Regional Variation in the Clinical Practice and Prognosis in Patients With Heart Failure With Reduced Ejection Fraction in Japan　― A Report From the Japanese Registry of Acute Decompensated Heart Failure (JROADHF) ―

Abstract

Background: The present study aimed to clarify the regional variations in clinical practice and the prognosis of patients with heart failure with reduced ejection fraction (HFrEF) in Japan using the Japanese Registry of Acute Decompensated Heart Failure (JROADHF).

Methods and Results: We recruited data of hospitalized patients with HFrEF (n=4,329) from the JROADHF. The patients were divided into 6 groups based on the region of Japan where they were hospitalized: Hokkaido-Tohoku (n=504), Kanto (n=958), Chubu (n=779), Kinki (n=902), Chugoku-Shikoku (n=446), and Kyushu (n=740). We compared the patients’ characteristics, including etiology of HF and prognosis after discharge. The age of the patients was lowest in the Kanto and Kinki regions. In contrast, there were no differences in the prevalence of comorbidities, levels of B-type natriuretic peptide, or left ventricular EF among the 6 groups. Post-discharge cardiospecific prognosis, specifically, the composite of cardiac death or HF hospitalization, cardiac death, and HF hospitalization, was comparable among the 6 regions.

Conclusions: There were no differences in cardiospecific prognosis in patients with HFrEF among the 6 regions in Japan.

Heart failure (HF) as a common clinical syndrome with high morbidity and mortality has been increasing worldwide,^1,2 so to improve the prognosis of patients with HF, task forces have summarized the accumulating evidence and proposed evidence-based treatments as guidelines.^3–6 The cardioprotective evidence is abundant for patients with HF with reduced ejection fraction (HFrEF) in particular,^3–6 but HF is a heterogeneous syndrome with various etiologic and pathophysiologic factors.^7,8 Regional variations in clinical practice and prognosis have been reported in the USA, Europe, and Asia, which suggests region-specific risk factors and gaps.^9,10

Japan has one of the fastest aging populations and the number of patients with HF is predicted to keep increasing.^11,12 In addition, regional variations in patients’ backgrounds and treatments have been reported in patients with coronary artery disease and cardiomyopathies, which are 2 of the leading causes of HF.^13–15 However, regional variations in Japanese patients with HF remain unclear, so we hypothesized that addressing such variations could potentially improve HF management and prognosis. Thus, the aim of the present study was to clarify regional variations in both clinical practice and prognosis of Japanese patients with HFrEF using the Japanese Registry of Acute Decompensated Heart Failure (JROADHF).¹⁶

Methods

Study Setting

The JROADHF database is a retrospective, multicenter, and nationwide registry that was established through collaboration between the Japanese Circulation Society and the Japanese Heart Failure Society.¹⁶ The protocol of JROADHF was conducted in accordance with the principles of the Declaration of Helsinki.^16,17 The rationale, design, and other details have been described previously.¹⁶ In brief, data were screened from the Japanese Registry Of All cardiac and vascular Diseases–the Japanese Diagnosis Procedure Combination system (JROAD-DPC) database, a nationwide claim database using the Japanese Diagnosis Procedure Combination/Per-Diem Payment System.^11,16 Patients’ data were recruited from the JROAD-DPC database on the basis of the combination of International Classification of Diseases-10 diagnosis codes related to HF (I50.0, I50.1 and I50.9) and an additional diagnostic code (30101 or 30102 representing acute HF or exacerbation of chronic HF), and a total of 13,238 patients were enrolled in the JROADHF with medical records from each institution linked.^11,16 Additional data including the etiology of HF, laboratory parameters, echocardiographic data, and post-discharge prognosis were adjudicated by investigators at each institution based on patients’ medical records.¹⁶ Of the patients included in the JROADHF, left ventricular ejection fraction (LVEF) was measured in a total of 11,573 on admission, and the proportion of each type of HF was as follows: 4,329 (37.4%) HFrEF (LVEF <40%); 2,024 (17.5%) HF with mildly reduced ejection fraction (40%≤LVEF<50%); and 5,220 (45.1%) HF with preserved EF (LVEF ≥50%).¹⁶ In the present study, we divided the HFrEF patients (n=4,329) into 6 groups based on the region of Japan where they were hospitalized (Figure 1): the Hokkaido-Tohoku (n=504, 11.6%), Kanto (n=958, 22.1%), Chubu (n=779, 18.0%), Kinki (n=902, 20.8%), Chugoku-Shikoku (n=446, 10.3%), and Kyushu (n=740, 17.1%) regions. We compared the patients’ characteristics, including HF etiology and prognosis after discharge. The leading causes of HF were classified as ischemic heart disease (IHD), cardiomyopathy, hypertensive heart disease, valvular heart disease, arrhythmia, or others. Regarding IHD, the prevalence of a prior history of percutaneous coronary intervention (PCI) without distinguishing causative diseases such as angina and myocardial infarction (MI) was extracted from the JROADHF database. The precipitating factors of worsening HF were defined as dietary non-compliance, uncontrolled hypertension, medication non-compliance, infection, arrhythmia, ischemia, or others. Cardioprotective drugs were defined in this study as renin-angiotensin system inhibitors, β-blockers, and mineralocorticoid receptor antagonists. Oral inotropes were defined as calcium sensitizer and/or other inotropic agents not including digitalis. There were no missing data for in-hospital and post-discharge prognosis for all patients with HFrEF in the JROADHF. To compare the post-discharge prognosis among the 6 groups, we focused on cardiospecific outcomes: the composite of cardiac death or HF hospitalization, cardiac death, and HF hospitalization. Cardiac death was defined in this study as death due to MI, HF, or arrhythmia. If a patient experienced ≥2 events, the first event was used for analyses.

