Literature DB >> 29535141

Predictors and Prognostic Value of Worsening Renal Function During Admission in HFpEF Versus HFrEF: Data From the KorAHF (Korean Acute Heart Failure) Registry.

Jeehoon Kang1,2,3, Jin Joo Park1, Young-Jin Cho1, Il-Young Oh1, Hyun-Ah Park4, Sang Eun Lee5, Min-Seok Kim5, Hyun-Jai Cho2, Hae-Young Lee2, Jin Oh Choi6, Kyung-Kuk Hwang7, Kye Hun Kim8, Byung-Su Yoo9, Seok-Min Kang10, Sang Hong Baek11, Eun-Seok Jeon6, Jae-Joong Kim5, Myeong-Chan Cho7, Shung Chull Chae12, Byung-Hee Oh5, Dong-Ju Choi13.   

Abstract

BACKGROUND: Worsening renal function (WRF) is associated with adverse outcomes in patients with heart failure. We investigated the predictors and prognostic value of WRF during admission, in patients with preserved ejection fraction (HFpEF) versus those with reduced ejection fraction (HFrEF). METHODS AND
RESULTS: A total of 5625 patients were enrolled in the KorAHF (Korean Acute Heart Failure) registry. WRF was defined as an absolute increase in creatinine of ≥0.3 mg/dL. Transient WRF was defined as recovery of creatinine at discharge, whereas persistent WRF was indicated by a nonrecovered creatinine level. HFpEF and HFrEF were defined as a left ventricle ejection fraction ≥50% and ≤40%, respectively. Among the total population, WRF occurred in 3101 patients (55.1%). By heart failure subgroup, WRF occurred more frequently in HFrEF (57.0% versus 51.3%; P<0.001 in HFrEF and HFpEF). Prevalence of WRF increased as creatinine clearance decreased in both heart failure subgroups. Among various predictors of WRF, chronic renal failure was the strongest predictor. WRF was an independent predictor of adverse in-hospital outcomes (HFrEF: odds ratio; 2.75; 95% confidence interval, 1.50-5.02; P=0.001; HFpEF: odds ratio, 9.48; 95% confidence interval, 1.19-75.89; P=0.034) and 1-year mortality (HFrEF: hazard ratio, 1.41; 95% confidence interval, 1.12-1.78; P=0.004 versus HFpEF: hazard ratio, 1.72; 95% confidence interval, 1.23-2.42; P=0.002). Transient WRF was a risk factor for 1-year mortality, whereas persistent WRF had no additive risk compared to transient WRF.
CONCLUSIONS: In patients with acute heart failure patients, WRF is an independent predictor of adverse in-hospital and follow-up outcomes in both HFrEF and HFpEF, though with a different effect size. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01389843.
© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Entities:  

Keywords:  heart failure; heart failure with preserved ejection fraction; heart failure with reduced ejection fraction; renal function

Mesh:

Substances:

Year:  2018        PMID: 29535141      PMCID: PMC5907555          DOI: 10.1161/JAHA.117.007910

Source DB:  PubMed          Journal:  J Am Heart Assoc        ISSN: 2047-9980            Impact factor:   5.501


Clinical Perspective

What Is New?

From a prospective, multicenter cohort, the KorAHF (Korean Acute Heart Failure) registry, worsening renal function (WRF) occurred in 55.1%, and patients with reduced ejection fraction had a higher rate of WRF than did the patients with preserved ejection fraction (HFpEF). WRF was an independent predictor of adverse in‐hospital outcomes (defined as all‐cause mortality or aggravation of heart failure during hospitalization) in both patients with reduced ejection fraction and HFpEF, whereas the effect size of WRF was 3‐fold larger in HFpEF. WRF was associated with 3‐month and 1‐year mortality in both patients with reduced ejection fraction and HFpEF. Regarding the degree of WRF (transient WRF and persistent WRF), transient WRF was an independent risk factor for long‐term mortality, whereas persistent WRF had no additive risk compared with transient WRF.

What Are the Clinical Implications?

Our results reflect the rate of WRF in real‐world heart failure patients; more than one half of acute heart failure patients experienced WRF, which was associated with adverse in‐hospital outcomes and adverse 1‐year mortality. We compared the effect size of WRF for adverse outcomes in acute heart failure patients with patients with reduced ejection fraction versus HFpEF, showing that WRF had a larger effect size on adverse outcomes in HFpEF patients. Patients with transient WRF had a higher risk for 1‐year mortality compared with those without WRF, whereas persistent WRF was not a risk factor compared with transient WRF.

Introduction

Worsening renal function (WRF) represents a deterioration of renal function over time, and it is associated with worse outcomes in patients with acute and chronic heart failure (HF).1, 2 Previous reports have shown that WRF is associated with death and HF hospitalization.3, 4 Bidirectional interactions exist between heart disease and kidney disease, referred to as cardiorenal syndrome,5 and neurohumoral maladaptation and decreased renal perfusion are 2 of the discussed mechanisms.6 Among patients with HF, up to 50% of the patients have normal or near normal left ventricular ejection fraction (LVEF), known as HF with preserved ejection fraction (HFpEF).7 They have a prognosis similar to those with HF with reduced ejection fraction (HFrEF).8 Whether HFpEF and HFrEF represent distinct forms of HF, or exist as part of an “HF spectrum,” has yet to be established.9 However, the different patterns of chamber remodeling and disparate responses to medical therapies suggest that they are 2 discrete disease processes. Furthermore, patients with HFrEF have higher B‐type natriuretic peptide (BNP) levels than patients with HFpEF, which suggests that they have a higher degree of neurohumoral activity.10, 11 This prompts consideration of whether the clinical significance of WRF may be dependent on HF type. Until now, the predictors of WRF and prognostic value of WRF on outcomes have not been well established in either type of HF. Therefore, in this study, we sought to evaluate the influence of WRF in acute HF patients according to HF type.

Methods

Data, analytical methods, and study materials will not be made available to other researchers for purposes of reproducing the results or replicating the procedure, because the data are protected by the Korean Ministry of Health and Welfare.

