and prognosis. These results confirm the heterogeneity of HFpEF and form a basis for tailoring trial design to individualized drug therapy in HFpEF patients.
Latent class analysis identified 5 patient clusters with differences in clinical characteristics in 6909 patients from the Swedish Heart Failure Registry. BMI, body mass index; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; HFpEF, heart failure with preserved ejection fraction; IHD, ischaemic heart disease; NYHA, New York Heart Association.
PDF
