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Heart Failure Etiologies and Clinical Factors precipitating for Worsening Heart Failure: findings from BIOSTAT-CHF Masatake Kobayashi 1 , Adriaan A. Voors 2 , Nicolas Girerd 1, Maxime Billotte 1 , Stefan D. Anker 3, John G. Cleland 4, Chim C. Lang 5, -AUTHORS- , Leong L. Ng 6, Dirk J. van Veldhuisen 2, Kenneth Dickstein 7, 8, Patrick Rossignol 1 , Faiez Zannad 1 , Jo?o Pedro Ferreira 1Université de Lorraine, INSERM, Centre d'Investigations Cliniques Plurithématique 1433, Inserm U1116, CHRU de Nancy and F-CRIN INI-CRCT, Nancy, France.Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein, Groningen, the Netherlands.Innovative Clinical Trials, Department of Cardiology and Pneumology, University Medical Centre G?ttingen (UMG), G?ttingen, Germany.National Heart & Lung Institute, Royal Brompton and Harefield Hospitals, Imperial College, London, UK.Division of Molecular and Clinical Medicine, School of Medicine, School of Medicine Centre for Cardiovascular and Lung Biology, Division of Medical Sciences, University of Dundee, Ninewells Hospital & Medical School, Dundee, UK.Department of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, and NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, LE3 9QP, UK.University of Bergen, Bergen, Norway.University of Stavanger, Stavanger, Norway.Running title: Etiologies and precipitants in patients with symptomatic heart failureCorresponding Author: Jo?o Pedro Ferreira Centre d’Investigation Clinique 1433 module Plurithématique, CHRU Nancy - Hopitaux de Brabois, Institut Lorrain du Coeur et des Vaisseaux Louis Mathieu, Nancy, 54500, France Email:j.ferreira@chru-nancy.fr Total number of tables and figures: tables 5 figures 2AbstractBackgroundKnowledge on the association between heart failure (HF) etiologies, precipitant causes and clinical outcomes may help in selecting tailored therapeutic strategies. MethodsThe prognostic value of both HF etiologies and precipitants for worsening HF were analyzed using the index cohort of BIOSTAT-CHF. The studied HF etiologies were: a) ischemic HF; b) dilated cardiomyopathy; c) hypertensive HF; d) valvular HF; and e) other/unknown. The precipitating factors for worsening HF were: a) atrial fibrillation; b) noncompliance; c) renal failure; d) acute coronary syndrome; e) hypertension; and f) Infection. The primary outcome was the composite of all-cause death or HF hospitalization.ResultsAmong 2,465 patients included in the study, 45% (N=1102) had ischemic HF, 10% (N=237) hypertensive HF, 7% (N=184) valvular HF, 23% (N=563) dilated cardiomyopathy, and 15% (N=379) had HF of other/unknown etiology. Patients with ischemic HF had the worst prognosis, whereas patients with dilated cardiomyopathy had the best prognosis. From the precipitating factors for worsening HF, renal failure was the one independently associated with worse prognosis (adjusted HR (95%CI)=1.48 (1.04-2.09), p<0.001). We found no interaction between HF etiologies and precipitating factors for worsening HF (p interaction>0.10 for all). Treatment up-titration likely benefits all patients irrespective of their etiology and/or precipitant (p interaction>0.10 for both). ConclusionsIn BIOSTAT-CHF, patients with HF of ischemic etiology, and those with worsening HF precipitated by renal failure (irrespective of the underlying HF etiology), had the highest rates of death and heart failure hospitalization. Treatment up-titration likely benefits patients irrespective of their etiology or precipitant factor. Keywords: Heart failure; etiology; precipitating factor; prognosisIntroductionHeart failure (HF) therapies have improved patients` outcome over the last decades, however those with worsening symptoms and/or signs of HF still have a poor prognosis PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Qb25pa293c2tpPC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

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ADDIN EN.CITE.DATA 1, 2. Both the etiology of HF and the factors leading to its decompensation may influence outcomes and drug response PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5aYW5uYWQ8L0F1dGhvcj48WWVhcj4yMDE4PC9ZZWFyPjxS

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ADDIN EN.CITE.DATA 3-7. Previous studies have shown that patients with HF of ischemic etiology have a worse prognosis than those with non-ischemic etiology PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYXJ0PC9BdXRob3I+PFllYXI+MTk5NzwvWWVhcj48UmVj

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AG==

ADDIN EN.CITE.DATA 7, 10, 11. Nonetheless, the prognostic assessment of the HF etiologies and the worsening HF precipitating factors, as well as their interaction and response to treatment, is yet to be determined. The systems BIOlogy study to Tailored Treatment in Chronic Heart Failure (BIOSTAT-CHF) allows the study of the associations between the HF etiologies, precipitants for worsening HF, treatment up-titration and clinical outcomes. The main aims of the present study are; 1) to describe the clinical characteristics of the patients with regard to their HF etiologies and worsening HF precipitants; 2) to study the association between HF etiologies and worsening HF precipitants with outcomes; 3) to assess whether the prognostic implications of the precipitating factors may be modified by the HF etiologies (and vice-versa); 4) to assess whether treatment up-titration is beneficial irrespective of the HF etiology and/or precipitant. MethodsPatient PopulationThe BIOSTAT-CHF was an international study and its main features have been previously described PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Wb29yczwvQXV0aG9yPjxZZWFyPjIwMTY8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 12, 13. From the 2,516 patients, we selected the 2,465 patients who had specific information on the HF etiologies (Figure 1). Patients were receiving <50% of the target doses of at least one of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers (ACEi/ARBs) and beta-blockers at the time of inclusion. The first 3 months of treatment were considered to be a treatment optimization phase. During the optimization phase, initiation or up-titration of ACEi/ARB and/or beta-blocker was done according to the routine clinical practice of the treating physicians, who were encouraged to follow the European Society of Cardiology guideline PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EaWNrc3RlaW48L0F1dGhvcj48WWVhcj4yMDA4PC9ZZWFy