Study Design and Population

The KorAHF (Korean Acute Heart Failure) registry was a prospective, multicenter cohort study that was designed to describe patient characteristics, current treatments, and short‐ and long‐term patient outcomes among Korean patients with acute HF. A total of 5625 patients were enrolled from the KorAHF registry from March 2011 to February 2014 at 10 tertiary centers. Detailed information on the study design and results has been previously reported elsewhere.4, 12 Briefly, patients with signs or symptoms of HF and either lung congestion, objective findings of left ventricular systolic dysfunction, or structural heart disease were eligible for the study. Detailed variables were collected at admission, and events including all‐cause mortality, mortality from HF aggravation, and rehospitalization for HF aggravation were recorded after discharge. Follow‐up data were collected from patients by the attending physician at 30 days and 3, 6, 12, 24, 36, 48, and 60 months after discharge. The study is currently continuing follow‐up. The study protocol was approved by the ethics committee at each participating center and was conducted according to the principles of the Declaration of Helsinki. All patients provided written informed consent for participation in the registry.

Study End Points and Definitions

Clinical outcomes included adverse in‐hospital outcomes (defined as all‐cause mortality or aggravation of HF during hospitalization) and all‐cause mortality during follow‐up. All‐cause mortality was analyzed by short‐term (3‐month) and long‐term (1‐year) events. Despite the absence of expert consensus in terms of the definition of WRF, WRF was defined as an absolute increase in creatinine of 0.3 mg/dL or more, as per previous studies.13 In the present study, WRF was limited to those occurring during admission. Transient WRF was defined as a recovery of creatinine level at discharge, by more than 0.3 mg/dL compared with the peak level during admission. Persistent WRF was defined as a nonrecovered creatinine level. Stages of glomerular filtration rate (GFR) were defined according to the Kidney Disease Outcomes Quality Initiative (KDOQI) Clinical Practice Guidelines for chronic renal failure (CRF). According to GFR at admission, GFR ≥60 mL/min per 1.73 m2, GFR 30 to 59 mL/min per 1.73 m2, and GFR <30 mL/min per 1.73 m2 were defined as “mildly,” “moderately,” and as “severely decreased GFR,” respectively. HFpEF and HFrEF were defined as LVEF ≥50% and LVEF≤40%, respectively.7 Patients with a 40%

Statistical Analyses

All variables and outcome analyses were based on WRF. Data are presented as numbers and frequencies for categorical variables and as means±SD for continuous variables. For comparison among groups, the χ2 test (or Fisher's exact test when any expected count was <5 for a 2×2 table) for categorical variables and the unpaired Student t test or 1‐way analysis of variance for continuous variables were applied. To estimate the predictors of WRF, and to predict the independent effect of WRF on adverse in‐hospital outcomes, we used the multivariable logistic regression model using a step‐wise algorithm. Variables found to be statistically significant in the univariate analysis were included in the multivariable model, excluding variables that were closely related to other clinical variables. As a result, variables such as sex, old age, body mass index, hypertension, diabetes mellitus, CRF, previous myocardial infarction, New York Heart Association grade, LVEF (HFrEF or HFpEF), laboratory results at admission (ie, white blood cell count, hemoglobin, sodium, BNP (or N‐terminal pro‐brain‐type natriuretic peptide, C‐reactive protein levels), and intravenous medications during admission (ie, diuretics, inotropes, and vasodilators) were included in the model. Assumptions of the logistic regression model (eg, dichotomous dependent variable, independence in each observation, linear relationship between continuous independent variables and the logit transformation of the dependent variable, and multicollinearity) were tested. The Cox and Snell R Square, Nagelkerke R square, and Hosmer‐Lemeshow goodness‐of‐fit test were used to evaluate model calibration. A 2‐sided probability value <0.05 was considered to estimate statistically significant differences. Statistical tests were performed using SPSS (v22.0; IMB Corporation, Armonk, NY) and Stata (version 10; 2007; StataCorp LP, College Station, TX).

Results

A total of 5625 patients were enrolled in the KorAHF registry. Mean age was 68.5±14.5 years, with a mean LVEF of 37.7±15.6%, and the most common etiology of HF was ischemic heart disease (2113 patients [37.6%]; Table 1). By definition, 3105 patients (55.2%) had HFrEF, 1295 (23.0%) had HFpEF, and the remaining patients had HF with mid‐range ejection fraction (40% patients with HFpEF and HFrEF at admission (Table 2) showed that the 2 groups had distinct characteristics.
Table 1

Etiology of the Total Population and HFrEF, HFpEF Subgroups

EtiologyTotal PopulationHFrEFHFpEF P Value
Ischemic heart disease2113 (37.6)1381 (43.0)295 (21.7)<0.001
Valvular heart disease804 (14.3)232 (7.5)405 (31.3)<0.001
Congenital heart disease63 (1.1)15 (0.5)28 (2.2)<0.001
Cardiomyopathy1159 (20.6)933 (30.0)82 (6.3)<0.001
Hypertensive222 (3.9)91 (2.9)82 (6.3)<0.001
Myositis78 (1.4)49 (1.6)13 (1.0)0.141
Infiltrative disease70 (1.2)23 (0.7)26 (2.0)<0.001
Tachycardia related600 (10.7)250 (8.1)182 (14.1)<0.001
Thyroid related30 (0.5)12 (0.4)11 (0.8)0.052
Toxic related59 (1.0)44 (1.4)3 (0.2)<0.001
Unknown178 (4.0)109 (3.5)69 (5.3)0.005
Others152 (3.5)30 (1.0)122 (9.4)<0.001

Values are expressed in n (%). HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction.