Figure 1.

Distribution of patients among the 6 regions of Japan. The institutions were selected by cluster random sampling from those included in the Japanese Registry of All cardiac and vascular Diseases–the Japanese Diagnosis Procedure Combination system (JROAD-DPC) database during 2013. Each region is color-coded on the left side and the number of patients with heart failure with reduced ejection fraction and the institutions in which they were hospitalized are shown on the right.

Statistical Analysis

The normality of all continuous variables used in this study was evaluated using the Shapiro-Wilk test and the variables were considered to be non-normally distributed. Continuous and categorical variables are expressed as the median (25th percentile, 75th percentile) and numbers (percent), respectively. We used the Kruskal-Wallis test for comparisons of continuous variables and, if significant, performed the Steel-Dwass test for post-hoc analysis. Categorical variables were compared using the chi-square test. Kaplan-Meier analysis was used to compare the post-discharge prognosis. We assessed the hazard ratio for the post-discharge cardiospecific outcomes in each region using Cox proportional hazard analysis considering the Kanto region, the central area of Japan, as the reference. Hazard ratios were further adjusted for age, sex, and etiology of HF. In addition, the associations between medical treatment at discharge and subsequent cardiospecific outcomes at 30, 90, and 180 days, as well as during the overall follow-up period, were evaluated using logistic regression analysis and Cox proportional hazard analysis. The heterogeneity of treatment effects across regions was evaluated by subgroup analysis.^18,19 Considering multiplicity, the threshold for significance was set as 0.05/number of subgroups to correct for the inflated false-positive rate based on the Bonferroni correction; statistical significance of interaction was P<0.007.^18,20 As supplementary material, we compared patients with and without cardioprotective drugs at discharge among those not lacking data of medications. Factors associated with the non-use of cardioprotective drugs were evaluated using logistic regression analysis. Odds ratios were further adjusted for age, sex, and factors with P<0.05 in the univariable analysis. P<0.05 was considered statistically significant for all analyses other than the subgroup analysis. The Steel-Dwass test was performed using EZR ver. 1.54 (Saitama Medical Center, Jichi Medical University, Saitama, Japan), which is a graphical user interface for R ver. 4.0.3 (The R Foundation for Statistical Computing, Vienna, Austria).²¹ More precisely, it is a modified version of R commander ver. 2.7-1 designed to add statistical functions frequently used in biostatistics.²¹ All other analyses were performed using SPSS ver. 28.0.1.0 (IBM, Armonk, NY, USA).