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ADDIN EN.CITE.DATA 14. Patients reaching at least 50% of the recommended dose of ACEi/ARB and/or beta-blocker at the 3-month visit were considered successfully up-titrated.BIOSTAT-CHF was conducted in concordance with the declaration of Helsinki, national ethics and legal requirements, as well as relevant EU legislation. The study was approved by national and local ethics committees and all patients recruited in BIOSTAT-CHF were given written informed consent to participate in the study. Precipitating Factors and Heart Failure EtiologyHF etiology was characterized according to the specified cases in the case report form (CRF) in categories of ischemic, hypertensive, valvular etiology, dilated cardiomyopathy and other/unknown, according to the treating clinical physicians (Supplemental table 1).In the BIOSTAT-CHF protocol/CRF there were six different classifications of worsening HF precipitating factors from which clinicians could choose (“tick box”): acute coronary syndrome (ACS), atrial fibrillation (AF), hypertension, renal failure, infection and non-compliance (diet, medications or iatrogenic). These factors were collected in the CRF, as per investigator clinical judgement according to the ESC guidelines PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EaWNrc3RlaW48L0F1dGhvcj48WWVhcj4yMDA4PC9ZZWFy

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ADDIN EN.CITE.DATA 14 (Supplementary table 1). More than 1 factor could be selected (whenever applicable). These factors were identified by the local investigators for each patient. The definitions provided by the above referenced guidelines were encouraged, where: ACS, would require elevation of troponin I above the 95th percentile and dynamic electrocardiographic alterations suggestive of acute myocardial ischemia PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYXNzYW5kPC9BdXRob3I+PFllYXI+MjAwNzwvWWVhcj48

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ADDIN EN.CITE.DATA 15; AF, presence of AF on the electrocardiogram; hypertension, office SBP>140 mmHg; renal failure, creatinine >1.5 mg/dl and or deterioration (>20% eGFR drop) of renal function compared with the last available measurement; and infection, with elevated inflammatory parameters, e.g., leucocyte, c-reactive peptide or procalcitonin.Statistical AnalysisCategorical variables are described as frequencies (percentages) and continuous variables are described as means ± standard deviation or median [25th and 75th percentiles] depending on their distribution. Comparisons of demographic, clinical and biological parameters among HF etiologies were conducted using χ? tests for categorical variables and Kruskal-Wallis test or Mann-Whitney test for continuous variables. The primary outcome was the composite of all-cause mortality or HF re-hospitalization. Survival probabilities were estimated using the Kaplan-Meier method and plotted as survival curves with HF etiologies and worsening HF precipitants at 360 and 60 days, respectively due to violation of proportional hazards after these time-points (the Kaplan-Meier curves during overall term follow-up are shown in Supplementary figure 1). Cox proportional-hazards models for HF etiologies and worsening HF precipitating factors were then used to obtain unadjusted and covariate adjusted hazard ratios (HRs) (with dilated cardiomyopathy and noncompliance as the reference groups, respectively). Multivariable models were adjusted for BIOSTAT-CHF risk score PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Wb29yczwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 16. The risk score for the composite outcome included age, HF hospitalization in the year before inclusion, presence of edema, N-terminal prohormone brain natriuretic peptide (NT-proBNP), SBP, hemoglobin, high-density lipoprotein levels, serum sodium concentration, and absence of beta-blocker. This risk score for all-cause mortality included age, higher blood urea nitrogen and NT-proBNP, lower hemoglobin and failure to prescribe a beta-blocker were adjusted for all-cause mortality PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Wb29yczwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PFJl

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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Wb29yczwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 16. With regard to the precipitants, we performed multivariable analyses after adjusting for ischemic etiology in addition to aforementioned covariates. An interaction test was performed to determine whether the effect of respective precipitants would be influenced by the HF etiology, and whether the response to treatment could be influenced by either HF etiology or precipitant. All analyzes were performed using R version 3.1.3 (R Development Core Team, Vienna, Austria). P-value<0.05 was considered statistically significant.ResultsPatient’s Characteristics by Heart Failure Etiology Of the 2,465 patients included in this study, the mean age was 68.4±12.0 years old, 73.2% was male, and the mean LVEF was 31.0±10.5%. With regard to the HF etiology, 45% (N=1102) had ischemic, 10% (N=237) hypertensive, 7% (N=184) valvular, 23% (N=563) dilated cardiomyopathy, and 15% (N=379) other/unknown (Table 1). Compared to patients with non-ischemic HF, patients with ischemic HF were older (mean age 70 vs 67 years), more often male (80 vs 68%) and had more cardiovascular comorbidities and worse renal function (all P<0.001). Amongst all etiologies, patients with dilated cardiomyopathy were the youngest, had fewest comorbidities, best renal function and highest prescription rates of ACEi/ARB and mineralocorticoid receptor antagonist (MRA) prescriptions. Distribution of Precipitating Factors According to Heart Failure EtiologyPatients with ischemic HF were more often precipitated by ACS (Table 2). Patients with hypertensive HF were mainly precipitated by both hypertensive crisis and AF, and the latter was also a major precipitant in patients with valvular HF and dilated cardiomyopathy. The patients’ characteristics according to the precipitating factors are depicted in the Supplementary table 2. Association of Heart Failure Etiologies with OutcomesThe primary outcome occurred in 46.7%, 45.6%, 42.2%, 35.9% and 29.3% of patients with valvular, ischemic, hypertensive HF, other/unknown etiology and dilated cardiomyopathy, respectively. Kaplan-Meier curves showed worse prognoses for ischemic and valvular HF (Figure 1). Considering dilated cardiomyopathy as the referent category, a higher risk of the composite outcome was observed in patients with HF of ischemic etiology; adjusted HR (95%CI)=1.34 (1.12-1.60), p<0.001 (Table 3). In contrast, no specific HF etiology was associated with all-cause mortality (all P-value>0.1). As a sensitivity analysis, the associations of HF etiologies with the primary outcome in ambulatory and hospitalized patients are shown in the Supplementary table 6.Association of Worsening HF Precipitating Factors with OutcomesThe primary outcome occurred in 68.0%, 45.3%, 40.3%, 39.1%, 36.8% and 36.3% of the patients precipitated by renal failure, infection, hypertension, AF, ACS and noncompliance, respectively. After adjusting for BIOSTAT-CHF risk score and ischemic etiology, renal failure was associated with higher incidence of the primary outcome; adjusted HR (95%CI)=1.49 (1.05-2.10), p=0.003 (Table 4). Similarly, renal failure tended to be associated with higher risk of all-cause mortality; adjusted HR (95%CI)=1.44 (0.96-2.15), p=0.08. With regard to the primary outcome, there was no significant interaction between HF etiology and the worsening HF precipitants (p=0.95). Association and Interaction with Treatment Up-TitrationPatients with HF of hypertensive etiology had more often successful treatment up-titration, whereas patients with valvular HF were less often up-titrated (Table 1). Interaction tests for the primary outcome did not show treatment up-titration heterogeneity with regards to HF etiology and/or precipitant factors (all P-value>0.10) (Table 5 & Supplementary table 5).DiscussionIn ambulant and hospitalized patients with worsening heart failure, we assessed the clinical characteristics and outcome of different etiologies and precipitating factors. We found that patients with ischemic HF and worsening HF precipitated by renal failure had the worst prognosis. Treatment up-titration was beneficial irrespective of the HF etiology and/or precipitant factor. These findings suggest that both the HF etiology and the precipitating factors provide relevant and independent prognostic information, and that treatment up-titration may benefit all patients regardless of their HF etiology and/or precipitant.Heart Failure EtiologiesOur results align with previous reports suggesting that the most common HF etiology was ischemia PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5TaG9yZTwvQXV0aG9yPjxZZWFyPjIwMTU8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 6, 17. Patients with ischemic HF were older, had more cardiovascular risk factors, comorbidities and worse prognosis PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5CYXJ0PC9BdXRob3I+PFllYXI+MTk5NzwvWWVhcj48UmVj