Table 2

Demographic and Laboratory Characteristics Between HFpEF and HFrEF Subgroups

HFrEFHFpEF P Value
Sex, male1872 (60.3%)496 (38.3%)<0.001
Age, y66.3±14.772.0±13.5<0.001
BMI, kg/m2 23.1±3.823.8±4.0<0.001
LVEF, %27.0±7.759.5±6.6<0.001
Risk factors
Hypertension, n (%)1832 (59.0)865 (66.8)<0.001
DM, n (%)1297 (41.8)435 (33.6)<0.001
Smoking, %a 21.3/22.5/56.211.9/16.5/7106<0.001
Previous MI, n (%)590 (19.0)112 (8.6)<0.001
Previous PCI, n (%)55 (18.2)151 (11.7)<0.001
Previous CABG, n (%)181 (5.8)34 (2.6)<0.001
COPD, n (%)328 (10.6)174 (13.4)0.006
CRF, n (%)449 (14.5)150 (11.6)0.011
Previous CVA, n (%)442 (14.2)206 (15.9)0.154
Alcohol, %b 7.5/35.0/57.55.3/25.6/69.2<0.001
Valve disease, n (%)279 (9.0)348 (26.9)<0.001
Arrythmia, n (%)898 (28.9)531 (41.0)<0.001
NYHA at admission, %13.7/37.0/49.318.5/37.5/43.9<0.001
Initial SBP, mm Hg128±29136±30<0.001
Initial DBP, mm Hg79±1977±18<0.001
Initial HR95±2586±26<0.001
Laboratory analysis
WBC, 109/L8770±42208160±3500<0.001
Hb, g/dL12.7±2.312.0±2.2<0.001
Platelet, 109/L216±92202±89<0.001
Total cholesterol, mg/dL153±43149±430.020
Triglyceride, mg/dL99±58101±610.556
HDL, mg/dL41±1442±130.165
LDL, mg/dL96±3790±370.001
Na, mEq/L137±5138±50.697
Uric acid, mg/dL7.3±3.16.7±2.6<0.001
BUN, mg/dL26.7±16.824.5±14.9<0.001
Creatinine, mg/dL1.51±1.471.28±1.07<0.001
Glucose, mg/dL158±78145±68<0.001
CRP, mg/L2.25±4.112.39±4.280.328
BNP, pg/mL1600±1410810±850<0.001
NTproBNP, pg/mL10 690±11 7005280±6870<0.001

BMI indicates body mass index; BNP, brain natriuretic peptide; BUN, blood urea nitrogen; CABG, coronary artery bypass graft surgery; COPD, chronic obstructive pulmonary disease; CRP, C‐reactive protein; CRF, chronic renal failure; CVA, cerebrovascular accident; DBP, diastolic blood pressure; DM, diabetes mellitus; Hb, hemoglobin; HDL, high‐density lipoprotein; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, heart rate; LDL, low‐density lipoprotein; LVEF, left ventricular ejection fraction; MI, myocardial infarction; Na, natrium; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; WBC, white blood cell.

Smoking: current smoker/ex‐smoker/never smoker.

Alcohol: heavy drinker/social drinker/never drinker.

Etiology of the Total Population and HFrEF, HFpEF Subgroups Values are expressed in n (%). HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction. Demographic and Laboratory Characteristics Between HFpEF and HFrEF Subgroups BMI indicates body mass index; BNP, brain natriuretic peptide; BUN, blood urea nitrogen; CABG, coronary artery bypass graft surgery; COPD, chronic obstructive pulmonary disease; CRP, C‐reactive protein; CRF, chronic renal failure; CVA, cerebrovascular accident; DBP, diastolic blood pressure; DM, diabetes mellitus; Hb, hemoglobin; HDL, high‐density lipoprotein; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, heart rate; LDL, low‐density lipoprotein; LVEF, left ventricular ejection fraction; MI, myocardial infarction; Na, natrium; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; WBC, white blood cell. Smoking: current smoker/ex‐smoker/never smoker. Alcohol: heavy drinker/social drinker/never drinker.

WRF and Risk Factors

At admission, creatinine level was 1.49±1.47 mg/dL, which peaked to 1.83±1.78 mg/dL during hospitalization and decreased to 1.40±1.36 mg/dL before discharge. WRF during admission occurred in 3101 patients (55.1%), of which 980 (17.4%) had a creatinine increase greater than 1.0 mg/dL. Patients with HFrEF had a higher rate of WRF than did those with HFpEF (56.9% versus 50.3%; P<0.001). Among patients with WRF, 1919 (61.9%) showed transient WRF; rates of persistent WRF were higher in patients with HFrEF (38.7% versus 34.3%; P=0.045; Figure 1).
Figure 1

Prevalence of WRF and persistent WRF. WRF occurred in 55.1% of the total population, among which 38.1% showed persistent WRF. In subgroups of HFrEF and HFpEF, WRF and persistent WRF were more common in the HFrEF group. Abbreviations: HFrEF indicates heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; WRF, worsening renal function.

Prevalence of WRF and persistent WRF. WRF occurred in 55.1% of the total population, among which 38.1% showed persistent WRF. In subgroups of HFrEF and HFpEF, WRF and persistent WRF were more common in the HFrEF group. Abbreviations: HFrEF indicates heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; WRF, worsening renal function. Characteristics of the “no WRF,” “transient WRF,” and “persistent WRF” groups at admission are shown in Table 3. Patients with persistent WRF were more “sick” with a greater number of risk factors, compared with those in the “no WRF” and “transient WRF” groups. Prevalence of WRF increased as GFR decreased, and among the types of WRF, persistent WRF was shown to increase gradually along with grade of GFR decrease (Figure 2A). This trend was also present in both HFrEF and HFpEF subgroups (Figure 2B and 2C).
Table 3

Demographic and Laboratory Characteristics According to the Severity of WRF

No WRF (n=2520)Transient WRF (n=1919)Persistent WRF (n=1182) P Value
Sex, male1270 (50.4%)1046 (54.5%)675 (57.1%)<0.001
Age, y67.4±14.869.0±14.670.0±13.4<0.001
BMI, kg/m2 23.6±3.923.1±3.923.1±3.7<0.001
LVEF, %38.8±15.737.0±16.036.3±14.8<0.001
Risk factors
Hypertension, n (%)1461 (58.0)1188 (61.9)845 (71.5)<0.001
DM, n (%)800 (31.7)833 (43.4)614 (51.9)<0.001
Smoking, %a 17.8/19.4/62.817.8/21.8/60.317.0/22.9/60.10.107
Previous MI, n (%)355 (14.1)327 (17.0)235 (19.9)<0.001
Previous PCI, n (%)371 (14.7)321 (16.7)251 (21.3)<0.001
Previous CABG, n (%)102 (4.1)116 (6.0)72 (6.1)0.003
COPD, n (%)273 (10.8)220 (11.5)140 (11.8)0.627
CRF, n (%)115 (4.6)312 (16.3)378 (32.0)<0.001
Previous CVA, n (%)340 (13.5)318 (16.6)194 (16.4)0.007
Alcohol, %b 6.8/33.3/59.96.8/29.7/63.55.8/31.9/62.40.075
Valve disease, n (%)352 (14.0)296 (15.4)160 (13.5)0.252
Arrhythmia, n (%)827 (32.8)674 (35.1)369 (31.2)0.064
NYHA II/III/IV at admission, %19.6/41.8/38.613.0/34.2/52.89.2/30.8/60.0<0.001
Initial SBP, mm Hg132±28128±32134±33<0.001
Initial DBP, mm Hg80±1876±1979±20<0.001
Initial HR92±2693±2793±250.054
Laboratory analysis
WBC, 109/L7850±31509400±44409250±4840<0.001
Hb, g/dL12.9±2.112.2±2.411.6±2.3<0.001
Platelet, 109/L213±79211±98205±950.001
Total cholesterol, mg/dL156±42147±44149±44<0.001
Triglyceride, mg/dL100±60100±6197±540.247
HDL, mg/dL44±1439±1440±14<0.001
LDL, mg/dL96±3691±3893±390.066
Na, mEq/L138±4137±5137±5<0.001
Uric acid, mg/dL6.3±2.57.7±3.17.4±2.9<0.001
BUN, mg/dL19.2±8.431.1±18.033.3±20.4<0.001
Creatinine, mg/dL0.99±0.531.63±1.322.31±2.38<0.001
Glucose, mg/dL142±62164±84170±88<0.001
CRP, mg/L1.50±3.072.89±4.773.24±5.02<0.001
BNP, pg/mL980±8901510±14101850±1620<0.001
NTproBNP, pg/mL5560±667011 000±11 10013 710±14 050<0.001
During Adm.
Mech. Ventil., n (%)63 (2.5)453 (23.6)346 (29.3)<0.001
Transfusion, n (%)140 (5.6)599 (31.2)464 (39.3)<0.001
Intravascular diuretics, n (%)1671 (66.3)1579 (82.3)963 (81.5)<0.001
Intravascular inotropics, n (%)361 (14.3)849 (44.2)539 (45.6)<0.001
Intravascular vasodilators, n (%)871 (34.6)848 (44.2)582 (49.2)<0.001