Results

Comparisons of the patients’ characteristics and etiologies of HF are shown in Table 1. The Chubu region was the oldest among the 6 regions and was statistically older than the Kanto and Kinki regions, which are 2 central areas of Japan (Hokkaido-Tohoku, Kanto, Chubu, Kinki, Chugoku-Shikoku, and Kyushu; 77.0, 75.0, 78.0, 75.0, 76.0, and 77.0 years, respectively, P=0.012). Prevalences of male sex and major comorbidities were comparable among the 6 regions. On the other hand, the leading etiology of HF and precipitating factor differed from region to region. IHD was the most prevalent, affecting approximately one-third of the whole population. The prevalence of cardiomyopathy varied roughly from 20% to 30% among the 6 regions. The proportion of valvular heart disease and arrhythmia was the lowest in the Kinki region. For laboratory data on admission, the levels of B-type natriuretic peptide and hemoglobin were comparable among the 6 regions. Estimated glomerular filtration rate was highest in the Chubu region (P=0.008). Echocardiography revealed no differences in LVEF among the 6 groups. During hospitalization, length of hospital stay and in-hospital mortality were comparable, but symptoms evaluated by the New York Heart Association (NYHA) functional class at discharge differed among the 6 regions. Specifically, the prevalence of the NYHA functional class III or IV was the highest in the Kyushu region and the lowest in the Kinki region (P<0.001). Laboratory data at discharge, except for levels of hemoglobin, differed among the 6 regions. Regarding medication at discharge, there were differences in the use of cardioprotective drugs. The frequency of prescribing all 3 types of cardioprotective drugs was highest in the Kyushu region (P<0.001). Regarding diuretics and inotropic agents, the use of loop diuretics and digitalis was comparable, but the use of vasopressin receptor antagonists and oral inotropes differed among the 6 regions (P=0.003 and P<0.001, respectively).