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ADDIN EN.CITE.DATA 8, 9, 18, 19. Among patients with non-ischemic HF, valvular HF has also been associated with worse prognosis PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LYWppbW90bzwvQXV0aG9yPjxZZWFyPjIwMTY8L1llYXI+

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ADDIN EN.CITE.DATA 20, 21. Indeed, in our study, patients with a valvular HF had worse clinical status, illustrated by high proportion of anemia and impaired renal function, which may contribute to worse outcomes. In contrast, dilated cardiomyopathy was associated with better outcomes. Favorable trends in optimal treatments and low prevalence of comorbidities have been recently documented, potentially leading to lower rates of adverse outcomes PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5NZXJsbzwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 22, 23. In the present analysis, patients with a dilated cardiomyopathy were the youngest, had good renal function, and higher baseline MRA prescriptions, which may improve their prognosis among HF etiologies PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5GZXJyZWlyYTwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+

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ADDIN EN.CITE.DATA 24-26. Patients with HF of hypertensive etiology might have been more often successfully up-titrated. However, the potential benefits of up-titration were preserved irrespective of the HF etiology. Our study is the first to assess the association between HF etiologies and HF treatment up-titration. Since the implementation of these optimal pharmacological treatments ameliorates HF prognosis PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Qb25pa293c2tpPC9BdXRob3I+PFllYXI+MjAxNjwvWWVh

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ADDIN EN.CITE.DATA 27, our findings could encourage clinical physicians to HF treatment up-titration regardless of HF etiologies.Precipitating FactorsWith regard to the worsening HF precipitating factors, our results were also consistent with the previously published studies. Patients with HF precipitated by renal failure were elderly, had more frequent prior HF admission, more comorbidities, more severe congestion and worse prognosis PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5HQzwvQXV0aG9yPjxZZWFyPjIwMDg8L1llYXI+PFJlY051

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ADDIN EN.CITE.DATA 10, 28-31. Renal failure as a precipitant may be determined by clinical deterioration and bytherapeutic approaches such as diuretics and renin angiotensin aldosterone system inhibitor ADDIN EN.CITE <EndNote><Cite><Author>Zannad</Author><Year>2018</Year><RecNum>734</RecNum><DisplayText><style face="superscript">3</style></DisplayText><record><rec-number>734</rec-number><foreign-keys><key app="EN" db-id="xp5afsv2jtzde2ett01vrwr3pzv0atdwva5z" timestamp="1536574798">734</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Zannad, F.</author><author>Rossignol, P.</author></authors></contributors><titles><title>Cardiorenal Syndrome Revisited</title><secondary-title>Circulation</secondary-title></titles><periodical><full-title>Circulation</full-title></periodical><pages>929-44</pages><volume>138</volume><dates><year>2018</year></dates><urls></urls></record></Cite></EndNote>3. In the present analysis, patients with renal failure were not likely to receive ACEi/ARB, MRA and diuretics, suggesting that renal failure in this setting may not be considered to be a subsequent deterioration. In addition, patients with HF precipitated by noncompliance were younger, had lower LVEF and more frequent prior HF admissions PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BcnJpZ288L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxS

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ADDIN EN.CITE.DATA 5, 32. Both of precipitants, noncompliance (used as referent variable in our analyses) and hypertension, have been associated with more favorable outcomes PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BcnJpZ288L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxS

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ADDIN EN.CITE.DATA 5. Conversely, our results did not show worse prognosis of either ACS or infection as a precipitant. ACS and infection have been reported to be associated with worse short-term outcomes PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BcnJpZ288L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxS

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ADDIN EN.CITE PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BcnJpZ288L0F1dGhvcj48WWVhcj4yMDE3PC9ZZWFyPjxS

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ADDIN EN.CITE.DATA 5, prognostic implication of these precipitants may vary thus with term follow-up. Previous reports showed less adverse impact of renal failure in the context of initiation/up-titration of ACEi/ARB on clinical outcomes PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5UZXN0YW5pPC9BdXRob3I+PFllYXI+MjAxMTwvWWVhcj48

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ADDIN EN.CITE.DATA 33-35. Notwithstanding, the present analysis showed that the occurrence of renal failure may discourage physicians to up-titrate ACEi/ARB in the ambulatory and hospitalized management of HF. However, our results may also suggest that beneficial effect of up-titration of HF treatments is not influenced by precipitating causes, including renal failure. Interplay between Heart Failure Etiologies and Precipitating FactorsACS was a frequent precipitant in patients with ischemic HF, whereas hypertension was a frequent precipitant in patients with hypertensive HF, both of which were consistent with previous literature PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DaGlvbmNlbDwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+

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ADDIN EN.CITE.DATA 32, 36. In contrast, patients with valvular HF were more likely to be precipitated by AF and renal failure. The disappearance of atrial contraction in AF or extensive fluid volume overload in renal failure, may contribute to be decompensated phase in patients with valvular HF PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Hb2xpYXNjaDwvQXV0aG9yPjxZZWFyPjIwMTg8L1llYXI+