BMI indicates body mass index; BNP, brain natriuretic peptide; BUN, blood urea nitrogen; COPD, chronic obstructive pulmonary disease; CRF, chronic renal failure; CRP, C‐reactive protein; DBP, diastolic blood pressure; DM, diabetes mellitus; HDL, high‐density lipoprotein cholesterol; HR, heart rate; LDL, low‐density lipoprotein cholesterol; LVEF, left ventricle ejection fraction; MI, myocardial infarction; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; WBC, white blood cell.

Smoking: current smoker/ex‐smoker/never smoker.

Alcohol: heavy drinker/social drinker/never drinker.

Figure 2

Prevalence of WRF by CRF stage. Prevalence of WRF increased along with the decrease of initial GFR at admission. Dark wine color represents persistent WRF, and gray color represents transient WRF. Both transient and persistent WRF increased as GFR grade decreased, in the (A) total study population, (B) HFrEF group, and (C) HFpEF group. GFR indiactes glomerular filtration rate; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Demographic and Laboratory Characteristics According to the Severity of WRF BMI indicates body mass index; BNP, brain natriuretic peptide; BUN, blood urea nitrogen; COPD, chronic obstructive pulmonary disease; CRF, chronic renal failure; CRP, C‐reactive protein; DBP, diastolic blood pressure; DM, diabetes mellitus; HDL, high‐density lipoprotein cholesterol; HR, heart rate; LDL, low‐density lipoprotein cholesterol; LVEF, left ventricle ejection fraction; MI, myocardial infarction; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; WBC, white blood cell. Smoking: current smoker/ex‐smoker/never smoker. Alcohol: heavy drinker/social drinker/never drinker. Prevalence of WRF by CRF stage. Prevalence of WRF increased along with the decrease of initial GFR at admission. Dark wine color represents persistent WRF, and gray color represents transient WRF. Both transient and persistent WRF increased as GFR grade decreased, in the (A) total study population, (B) HFrEF group, and (C) HFpEF group. GFR indiactes glomerular filtration rate; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function. Among various risk factors identified for WRF, CRF and usage of inotropes were the strongest predictors of WRF (Table 4). When the population was divided into patients with HFrEF and those with HFpEF, the 2 populations showed different risk‐factor profiles; CRF, hyponatremia, anemia, high BNP or N‐terminal pro‐brain‐type natriuretic peptide, high C‐reactive protein, high uric acid levels, and usage of diuretics and inotropes were common risk factors, whereas low body mass index, hypertension, diabetes mellitus, and vasodilator usage during admission were predictors of WRF in patients with HFrEF only.
Table 4

Multivariate Analysis for Predictors of WRF

FactorWholeHFrEFHFpEF
OR95% CI P ValueOR95% CI P ValueOR95% CI P Value
Sex, female1.261.05 to 1.520.015
BMI <25 kg/m2 1.201.00 to 1.450.0491.261.01 to 1.580.041
Hypertension1.221.02 to 1.450.0301.271.03 to 1.560.028
Diabetes mellitus1.301.09 to 1.550.0031.261.03 to 1.550.027
CRF4.623.36 to 6.34<0.0015.243.55 to 7.75<0.0012.971.69 to 5.23<0.001
Na <135 mmol/L1.781.44 to 2.19<0.0011.641.28 to 2.11<0.0012.201.49 to 3.24<0.001
Hb <12 g/dL1.631.36 to 1.96<0.0011.731.38 to 2.17<0.0011.521.10 to 2.090.011
High BNP or NTproBNP1.681.41 to 2.00<0.0011.521.24 to 1.87<0.0012.171.52 to 3.09<0.001
Uric acid >7 mg/dL2.281.92 to 2.70<0.0012.321.90 to 2.84<0.0012.541.83 to 3.52<0.001
CRP >0.5 mg/dL1.631.36 to 1.95<0.0011.731.39 to 2.16<0.0011.431.02 to 1.990.037
Diuretic usage1.551.26 to 1.90<0.0011.321.03 to 1.690.0272.431.67 to 3.53<0.001
Inotropic usage4.884.03 to 5.92<0.0014.323.48 to 5.36<0.0018.655.45 to 13.74<0.001
Vasodilator usage1.301.10 to 1.540.0011.451.19 to 1.78<0.001
HFrEF (vs HFpEF)0.840.70 to 1.020.077

BMI indicates body mass index; BNP, brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; WBC, white blood cell; WRF, worsening renal function.

Multivariate Analysis for Predictors of WRF BMI indicates body mass index; BNP, brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; WBC, white blood cell; WRF, worsening renal function.