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ADDIN EN.CITE.DATA 20, 21, 37, 38. To the best of our knowledge, this is the first report to study and relate the HF etiologies to the worsening HF precipitating factors. We found no statistical interaction between the HF etiology and the worsening HF precipitants with regard to the study outcomes, suggesting that both entities may have independent prognostic value. Our observation may help potentially clinicians in better identifying the worsening HF precipitants in the light of the patients’ history and also in identifying those patients at higher risk of subsequent events.LimitationsOur study has several limitations. This is a post-hoc analysis of the BIOSTAT-CHF, hence the limitations inherent to observational data are present herein and causality cannot be inferred. By design, BIOSTAT-CHF enrolled patients not on optimal guideline medical therapy. Although, this condition is frequent, results may not be generalizable to patients on optimal therapy. The HF etiologies and precipitants were ascertained by the treating physicians, representing a diagnosis concordant with the clinical practice PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5XdTwvQXV0aG9yPjxZZWFyPjIwMDg8L1llYXI+PFJlY051

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ADDIN EN.CITE.DATA 39. A number of other factors previously reported as potentially precipitating decompensated HF were not captured in this study, because these are difficult to trace. These include, and are not limited to, dietary factors such as excessive salt intake and concomitant drugs such as steroidal and non-steroidal inflammatory drugs, frequently used as self-medications and therefore, under reported. The number of each individual precipitant was small, potentially having limited power of the associations. However, our results were consistent with previous reports, reinforcing the external validation of our findings.ConclusionsBoth etiology and precipitating factors for worsening HF may provide independent prognostic information. Patients with HF of ischemic etiology, and those with worsening HF precipitated by renal failure had the worst clinical prognosis. Treatment up-titration likely benefits patients irrespective of their etiology or precipitant factor. These findings may help in better identifying patients’ risk based both on their HF etiology and the factor that led to the visit, and should encourage the up-titration of life-saving therapies irrespective of the HF etiology and/or precipitant. FundingThis project was funded by a grant from the European Commission (FP7-242209-BIOSTAT-CHF; EudraCT 2010–020808–29). JPF, NG, PR and FZ are supported by a public grant overseen by the French National Research Agency (ANR) as part of the second “Investissements d’Avenir” program FIGHT-HF (reference: ANR-15-RHU-0004) and by the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE. And by Contrat de Plan Etat-Lorraine and FEDER Lorraine.DisclosuresMK and JPF have no conflicts of interest to disclose with regard to the present manuscript.PR: Personal fees (consulting) from Novartis, Relypsa, AstraZeneca, Grünenthal, Stealth Peptides, Fresenius, Idorsia, Vifor Fresenius Medical Care Renal Pharma, Vifor and CTMA; lecture fees from Bayer and CVRx; cofounder of CardioRenal AAV received consultancy fees and/or research grants from: Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, GSK, Novartis, Roche Diagnostics, ServierReference ADDIN EN.REFLIST 1.Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, Falk V, Gonzalez-Juanatey JR, Harjola VP, Jankowska EA, Jessup M, Linde C, Nihoyannopoulos P, Parissis JT, Pieske B, Riley JP, Rosano GM, Ruilope LM, Ruschitzka F, Rutten FH and van der Meer P. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC)Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. 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Importance of venous congestion for worsening of renal function in advanced decompensated heart failure. J Am Coll Cardiol. 