Adverse In‐Hospital Outcomes

Among the entire study population, the mean hospitalization duration was 14.0±17.6 days; overall, it was longer in patients with HFrEF than in those with HFpEF (14.8±17.7 versus 12.9±16.9 days; P=0.001). It was also longer in patients with WRF than in those without WRF (7.9±5.2 versus 18.9±22.0 days; P<0.001). Adverse in‐hospital outcomes occurred in 292 patients (5.2%). Patients with WRF during admission had a higher number of in‐hospital outcomes (24/2520 [1.0%] versus 268/3101 [8.6%], P<0.001 in WRF (−) and WRF (+), respectively) in both the total population and the subgroups of HFrEF and HFpEF (Table 5). In the multivariate analysis, WRF was independently associated with adverse in‐hospital outcomes in the total patient population (odds ratio, 3.18; 95% confidence interval [CI], 1.78–5.67; P<0.001), as well as in the subgroups of HFrEF (odds ratio, 2.73; 95% CI, 1.48–5.01; P=0.001) and HFpEF (odds ratio, 8.53; 95% CI, 1.06–68.48; P=0.044; Table 6).
Table 5

Adverse in‐Hospital Clinical Outcomes

No WRFWRF P Value
Total population24/2520 (1.0%)268/3101 (8.6%)<0.001
HFrEF16/1339 (1.2%)149/1765 (8.4%)<0.001
HFpEF3/643 (0.5%)36/651 (5.5%)<0.001

HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Table 6

Multivariate Analysis for Predictors of Adverse in‐Hospital Outcomes

TotalHFrEFHFpEF
OR95% CI P ValueOR95% CI P ValueOR95% CI P Value
WRF3.181.78 to 5.67<0.0012.731.48 to 5.010.0018.531.06 to 68.480.044
Age >70 y2.081.40 to 3.10<0.0012.291.48 to 3.54<0.001NA
Arrhythmia1.721.13 to 2.620.0112.051.25 to 3.370.004NA
CRP >0.5 mg/dL1.661.16 to 2.370.0051.601.07 to 2.370.021NA
High BNP or NTproBNP1.611.07 to 2.430.0221.611.01 to 2.570.044NA
Inotropics usage6.744.39 to 10.33<0.0016.363.95 to 10.26<0.0018.453.16 to 22.63<0.001
HFrEF (vs HFpEF)1.140.71 to 1.830.590NANA

BNP indicates brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; Hb, hemoglobin; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, hazard ratio; Na, sodium; NA, not applicable; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; OR, odds ratio; UA, uric acid; WRF, worsening renal function.

Adverse in‐Hospital Clinical Outcomes HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function. Multivariate Analysis for Predictors of Adverse in‐Hospital Outcomes BNP indicates brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; Hb, hemoglobin; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, hazard ratio; Na, sodium; NA, not applicable; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; OR, odds ratio; UA, uric acid; WRF, worsening renal function.

Short‐ and Long‐Term Follow‐up Mortality by WRF

During the 1‐year follow‐up duration, 970 patients (17.2%) died. Regarding short‐term (3‐month) and long‐term (1‐year) mortality, mortality increased with severity of WRF in the total population, and in the HFrEF and HFpEF subgroups (Figure 3; Table 7). Using a Cox proportional hazard model, WRF was independently associated with short‐term mortality (hazard ratio [HR], 1.66; 95% CI, 1.22–2.25; P=0.001) and long‐term mortality (HR, 1.39; 95% CI, 1.14–1.69; P=0.001). When stratified according to HF type, WRF remained a significant risk factor in both the HFrEF and HFpEF subgroups (Table 8). Regarding the association with 3‐ and 12‐month mortality, WRF has a larger effect size in HFpEF compared with HFrEF (3‐month mortality: HR 1.59 for HFrEF and HR 1.86 for HFpEF; 12‐month mortality: HR 1.35 for HFrEF and HR 1.54 for HFpEF; Table 8).
Figure 3

Survival curve of the total population by the severity of WRF. Short‐term (3‐month) and long‐term (1‐year) mortality increased with severity of WRF in (A) the total study population, (B) the HFrEF group, and (C) the HFpEF group. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Table 7

1‐Year Follow‐up Clinical Outcomes

No WRFTransient WRFPersistent WRF P Value
3‐month mortality
Total population109 (4.3)185 (10.0)145 (14.5)<0.001
HFrEF69 (5.2)106 (10.2)89 (15.3)<0.001
HFpEF24 (3.7)38 (9.0)28 (14.6)<0.001
1‐year mortality
Total population298 (11.9)407 (22.0)265 (26.6)<0.001
HFrEF161 (12.1)224 (21.5)157 (26.9)<0.001
HFpEF74 (11.5)93 (21.9)48 (25.0)<0.001

Values are expressed in n (%). HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Table 8

Multivariate Analysis for Predictors of All‐Cause Mortality During Follow‐up

TotalHFrEFHFpEF
HR95% CI P ValueHR95% CI P ValueHR95% CI P Value
3‐month mortality
WRF1.661.22 to 2.250.0011.591.10 to 2.290.0131.861.06 to 3.270.031
Age >70 y2.461.81 to 3.35<0.0012.501.77 to 3.55<0.0012.361.22 to 4.600.011
Female sex1.371.04 to 1.800.028NANA
BMI <25 kg/m2 1.691.21 to 2.360.0021.731.14 to 2.630.010NA
Hb <12 g/dL1.300.99 to 1.700.0621.411.02 to 1.950.038NA
Na <135 mmol/L1.671.28 to 2.18<0.0011.871.37 to 2.54<0.001NA
UA >7 mg/dL1.341.04 to 1.740.024NA1.861.14 to 3.030.013
CRP >0.5 mg/dL1.461.13 to 1.890.0041.431.06 to 1.940.0201.631.00 to 2.640.049
High BNP or NTproBNP1.761.32 to 2.36<0.0011.951.35 to 2.84<0.001NA
12‐month mortality
WRF1.391.14 to 1.690.0011.351.06 to 1.710.0141.541.08 to 2.180.016
Age >70 y2.201.80 to 2.69<0.0012.301.83 to 2.90<0.0011.951.28 to 2.980.002
Female sex1.291.07 to 1.550.007NANA
BMI <25 kg/m2 1.471.20 to 1.82<0.0011.311.02 to 1.680.0381.941.33 to 2.840.001
Diabetes mellitus1.181.00 to 1.410.0531.281.04 to 1.580.022NA
CRF1.361.10 to 1.690.0051.431.11 to 1.840.006NA
Hb <12 g/dL1.431.19 to 1.73<0.0011.461.17 to 1.830.001NA
Na <135 mmol/L1.641.37 to 1.96<0.0011.731.39 to 2.14<0.0011.421.01 to 2.000.047
UA >7 mg/dL1.201.01 to 1.430.036NA1.571.15 to 2.160.005
CRP >0.5 mg/dL1.321.11 to 1.560.0021.341.09 to 1.650.005NA
High BNP or NTproBNP1.491.23 to 1.79<0.0011.681.33 to 2.14<0.001NA

BNP indicates brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; Hb, hemoglobin; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, hazard ratio; Na, sodium; NA, not applicable; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; OR, odds ratio; UA, uric acid; WRF, worsening renal function.

Survival curve of the total population by the severity of WRF. Short‐term (3‐month) and long‐term (1‐year) mortality increased with severity of WRF in (A) the total study population, (B) the HFrEF group, and (C) the HFpEF group. HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function. 1‐Year Follow‐up Clinical Outcomes Values are expressed in n (%). HFpEF indicates heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function. Multivariate Analysis for Predictors of All‐Cause Mortality During Follow‐up BNP indicates brain natriuretic peptide; CI, confidence interval; CRF, chronic renal failure; CRP, C‐reactive protein; Hb, hemoglobin; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, hazard ratio; Na, sodium; NA, not applicable; NTproBNP, N‐terminal pro‐brain‐type natriuretic peptide; OR, odds ratio; UA, uric acid; WRF, worsening renal function. We also analyzed whether transient WRF and persistent WRF had different effects on long‐term mortality. Transient WRF, when compared with the “no WRF” group, was a significantly associated with long‐term mortality after adjusting for other risk factors (Table 9). However, persistent WRF was not associated with mortality, when compared with transient WRF.
Table 9

Effect of Persistent and Transient WRF on 1‐Year Follow‐up Mortality

HR95% CI P Value
Total population
WRF vs no WRFUnadjusted2.161.88 to 2.48<0.001
Adjusted1.441.19 to 1.75<0.001
Transient WRF vs no WRFUnadjusted1.981.71 to 2.30<0.001
Adjusted1.351.09 to 1.670.006
Persistent WRF vs Transient WRFUnadjusted1.271.09 to 1.480.003
Adjusted1.170.95 to 1.440.150
HFrEF
WRF vs no WRFUnadjusted2.091.74 to 2.51<0.001
Adjusted1.351.06 to 1.710.014
Transient WRF vs no WRFUnadjusted1.881.53 to 2.30<0.001
Adjusted1.321.02 to 1.710.038
Persistent WRF vs Transient WRFUnadjusted1.331.09 to 1.640.006
Adjusted1.140.89 to 1.460.290
HFpEF
WRF vs no WRFUnadjusted2.171.64 to 2.88<0.001
Adjusted1.541.08 to 2.180.016
Transient WRF vs no WRFUnadjusted2.061.52 to 2.80<0.001
Adjusted1.501.03 to 2.200.034
Persistent WRF vsTransient WRFUnadjusted1.190.84 to 1.690.322
Adjusted1.140.75 to 1.720.538

CI indicates confidence interval; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Effect of Persistent and Transient WRF on 1‐Year Follow‐up Mortality CI indicates confidence interval; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; WRF, worsening renal function.

Discussion

In the current study, we determined the predictors of WRF during admission and examined the prognostic value of WRF for in‐hospital and short‐ and long‐term outcomes according to the HF type (ie, HFrEF versus HFpEF) and severity of WRF (ie, transient versus persistent WRF). As expected, patients with more‐severe WRF had more cardiac risk factors at admission. Among the various predictors of WRF, CRF and usage of inotropes were the predictors with the largest odds ratio. Interestingly, although WRF was a significant risk factor in both HFpEF and HFrEF, the effect size on in‐hospital outcomes was 3‐fold larger in HFpEF. Finally, WRF was associated with short‐ and long‐term mortality in both HFrEF and HFpEF, and the mortality rate increased alongside the degree of WRF, from no WRF, to transient WRF, and then to persistent WRF. After adjustment, transient WRF was an independent risk factor for long‐term mortality, whereas persistent WRF had no additive risk compared to transient WRF.

Predictors of WRF in HFrEF and HFpEF

There exists a close neurohumoral interaction between the heart and kidney.5, 6 Moreover, HFrEF and HFpEF have distinct anatomical contributors to the differences in hemodynamic and neurohumoral effects; specifically, patients with HFrEF have higher BNP levels than do HFpEF patients in this study and others.11 In this study, prevalence of WRF was higher in patients with HFrEF than in those with HFpEF, and HFrEF was associated with a 1.19‐fold increased risk for WRF. A significant correlation between WRF and BNP levels was also found (data not shown). Regarding the predictors of WRF, most predictors of WRF were similar in HFrEF and HFpEF; among them, CRF and inotropic usage were shown to have the greatest impact. Patients with preexisting renal dysfunction are more vulnerable to diverse insults, which is demonstrated by the increased prevalence of WRF and persistent WRF in patients with more‐decreased initial GFR. Furthermore, use of inotropic agents indicates a hemodynamic instability that may cause renal hypoperfusion.

WRF as a Risk Factor in HF

Defined as reduction in glomerular filtration, WRF has been associated with adverse outcomes in patients with HF in previous studies. Pimentel et al reported that patients with WRF had a significantly increased risk of all‐cause death and hospital admission in chronic HF patients.14 Damman et al showed that WRF was associated with lower survival and more morbidity in acute HF patients, from the COACH (Coordinating Study Evaluating Outcome of Advising and Counseling in Heart Failure) study.15 Additionally, a meta‐analysis by Damman et al including 45 000 patients from 28 studies showed that WRF was associated with mortality whereas CRF, hypertension, diabetes mellitus, age, and diuretic use were significant predictors for occurrence of WRF.4 Although these studies show similar results, the precise mechanism by which WRF exerts adverse prognostic effects remains unclear. Testani et al explained that several hypothetical mechanisms, including inflammation, oxidative stress, or induction of apoptosis by uremic toxins, may partially contribute to the adverse effect of WRF.16 However, this study also claimed that it is still uncertain whether WRF is a mediator or marker for adverse outcomes. In this study, magnitude of effect size for WRF decreased from 3.18, to 1.66, to 1.39 for adverse in‐hospital outcomes, and 3‐ and 12‐month mortality, respectively. Because we defined WRF as an in‐hospital event, this decrease seems understandable. Although the exact mechanisms are still not well defined, there are a couple of proposed explanations for the role of WRF as a predictor of adverse outcomes. Renal dysfunction may reflect impaired hemodynamic status that is related to severity of the underlying HF, reflected by the high HR for in‐hospital outcomes.17 Furthermore, renal dysfunction might be a marker of general vascular disease, such as severity of atherosclerosis in both the kidney and heart, which explains the long‐term outcomes with a smaller impact size.18