2009;53:589-96.39.Wu JR, Moser DK, Chung ML and Lennie TA. Objectively measured, but not self-reported, medication adherence independently predicts event-free survival in patients with heart failure. J Card Fail. 2008;14:203-10.Table 1. Patient Characteristic according to the Heart Failure Etiologies?Global(N=2465)Ischemic HF (N=1102)Non-ischemic HFP-value betweenischemic vs non-ischemic P-value amongall etiologies???Overall (N=1363)Hypertensive HF (N=237)Valvular HF (N=184)DilatedCardiomyopathy (N=563)Other/Unknown(N=379)???Age, yrs68.4 ± 12.070.0 ± 10.667.1 ± 12.872.9 ± 10.371.7 ± 11.562.3 ± 12.768.1 ± 12.5<0.001<0.001Male, N (%)1805 (73.2 %)883 (80.1 %)922 (67.6 %)135 (57.0 %)103 (56.0 %)425 (75.5 %)259 (68.3 %)<0.001<0.001BMI, kg/m?27.9 ± 5.528.1 ± 5.327.8 ± 5.628.4 ± 5.626.5 ± 4.927.6 ± 5.328.2 ± 6.30.090.003Medical history Hypertension, N (%)1539 (62.4 %)767 (69.6 %)772 (56.6 %)230 (97.0 %)101 (54.9 %)251 (44.6 %)190 (50.1 %)<0.001<0.001 Diabetes mellitus, N (%)798 (32.4 %)447 (40.6 %)351 (25.8 %)87 (36.7 %)32 (17.4 %)136 (24.2 %)96 (25.3 %)<0.001<0.001 Myocardial infarction, N (%)940 (38.1 %)838 (76.0 %)102 (7.5 %)19 (8.0 %)12 (6.5 %)25 (4.4 %)46 (12.1 %)<0.001<0.001 Stroke, N (%)231 (9.4 %)135 (12.3 %)96 (7.0 %)20 (8.4 %)17 (9.2 %)27 (4.8 %)32 (8.4 %)<0.001<0.001 PAD, N (%)267 (10.8 %)169 (15.3 %)98 (7.2 %)26 (11.0 %)16 (8.7 %)26 (4.6 %)30 (7.9 %)<0.001<0.001 COPD, N (%)423 (17.2 %)204 (18.5 %)219 (16.1 %)38 (16.0 %)29 (15.8 %)88 (15.6 %)64 (16.9 %)0.110.59Prior HF admission, N (%)780 (31.6 %)383 (34.8 %)397 (29.1 %)71 (30.0 %)56 (30.4 %)181 (32.1 %)89 (23.5 %)0.0030.002Clinical profile NYHA class ≥ III, N (%)1491 (62.2 %)680 (63.1 %)811 (61.4 %)145 (63.3 %)127 (71.3 %)321 (58.5 %)218 (59.9 %)0.410.03 Rales, N (%)240 (19.0 %)107 (18.8 %)133 (19.1 %)25 (18.4 %)18 (16.2 %)34 (13.4 %)56 (28.9 %)0.880.001 Juglar venous pressure, N (%)544 (31.5 %)249 (31.4 %)295 (31.6 %)43 (29.7 %)54 (41.2 %)112 (28.5 %)86 (32.6 %)0.920.10 Leg edema, N (%)2063 (83.7 %)923 (83.8 %)1140 (83.7 %)196 (82.7 %)157 (85.3 %)472 (83.8 %)315 (83.3 %)0.970.97 Systolic blood pressure, mmHg124.8 ± 21.9124.2 ± 20.9125.3 ± 22.6140.6 ± 26.8123.0 ± 21.2121.0 ± 19.2123.4 ± 21.30.39<0.001 Heart rate, bpm79.9 ± 19.575.9 ± 16.183.1 ± 21.384.2 ± 20.986.1 ± 22.181.3 ± 19.883.8 ± 23.0<0.001<0.001Hospitalized patients, N (%)1655 (67.1 %)706 (64.0 %)949 (69.6 %)156 (65.8 %)148 (80.4 %)366 (65.0 %)279 (73.6 %)0.003<0.001Echocardiogram LVEF, %31.0 ± 10.530.4 ± 9.031.4 ± 11.636.8 ± 11.637.3 ± 14.726.7 ± 7.832.5 ± 11.80.85<0.001 LVEF ≤ 40%, N (%)1973 (89.7 %)915 (93.8 %)1058 (86.4 %)170 (77.3 %)116 (69.0 %)517 (98.3 %)255 (82.3 %)<0.001<0.001 MR ≥ moderate, N (%)1103 (47.1 %)483 (46.4 %)620 (47.7 %)98 (43.0 %)96 (54.5 %)272 (50.8 %)154 (42.8 %)0.510.02Medication at baseline ACEi or ARB, N (%)1783 (72.3 %)773 (70.1 %)1010 (74.1 %)168 (70.9 %)123 (66.8 %)445 (79.0 %)274 (72.3 %)0.030.001 Beta-blocker, N (%)2059 (83.5 %)964 (87.5 %)1095 (80.3 %)177 (74.7 %)136 (73.9 %)477 (84.7 %)305 (80.5 %)<0.001<0.001 MRA, N (%)1312 (53.2 %)601 (54.5 %)711 (52.2 %)98 (41.4 %)79 (42.9 %)346 (61.5 %)188 (49.6 %)0.24<0.001 Loop diuretics, N (%)2454 (99.6 %)1101 (99.9 %)1353 (99.3 %)234 (98.7 %)184 (100.0 %)558 (99.1 %)377 (99.5 %)0.040.04 Digoxin, N (%)481 (19.5 %)150 (13.6 %)331 (24.3 %)46 (19.4 %)48 (26.1 %)145 (25.8 %)92 (24.3 %)<0.001<0.001Medication at 3 months ACEi/ARB ≥50% target dose1286 (52.2 %)572 (51.9 %) 714 (52.4 %)154 (65.0 %)70 (38.0 %)297 (52.8 %)193 (50.9 %)0.81<0.001 % ACEi/ARB target dose50.0(25.0 - 66.7)50.0(16.7 - 62.5)50.0(25.0 – 75.0)50.0(25.0 - 100.0)25.0(12.5 - 50.0)50.0(25.0 - 75.0)50.0(25.0 - 62.5)0.08<0.001 Beta-blocker ≥50% target dose879 (35.7 %)404 (36.7 %)475 (34.8 %)89 (37.6 %)64 (34.8 %)185 (32.9 %)137 (36.1 %)0.350.58 % beta-blocker target dose25.0(12.5 - 50.0)25.0(12.5 - 50.0)25.0(12.5 – 50.0)25.0(12.5 - 50.0)25.0(8.3 - 50.0)25.0(12.5 - 50.0)25.0(12.5 - 50.0)0.620.36Laboratory Hemoglobin, g/dl13.2 ± 1.913.0 ± 1.913.3 ± 1.913.0 ± 1.812.8 ± 1.913.6 ± 1.813.4 ± 1.90.002<0.001 Blood urea nitrogen, mg/dl41.8 ± 32.644.8 ± 34.739.3 ± 30.637.1 ± 26.343.6 ± 36.440.1 ± 30.537.4 ± 29.7<0.001<0.001 eGFR, mL/min/1.73m?62.0 ± 24.358.9 ± 23.264.5 ± 24.861.2 ± 24.158.6 ± 22.868.5 ± 25.763.9 ± 23.9<0.001<0.001 Sodium, mmol/l139.1 ± 4.0139.0 ± 3.9139.3 ± 4.0139.8 ± 4.3139.0 ± 3.7139.1 ± 4.0139.3 ± 4.10.0440.02 Potassium, mmol/l4.3 ± 0.64.3 ± 0.64.2 ± 0.64.2 ± 0.64.2 ± 0.64.3 ± 0.64.2 ± 0.50.020.07 NT-proBNP, pg/ml4280(2359-8475)3988(2288-8220)4341(2400-8576)3808(2366-7539)4883(2621-8282)4339(1938-9019)4443(2604-8538)0.610.51Values are Mean ± SD, n (%) or median (25th to 75th percentile)BMI, body mass index; PAD, peripheral artery disease; COPD, chronic obstructive pulmonary disease; HF, heart failure; NYHA, New York Heart Association; ECG, electrocardiogram; LVEF, left ventricular ejection fraction; MR, mitral regurgitation; ACEi, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; MRA, mineralocorticoid receptor antagonist; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal prohormone brain natriuretic peptide.Table 2. Prevalence of Precipitating Factors according to the Heart Failure EtiologiesIschemic HF(N=1102)Hypertensive HF(N=237)Valvular