Impact of WRF on Outcomes in HFrEF Versus HFpEF

Whereas WRF was an independent risk factor for all analyzed outcomes, the effect size was larger in HFpEF; particularly for in‐hospital outcomes, effect size was 3‐fold larger in HFpEF. No current studies have compared the effect size of WRF in HF subtypes, whereas a previous study showed that WRF was a predictor of adverse events in HFpEF.19 Regarding the distinct pathophysiology of HFpEF and HFrEF, it is known that unfavorable volume distribution is a more‐frequent cause of acute decompensation in HFpEF, rather than absolute volume overload.20 Therefore, WRF in HFpEF may reflect a relative hypovolemic status with impaired fluid refilling from the extravascular space to the plasma, which can aggravate both renal and cardiac function. In contrast, patients with HFrEF experience absolute volume overload. WRF in HFrEF may develop during decongestion therapy with diuretics, which can temporarily reduce low effective circulating volume. This could account for the higher proportion of transient WRF in the HFrEF group in our population. Moreover, WRF in HFpEF could be more strongly associated with adverse outcomes compared with HFrEF. However, this can only partially explain the larger effect of WRF in HFpEF, attributed to the complex pathophysiology of WRF. The other independent predictors of mortality in the HFrEF subgroup were closely identical to those of the total HF population, whereas the HFpEF subgroup showed a smaller number of predictors. HFrEF seemed to be more multifactorial compared with HFpEF, and WRF seemed to play a larger role in HFpEF.

Two Types of WRF: Transient Versus Persistent WRF

From our study, severity of WRF increased as renal function at admission worsened, with more patients with persistent WRF among those with lower GFR. Transient WRF occurs in those with derangements in hemodynamics and neurohormones during acute HF, which may include interaction with diuretics or other theoretically reversible factors. On the other hand, persistent WRF may occur from insults related to coexisting comorbidities and aspects of the HF disease process itself that are irreversible.21 The question of the effect of transient WRF remains controversial. Krishnamoorthy et al showed that transient WRF was associated with a higher risk of 90‐day mortality,22 whereas Aronson et al23 reported that patients hospitalized for HF with transient WRF did not have significantly increased mortality at 6 months postdischarge. In our study, in terms of postdischarge short‐ and long‐term outcomes, transient WRF was an equivalent risk factor to persistent WRF. This discrepancy may be partially attributed to the various definitions of WRF and the outcomes of each study. Because we defined transient WRF as the recovery of renal function during hospitalization,24 those with a slower recovery (ie, those who show recovered renal function at outpatient follow‐up) could have been categorized into the persistent WRF group, thereby diluting the pure effect of persistent WRF. Further studies using universal definitions are mandatory to investigate the effect of transient WRF on outcomes in patients with acute HF.

Study Limitations

There are several limitations in this study. First, although we applied the widely used definition of WRF, this definition has intrinsic limits. Increase in creatinine cannot directly reflect GFR, and it also depends strongly on the renal function at admission. Additionally, regarding that we defined transient and persistent WRF by the creatinine level during admission, some patients might have been misclassified, according to the baseline creatinine level of an individual. Furthermore, according to the time point of the initial laboratory test, the initial creatinine level might not have been the actual baseline level, and therefore some patients with WRF may have been missed. Second, given that this study was based on a registry cohort, it is subject to various biases. Although our study results prove the strong association between WRF and poor clinical outcomes, the observational nature of our study also limits the interpretation of the causal relationship between WRF and clinical outcomes.

Conclusions

WRF was present in 55% of patients in the KorAHF registry. Incidence of WRF increased as renal function at admission decreased and was higher in patients with HFrEF than in those with HFpEF. Predictors of WRF were similar in both HF types. WRF was a prognostic factor of adverse in‐hospital and long‐term outcomes, with a larger effect size in HFpEF compared with HFrEF. Regardless of the degree of WRF, transient and persistent WRF seem to be equivalent risk factors.

Sources of Funding

This work was supported by Research of Korea Centers for Disease Control and Prevention (2010‐E63003‐00, 2011‐E63002‐00, 2012‐E63005‐00, 2013‐E63003‐00, 2013‐E63003‐01, 2013‐E63003‐02, and 2016‐ER6303‐00).

Disclosures

None.
  24 in total

Review 1.  Cardiorenal syndrome: new perspectives.

Authors:  Jeremy S Bock; Stephen S Gottlieb
Journal:  Circulation       Date:  2010-06-15       Impact factor: 29.690

2.  Prognostic value of NT-proBNP in heart failure with preserved versus reduced EF.

Authors:  Si-Hyuck Kang; Jin Joo Park; Dong-Ju Choi; Chang-Hwan Yoon; Il-Young Oh; Seok-Min Kang; Byung-Su Yoo; Eun-Seok Jeon; Jae-Joong Kim; Myeong-Chan Cho; Shung Chull Chae; Kyu-Hyung Ryu; Byung-Hee Oh
Journal:  Heart       Date:  2015-08-28       Impact factor: 5.994

3.  Prognostic value of worsening renal function in outpatients with chronic heart failure.

Authors:  Rodrigo Pimentel; Marta Couto; Olga Laszczyńska; Fernando Friões; Paulo Bettencourt; Ana Azevedo
Journal:  Eur J Intern Med       Date:  2014-06-27       Impact factor: 4.487

4.  Relation of worsened renal function during hospitalization for heart failure to long-term outcomes and rehospitalization.

Authors:  David E Lanfear; Edward L Peterson; Janis Campbell; Hemant Phatak; David Wu; Karen Wells; John A Spertus; L Keoki Williams
Journal:  Am J Cardiol       Date:  2011-01       Impact factor: 2.778

5.  Both in- and out-hospital worsening of renal function predict outcome in patients with heart failure: results from the Coordinating Study Evaluating Outcome of Advising and Counseling in Heart Failure (COACH).

Authors:  Kevin Damman; Tiny Jaarsma; Adriaan A Voors; Gerjan Navis; Hans L Hillege; Dirk J van Veldhuisen
Journal:  Eur J Heart Fail       Date:  2009-09       Impact factor: 15.534

Review 6.  Worsening renal function and prognosis in heart failure: systematic review and meta-analysis.