HF(N=184)DilatedCardiomyopathy(N=563)Other/Unknown(N=379)P-valuePrecipitating factor Acute coronary syndrome, N (%)94 (8.6 %)4 (1.7 %)2 (1.1 %)5 (0.9 %)16 (4.2 %)<0.001 Atrial fibrillation, N (%)199 (18.1 %)72 (30.5 %)71 (38.8 %)97 (17.3 %)138 (36.5 %)<0.001 Hypertension, N (%)43 (3.9 %)51 (21.5 %)9 (4.9 %)12 (2.1 %)19 (5.0 %)<0.001 Renal failure, N (%)136 (12.4 %)26 (11.0 %)28 (15.2 %)36 (6.4 %)42 (11.1 %)0.001 Infection, N (%)59 (5.4 %)13 (5.5 %)10 (5.6 %)20 (3.6 %)26 (6.9 %)0.25 Noncompliance, N (%)160 (14.5 %)25 (10.5 %)20 (10.9 %)86 (15.3 %)49 (12.9 %)0.27 Table 3. Cox Proportional Hazard Models of the Heart Failure Etiologies for the Clinical OutcomesComposite outcomeUnadjustedAdjusted forBIOSTAT-CHF risk scoreHR (95% CI)P-valueHR (95% CI)P-value Dilated cardiomyopathy(reference)?(reference)? Ischemic HF1.76 (1.48 - 2.10)<0.0011.34 (1.12 - 1.60)0.001 Hypertensive HF1.49 (1.16 - 1.91)0.0021.27 (0.99 - 1.62)0.06 Valvular HF1.85 (1.43 - 2.40)<0.0011.21 (0.93 - 1.57)0.16 Other/Unknown1.32 (1.05 - 1.66)0.021.17 (0.93 - 1.46)0.19All-cause deathUnadjustedAdjusted forBIOSTAT-CHF risk scoreHR (95% CI)P-valueHR (95% CI)P-value Dilated cardiomyopathy(reference)?(reference)? Ischemic HF1.72 (1.38 - 2.14)<0.0011.05 (0.84 - 1.32)0.66 Hypertensive HF1.43 (1.04 - 1.95)0.031.26 (0.92 - 1.73)0.15 Valvular HF1.58 (1.13 - 2.21)0.011.12 (0.80 - 1.56)0.52 Other/Unknown1.34 (1.01 - 1.78)0.041.15 (0.87 - 1.53)0.32HR, hazard ratio; CI, confidence interval; HF, heart failure.Table 4. Cox Proportional Hazard Models of Individual Precipitants for the Clinical OutcomesComposite outcomeUnadjustedAdjusted forBIOSTAT-CHF risk scoreAdjusted for BIOSTAT-CHFrisk score and Ischemic etiologyP-value forinteractionwith HF etiologiesHR (95% CI)P-valueHR (95% CI)P-valueHR (95% CI)P-valueNoncompliance(reference)(reference)(reference)0.95Acute coronary syndrome1.08 (0.69 - 1.71)0.741.18 (0.75 - 1.87)0.481.10 (0.69 - 1.75)0.68Atrial fibrillation1.10 (0.82 - 1.46)0.541.01 (0.76 - 1.35)0.951.04 (0.78 - 1.39)0.78Hypertension1.03 (0.66 - 1.61)0.901.37 (0.88 - 2.15)0.171.39 (0.89 - 2.18)0.15Renal failure2.61 (1.87 - 3.65)<0.0011.48 (1.04 - 2.09)0.031.49 (1.05 - 2.10)0.03Infection1.31 (0.85 - 2.01)0.230.97 (0.62 - 1.49)0.870.97 (0.63 - 1.50)0.88All-cause deathUnadjustedAdjusted forBIOSTAT-CHF risk scoreAdjusted for BIOSTAT-CHFrisk score and Ischemic etiologyP-value forinteractionwith HF etiologiesHR (95% CI)P-valueHR (95% CI)P-valueHR (95% CI)P-valueNoncompliance(reference)(reference)(reference)0.67Acute coronary syndrome1.18 (0.69 - 2.01)0.541.22 (0.71 - 2.07)0.471.24 (0.72 - 2.12)0.44Atrial fibrillation1.06 (0.75 - 1.51)0.731.04 (0.73 - 1.47)0.851.03 (0.72 - 1.46)0.89Hypertension0.54 (0.27 - 1.07)0.080.78 (0.39 - 1.55)0.480.78 (0.39 - 1.55)0.47Renal failure2.83 (1.92 - 4.17)<0.0011.44 (0.97 - 2.16)0.071.44 (0.96 - 2.15)0.08Infection1.45 (0.88 - 2.40)0.150.99 (0.59 - 1.64)0.950.99 (0.59 - 1.64)0.95HR, hazard ratio; CI, confidence interval; HF, heart failure. Table 5. Cox Proportional Hazard Models for the Primary Outcome according to Successful Up-titration of ≥50% of Guideline-Recommended Target DosesIschemic vs Non-ischemic HFRenal failure vs Other precipitantsAdjusted HR (95% CI)P-value forinteractionAdjusted HR (95% CI)P-value forinteractionOverall1.19 (1.05 - 1.34)1.44 (1.09 - 1.91)ACEi/ARB ≥50% of target doseUnsuccessful1.23 (1.05 - 1.45)0.761.56 (1.11 - 2.18)0.98Successful1.12 (0.93 - 1.37)1.13 (0.67 - 1.88)BB ≥50% of target doseUnsuccessful1.14 (0.98 - 1.33)0.291.37 (0.98 - 1.93)0.17Successful1.28 (1.03 - 1.60)1.88 (1.11 - 3.19)ACEi/ARB and BB ≥50% of target doseUnsuccessful1.17 (1.02 - 1.34)0.241.48 (1.10 - 1.99)0.88Successful1.27 (0.92 - 1.75)1.20 (0.51 - 2.83) HF, heart failure; HR, hazard ratio; CI, confidence interval; ACEi, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BB, beta-blocker.Figure 1. Flowchart of Patients from the BIOSTAT-CHFcentercenter00Figure 2. Survival Curves for the Primary Outcome according to the Heart Failure Etiologies and Individual Precipitating Factorscenterbottom00Supplementary table 1. Heart Failure Etiologies and Precipitating Factors in the Protocol of BIOSTAT-CHF5 MEDICAL HISTORY: HEART FAILURE Etiology assessedNo ?0 Yes ?1Ischemic heart disease Hypertension Cardiomyopathy Valvular disease Unknown etiology Other Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 Primary ?1 Contributory ?2 Not Present ?3 Unknown ?4 7 FAMILY HISTORY7.7 Cause of the Heart Failure is a dilated cardiomyopathy? No ?0 Yes ?1 10 INPATIENT HOSPITALIZATION / OUTPATIENT CLINIC 10.4 Precipitating factors for this hospitalization / outpatient clinic visit? No ?0 Yes ?1 If Yes, specify: ??????????????10.4.1 Acute coronary syndrome Present ?1 Absent ?2 Not certain ?3 10.4.2 Non-Compliance (behavior, drugs) Present ?1 Absent ?2 Not certain ?3 10.4.3 Atrial Fibrillation Present ?1 Absent ?2 Not certain ?3 10.4.4 Ventricular Arrhythmia Present ?1 Absent ?2 Not certain ?3 10.4.5 Infection Present ?1 Absent ?2 Not certain ?3 10.4.6 Uncontrolled hypertension Present ?1 Absent ?2 Not certain ?3 10.4.7 Brady arrhythmias Present ?1 Absent ?2 Not certain ?3 10.4.8 Renal dysfunction Present ?1 Absent ?2 Not certain ?3 10.4.9 Iatrogenic Present ?1 Absent ?2 Not certain ?3 10.4.10 Other? Present ?1 Absent ?2 Not certain ?3 If Yes, specify ?????????????? CASE REPORT FORM A systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF)Protocol version 2.6 Amended, dated 25 April 2012 CRF version 2.0.0, dated: 21 December 2012Supplementary table 2. Patients Characteristics according to Individual Precipitating FactorsGlobal(N=845)ACS(N=68)Atrial fibrillation(N=353)Hypertension(N=67)Renal failure(N=100)Infection(N=64)Noncompliance(N=193)p-valueAge, yrs68.4 ± 12.069.1 ± 12.071.2 ± 10.668.5 ± 12.371.4 ± 13.068.7 ± 11.263.2 ± 12.5<0.001Male, N (%)1805 (73.2 %)46 (67.6 %)250 (70.8 %)40 (59.7 %)73 (73.0 %)39 (60.9 %)147 (76.2 %)0.07Body mass index, kg/m?27.9 ± 5.527.5 ± 5.028.5 ± 5.528.0 ± 5.027.5 ± 4.926.8 ± 4.628.3 ± 5.60.21Medical history Hypertension, N (%)1539 (62.4 %)40 (58.8 %)204 (57.8 %)64 (95.5 %)64 (64.0 %)35 (54.7 %)112 (58.0 %)<0.001 Diabetes mellitus, N (%)798 (32.4 %)27 (39.7 %)100 (28.3 %)23 (34.3 %)44 (44.0 %)22 (34.4 %)72 (37.3 %)0.04 Myocardial infarction, N (%)940 (38.1 %)53 (77.9 %)85 (24.1 %)16 (23.9 %)46 (46.0 %)26 (40.6 %)67 (34.7 %)<0.001 Stroke, N (%)231 (9.4 %)5 (7.4 %)46 (13.0 %)2 (3.0 %)12 (12.0 %)12 (18.8 %)17 (8.8 %)0.04 PAD, N (%)267 (10.8 %)7 (10.3 %)35 (9.9 %)11 (16.4 %)18 (18.0 %)9 (14.1 %)25 (13.0 %)0.27 COPD, N (%)423 (17.2 %)10 (14.7 %)54 (15.3 %)9 (13.4 %)18 (18.0 %)24 (37.5 %)29 (15.0 %)<0.001Prior HF admission, N (%)780 (31.6 %)8 (11.8 %)104 (29.5 %)14 (20.9 %)46 (46.0 %)18 (28.1 %)68 (35.2 %)<0.001Clinical profile NYHA class ≥ III, N (%)1491 (62.2 %)32 (50.0 %)234 (67.8 %)36 (57.1 %)75 (78.9 %)51 (83.6 %)123 (64.7 %)<0.001 Rales, N (%)240 (19.0 %)9 (20.5 %)44 (21.9 %)6 (13.0 %)14 (25.9 %)14 (26.9 %)14 (14.1 %)0.25 Juglar venous pressure, N (%)543 (31.5 %)9 (20.0 %)78 (32.5 %)10 (21.7 %)29 (35.8 %)21 (48.8 %)36 (27.5 %)0.03 Leg edema, N (%)2063 (83.7 %)50 (73.5 %)305 (86.4 %)55 (82.1 %)90 (90.0 %)57 (89.1 %)155 (80.3 %)0.02 Systolic blood pressure, mmHg124.8 ± 21.9119.3 ± 22.3123.7 ± 19.4169.9 ± 25.8118.9 ± 20.6122.0 ± 22.8121.4 ± 18.0<0.001 Heart rate, bpm79.9 ± 19.575.3 ± 15.589.0 ± 24.684.0 ± 21.373.9 ± 11.984.7 ± 22.076.7 ± 16.1<0.001Hospitalized patients, N (%)682 (80.7 %)65 (95.6 %)283 (80.2 %)56 (83.6 %)86 (86.0 %)63 (98.4 %)129 (66.8 %)<0.001Echocardiogram LVEF, %31.0 ± 10.531.8 ± 7.933.9 ± 12.134.9 ± 10.231.8 ± 11.031.3 ± 15.228.5 ± 8.3<0.001 MR ≥ moderate, N (%)1103 (47.1 %)18 (27.7 %)178 (52.0 %)20 (30.3 %)46 (50.0 %)26 (43.3 %)90 (49.2 %)<0.001Medication at baseline ACEi or ARB, N (%)1783 (72.3 %)55 (80.9 %)252 (71.4 %)49 (73.1 %)58 (58.0 %)42 (65.6 %)153 (79.3 %)0.002 %ACEi or ARB target dose25.0(0.0 - 50.0)25.0(12.5 - 50.0)25.0(0 - 50.0)50.0(0 - 100.0)15.5(0 - 50.0)25.0(0 - 50.0)25.0(12.5 - 50.0)0.03 Beta-blocker, N (%)2059 (83.5 %)60 (88.2 %)290 (82.2 %)52 (77.6 %)79 (79.0 %)46 (71.9 %)170 (88.1 %)0.03 %beta-blocker target dose25.0(6.2 - 47.5)25.0(12.5 - 37.5)25.0(6.2 - 50.0)15.6(4.2 - 50.0)12.5(4.2 - 50.0)12.5(0 - 48.8)12.5(6.2 - 25.0)0.22 MRA, N (%)1312 (53.2 %)29 (42.6 %)185 (52.4 %)27 (40.3 %)39 (39.0 %)35 (54.7 %)126 (65.3 %)<0.001 Loop diuretics dose, mg40.0(20.0 - 80.0)40.0(25.0 - 80.0)40.0(8.0 - 80.0)40.0(20.0 - 80.0)40.0(20.0 - 100.0)40.0(25.0 - 80.0)40.0(40.0 - 75.0)0.02Medication at 3 months ACEi/ARB ≥50% target dose1286 (52.2 %)36 (52.9 %)172 (48.7 %)45 (67.2 %)31 (31.0 %)33 (51.6 %)102 (52.8 %)<0.001 %ACEi/ARB target dose50.0(25.0 - 66.7)50.0(20.8 - 50.0)37.5(25.0 - 50.0)50.0(25.0 - 100.0)20.8(0 - 50.0)50.0(25.0 - 75.0)50.0(25.0 - 62.5)<0.001 Beta-blocker ≥50% target dose879 (35.7 %)16 (23.5 %)134 (38.0 %)26 (38.8 %)36 (36.0 %)19 (29.7 %)49 (25.4 %)0.02 %beta-blocker target dose25.0(12.5 - 50.0)25.0(14.6 - 47.5)25.0(12.5 - 50.0)25.0(12.5 - 50.0)25.0(8.3 - 50.0)25.0(6.2 - 50.0)25.0(12.5 - 50.0)0.06Laboratory Hemoglobin, g/dl13.2 ± 1.912.7 ± 1.813.5 ± 1.913.6 ± 1.511.9 ± 2.112.4 ± 1.713.5 ± 1.9<0.001 Blood urea nitrogen, mg/dl41.8 ± 32.634.2 ± 33.136.2 ± 28.231.7 ± 26.561.5 ± 38.630.7 ± 19.741.8 ± 27.7<0.001 eGFR, mL/min/1.73m?62.0 ± 24.368.6 ± 20.065.8 ± 21.268.1 ± 26.530.5 ± 8.968.3 ± 