Authors:  Kevin Damman; Gerjan Navis; Adriaan A Voors; Folkert W Asselbergs; Tom D J Smilde; John G F Cleland; Dirk J van Veldhuisen; Hans L Hillege
Journal:  J Card Fail       Date:  2007-10       Impact factor: 5.712

7.  Relationship between central hemodynamics and regional blood flow in normal subjects and in patients with congestive heart failure.

Authors:  M E Leithe; R D Margorien; J B Hermiller; D V Unverferth; C V Leier
Journal:  Circulation       Date:  1984-01       Impact factor: 29.690

Review 8.  Renal impairment, worsening renal function, and outcome in patients with heart failure: an updated meta-analysis.

Authors:  Kevin Damman; Mattia A E Valente; Adriaan A Voors; Christopher M O'Connor; Dirk J van Veldhuisen; Hans L Hillege
Journal:  Eur Heart J       Date:  2013-10-27       Impact factor: 29.983

9.  How to diagnose diastolic heart failure: a consensus statement on the diagnosis of heart failure with normal left ventricular ejection fraction by the Heart Failure and Echocardiography Associations of the European Society of Cardiology.

Authors:  Walter J Paulus; Carsten Tschöpe; John E Sanderson; Cesare Rusconi; Frank A Flachskampf; Frank E Rademakers; Paolo Marino; Otto A Smiseth; Gilles De Keulenaer; Adelino F Leite-Moreira; Attila Borbély; István Edes; Martin Louis Handoko; Stephane Heymans; Natalia Pezzali; Burkert Pieske; Kenneth Dickstein; Alan G Fraser; Dirk L Brutsaert
Journal:  Eur Heart J       Date:  2007-04-11       Impact factor: 29.983

Review 10.  Cardiorenal syndrome--current understanding and future perspectives.

Authors:  Branko Braam; Jaap A Joles; Amir H Danishwar; Carlo A Gaillard
Journal:  Nat Rev Nephrol       Date:  2013-11-19       Impact factor: 28.314

View more
  11 in total

1.  Multimorbidity, guideline-directed medical therapies, and associated outcomes among hospitalized heart failure patients.

Authors:  Shinsuke Takeuchi; Takashi Kohno; Ayumi Goda; Yasuyuki Shiraishi; Masataka Kawana; Mike Saji; Yuji Nagatomo; Yosuke Nishihata; Makoto Takei; Shintaro Nakano; Kyoko Soejima; Shun Kohsaka; Tsutomu Yoshikawa
Journal:  ESC Heart Fail       Date:  2022-05-13

Review 2.  Prognostic and Therapeutic Implications of Renal Insufficiency in Heart Failure.

Authors:  Se Yong Jang; Dong Heon Yang
Journal:  Int J Heart Fail       Date:  2022-01-26

3.  Worsening Renal Function during Acute Decompensated Heart Failure: A Bad Signal Never to Ignore.

Authors:  Sang-Hyeon Park; Jeehoon Kang
Journal:  Int J Heart Fail       Date:  2021-04-14

Review 4.  Paradigm Shifts of Heart Failure Therapy: Do We Need Another Paradigm?

Authors:  Hae-Young Lee; Byung-Hee Oh
Journal:  Int J Heart Fail       Date:  2020-04-06

5.  Clinical Impact of Worsening Renal Function in Elderly Patients with Acute Decompensated Heart Failure.

Authors:  Akinori Sawamura; Hiroki Kajiura; Takuya Sumi; Norio Umemoto; Tsuyoshi Sugiura; Toshio Taniguchi; Masako Ohashi; Toru Asai; Kiyokazu Shimizu; Toyoaki Murohara
Journal:  Int J Heart Fail       Date:  2021-03-29

6.  Implantable Cardioverter-defibrillator Utilization and Its Outcomes in Korea: Data from Korean Acute Heart Failure Registry.

Authors:  Youngjin Cho; Sang Yeong Cho; Il Young Oh; Ji Hyun Lee; Jin Joo Park; Hae Young Lee; Kye Hun Kim; Byung Su Yoo; Seok Min Kang; Sang Hong Baek; Eun Seok Jeon; Jae Joong Kim; Myeong Chan Cho; Shung Chull Chae; Byung Hee Oh; Dong Ju Choi
Journal:  J Korean Med Sci       Date:  2020-11-30       Impact factor: 2.153

7.  Phenomapping in patients experiencing worsening renal function during hospitalization for acute heart failure.

Authors:  Ryuichiro Yagi; Makoto Takei; Shun Kohsaka; Yasuyuki Shiraishi; Nobuhiro Ikemura; Satoshi Shoji; Nozomi Niimi; Satoshi Higuchi; Ayumi Goda; Takashi Kohno; Yuji Nagatomo; Yosuke Nishihata; Yasumori Sujino; Mike Saji; Yukinori Ikegami; Shintaro Nakano; Toshiyuki Takahashi; Keiichi Fukuda; Tsutomu Yoshikawa
Journal:  ESC Heart Fail       Date:  2021-09-20

8.  Acute Decompensated Heart Failure and the Kidney: Physiological, Histological and Transcriptomic Responses to Development and Recovery.

Authors:  Miriam T Rademaker; Anna P Pilbrow; Leigh J Ellmers; Suetonia C Palmer; Trent Davidson; Prisca Mbikou; Nicola J A Scott; Elizabeth Permina; Christopher J Charles; Zoltán H Endre; A Mark Richards
Journal:  J Am Heart Assoc       Date:  2021-09-17       Impact factor: 5.501

9.  Guideline-directed therapy at discharge in patients with heart failure and atrial fibrillation.

Authors:  Min-Soo Ahn; Byung Su Yoo; Junghan Yoon; Seung-Hwan Lee; Jang Young Kim; Sung Gyun Ahn; Young Jin Youn; Jun-Won Lee; Jung-Woo Son; Hye Sim Kim; Dae Ryong Kang; Hyun-Jai Cho; Hae-Young Lee; Eun Seok Jeon; Seok-Min Kang; Dong-Ju Choi; Myeong-Chan Cho
Journal:  Heart       Date:  2019-09-06       Impact factor: 5.994

Review 10.  Renal dysfunction in cardiovascular diseases and its consequences.

Authors:  Giacomo Deferrari; Adriano Cipriani; Edoardo La Porta
Journal:  J Nephrol       Date:  2020-09-01       Impact factor: 3.902

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.