36.067.7 ± 20.9<0.001 Sodium, mmol/l139.1 ± 4.0138.8 ± 3.4139.4 ± 3.8140.3 ± 3.4138.2 ± 4.3137.2 ± 4.6139.3 ± 3.9<0.001 Potassium, mmol/l4.3 ± 0.64.2 ± 0.54.2 ± 0.54.2 ± 0.64.4 ± 0.74.0 ± 0.64.4 ± 0.7<0.001 NT-proBNP, pg/ml4280(2359 - 8475)3408(1941 - 7764)3899(2559 - 7419)4988(3183 - 7921)7500(3723 - 15805)7255(3290 - 14111)5000(2090 - 8105)<0.001 Values are Mean ± SD, n (%) or median (25th to 75th percentile)ACS, acute coronary syndrome; PAD, peripheral artery disease; COPD, chronic obstructive pulmonary disease; HF, heart failure; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction; MR, mitral regurgitation; ACEi, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; MRA, mineralocorticoid receptor antagonist; eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal prohormone brain natriuretic peptide.Supplementary table 3. Cox Proportional Hazard Models of the Heart Failure Etiologies after Adjusting for BIOSTAT-CHF risk score and Renal FailureComposite outcomeAdjusted forBIOSTAT-CHF risk scoreAdjusted for BIOSTAT-CHFrisk score and renal failureP-value forinteraction with renal failureHR (95% CI)P-valueHR (95% CI)P-value Dilated cardiomyopathy(reference)?(reference)0.15 Ischemic HF1.34 (1.12 - 1.60)0.0011.34 (1.12 – 1.60)0.001 Hypertensive HF1.27 (0.99 - 1.62)0.061.26 (0.98 – 1.62)0.07 Valvular HF1.21 (0.93 - 1.57)0.161.21 (0.93 – 1.57)0.16 Other/Unknown1.17 (0.93 - 1.46)0.191.16 (0.92 – 1.46)0.21All-cause deathAdjusted forBIOSTAT-CHF risk scoreAdjusted for BIOSTAT-CHFrisk score and renal failureP-value forinteraction with renal failureHR (95% CI)P-valueHR (95% CI)P-value Dilated cardiomyopathy(reference)?(reference)?0.48 Ischemic HF1.05 (0.84 - 1.32)0.661.06 (0.85 – 1.33)0.62 Hypertensive HF1.26 (0.92 - 1.73)0.151.26 (0.92 – 1.73)0.14 Valvular HF1.12 (0.80 - 1.56)0.521.12 (0.80 – 1.56)0.54 Other/Unknown1.15 (0.87 - 1.53)0.321.15 (0.87 – 1.52)0.33HR, hazard ratio; CI, confidence interval; HF, heart failure.Supplementary table 4. Association between Heart Failure Etiologies and Up-titration of ≥50% of Guideline-Recommended Target DosesUnivariableMultivariable modelACEi/ARBOR95% CIP-valueOR95% CIP-value Unknown/other(reference)(reference) Ischemic HF1.040.85 - 1.270.740.970.73 - 1.290.86 Hypertensive HF1.791.28 - 2.50<0.0011.310.88 - 1.940.18 Valvular HF0.590.41 - 0.850.0040.700.46 - 1.050.09 Dilated cardiomyopathy1.080.83 - 1.400.580.910.67 - 1.240.55Beta-blockerOR95% CIP-valueOR95% CIP-value Unknown/other(reference)(reference) Ischemic HF1.020.80 - 1.310.861.040.78 – 1.380.79 Hypertensive HF1.060.76 - 1.490.720.880.59 – 1.290.50 Valvular HF0.940.65 - 1.360.750.990.66 – 1.490.97 Dilated cardiomyopathy0.860.66 - 1.140.300.780.57 – 1.070.12OR, odd ratio; CI, confidence interval; ACEi, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; HF, heart failure.Multivariable model: adjusted for age, sex, body mass index, diabetes mellitus, left ventricular ejection fraction, systolic blood pressure, potassium and estimated glomerular filtration rate. Supplementary table 5. Interaction for the Primary Outcome between Heart Failure Treatment, Heart Failure Etiology and PrecipitantP-value for interactionwith HF etiologywith precipitantACEi/ARB ≥50% of target dose0.790.29Beta-blocker ≥50% of target dose0.550.41ACEi/ARB and beta-blocker ≥50% of target dose0.560.64HF, heart failure; ACEi, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker.Supplementary table 6. Cox Proportional Hazard Models of the Heart Failure Etiologies for the Primary Outcome in Ambulant and Hospitalized PatientsAmbulant PatientsHospitalized PatientsP-value forinteraction withambulatory/hospitalizationNEvent (%)HR (95% CI)P-valueNEvent (%)HR (95% CI)P-valueEtiologies Dilated cardiomyopathy19717.3(reference)36635.8(reference)0.51 Ischemic HF39734.31.46 (0.99 - 2.14)0.05670552.11.32 (1.08 - 1.61)0.007 Hypertensive HF8140.71.50 (0.92 - 2.44)0.1115642.91.17 (0.87 - 1.57)0.31 Valvular HF3641.71.48 (0.80 - 2.74)0.21148481.14 (0.85 - 1.52)0.39 Other/Unknown100261.26 (0.75 - 2.10)0.3827939.41.11 (0.86 - 1.43)0.42HR, hazard ratio; CI, confidence interval; HF, heart failure. Cox hazard model for the composite of all-cause mortality or HF re-hospitalization was adjusted for BIOSTAT-CHF risk score PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Wb29yczwvQXV0aG9yPjxZZWFyPjIwMTc8L1llYXI+PFJl

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ADDIN EN.CITE.DATA 16.centerbottom00Supplementary figure 1. Survival Curves for the Primary Outcome according to the Heart Failure Etiologies and Individual Precipitating Factors ................
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