Table 1. Patients’ Characteristics by Region

	Total (n=4,329)	Hokkaido- Tohoku region (n=504)	Kanto region (n=958)	Chubu region (n=779)	Kinki region (n=902)	Chugoku- Shikoku region (n=446)	Kyushu region (n=740)	P value
Demographic data
Age (years)	76.0 (65.0, 84.0)	77.0 (65.0, 84.0)	75.0 (64.0, 83.0)	78.0 (68.0, 84.0)*,†	75.0 (65.0, 83.0)	76.0 (65.0, 84.0)	77.0 (65.0, 84.0)	0.012
Male sex, n (%)	2,875 (66.4)	334 (66.3)	671 (70.0)	507 (65.1)	607 (67.3)	288 (64.6)	468 (63.2)	0.060
Etiology of HF, n (%)								<0.001
Ischemic heart disease	1,524 (36.3)	187 (37.1)	314 (35.6)	271 (35.5)	331 (37.4)	142 (32.8)	279 (38.2)
Cardiomyopathy	1,022 (24.3)	135 (26.8)	214 (24.2)	177 (23.2)	256 (28.9)	95 (21.9)	145 (19.8)
Hypertensive heart disease	498 (11.9)	57 (11.3)	110 (12.5)	89 (11.6)	96 (10.8)	47 (10.9)	99 (13.5)
Valvular heart disease	456 (10.9)	63 (12.5)	101 (11.4)	87 (11.4)	74 (8.4)	37 (8.5)	94 (12.9)
Arrhythmia	481 (11.4)	51 (10.1)	112 (12.7)	99 (13.0)	71 (8.0)	73 (16.9)	75 (10.3)
Others	220 (5.2)	11 (2.2)	32 (3.6)	41 (5.4)	58 (6.5)	39 (9.0)	39 (5.3)
Prior history of HF hospitalization, n (%)	1,648 (38.1)	219 (43.5)	329 (34.3)	262 (33.6)	354 (39.2)	178 (39.9)	306 (41.4)	<0.001
Prior history of PCI, n (%)	935 (22.1)	115 (22.8)	187 (20.8)	142 (18.5)	220 (24.6)	111 (25.5)	160 (21.8)	0.023
Comorbidities
Ischemic heart disease, n (%)	1,893 (43.7)	233 (46.2)	398 (41.5)	334 (42.9)	389 (43.1)	196 (43.9)	343 (46.4)	0.349
Hypertension, n (%)	2,923 (67.5)	345 (68.5)	655 (68.4)	543 (69.7)	593 (65.7)	307 (68.8)	480 (64.9)	0.283
Diabetes mellitus, n (%)	1,577 (36.4)	179 (35.5)	337 (35.2)	285 (36.6)	343 (38.0)	169 (37.9)	264 (35.7)	0.788
Dyslipidemia, n (%)	1,500 (34.7)	180 (35.7)	330 (34.4)	257 (33.0)	342 (37.9)	147 (33.0)	244 (33.0)	0.225
Atrial fibrillation, n (%)	1,540 (35.7)	191 (38.3)	334 (34.9)	285 (36.9)	308 (34.3)	169 (38.2)	253 (34.2)	0.435
Chronic kidney disease, n (%)	3,199 (73.9)	372 (73.8)	701 (73.2)	556 (71.4)	668 (74.1)	340 (76.2)	562 (75.9)	0.335
Stroke, n (%)	602 (13.9)	70 (13.9)	136 (14.2)	108 (13.9)	119 (13.2)	68 (15.2)	101 (13.6)	0.948
Peripheral artery disease, n (%)	278 (6.4)	44 (8.7)	63 (6.6)	37 (4.7)	58 (6.4)	26 (5.8)	50 (6.8)	0.129
COPD, n (%)	230 (5.3)	27 (5.4)	33 (3.4)	44 (5.6)	52 (5.8)	32 (7.2)	42 (5.7)	0.063
Data on admission
Precipitating factor, n (%)								0.001
Dietary non-compliance	1,013 (24.1)	129 (25.6)	205 (23.2)	175 (22.9)	235 (26.5)	113 (26.1)	156 (21.3)
Uncontrolled hypertension	299 (7.1)	38 (7.5)	73 (8.3)	65 (8.5)	61 (6.9)	24 (5.5)	38 (5.2)
Medication non-compliance	227 (5.4)	33 (6.5)	47 (5.3)	30 (3.9)	39 (4.4)	35 (8.1)	43 (5.9)
Infection	561 (13.4)	61 (12.1)	124 (14.1)	100 (13.1)	109 (12.3)	62 (14.3)	105 (14.4)
Arrhythmia	526 (12.5)	60 (11.9)	110 (12.5)	86 (11.3)	114 (12.9)	73 (16.9)	83 (11.4)
Ischemia	380 (9.0)	50 (9.9)	79 (9.0)	58 (7.6)	86 (9.7)	32 (7.4)	75 (10.3)
Others	1,194 (28.4)	133 (26.4)	244 (27.7)	250 (32.7)	242 (27.3)	94 (21.7)	231 (31.6)
Body mass index (kg/m2)	22.4 (19.9, 25.2)	23.0 (20.1, 25.7)	22.6 (19.8, 25.4)	21.9 (19.6, 25.0)	22.4 (20.1, 25.1)	22.5 (19.9, 25.5)	22.2 (19.8, 25.1)	0.026
SBP (mmHg)	131.0 (112.0, 155.0)	130.0 (110.0, 151.0)*	134.0 (114.0, 160.0)†	133.0 (112.0, 156.0)	130.0 (111.0, 153.0)*	130.0 (110.0, 153.0)	130.0 (111.0, 152.0)*	0.001
BNP (pg/mL)	1,029.3 (580.3, 1,748.7)	981.7 (567.6, 1,714.0)	1,103.8 (588.0, 1,713.3)	953.5 (586.8, 1,643.5)	1,047.4 (565.8, 1,880.1)	943.7 (573.8, 1,716.0)	1,037.5 (601.5, 1,809.0)	0.628
Hemoglobin (g/dL)	12.3 (10.8, 14.0)	12.4 (10.9, 14.0)	12.4 (10.9, 14.1)	12.3 (10.7, 13.9)	12.2 (10.7, 13.9)	12.5 (11.0, 14.0)	12.3 (10.7, 14.1)	0.406
eGFR (mL/min/1.73 m2)	45.9 (30.4, 61.5)	45.6 (31.8, 60.5)	47.2 (32.2, 62.8)	48.7 (31.7, 63.1)†	44.9 (28.7, 60.9)	44.5 (30.7, 60.4)	44.3 (29.0, 60.0)	0.008
Sodium (mEq/L)	140.0 (137.0, 142.0)	139.0 (137.0, 141.0)	140.0 (137.0, 142.0)	140.0 (137.0, 142.0)	139.5 (137.0, 142.0)	139.0 (137.0, 142.0)	140.0 (137.0, 142.0)	0.004
LVEF (%)	30.0 (23.0, 34.0)	29.0 (24.0, 34.0)	29.0 (23.0, 34.0)	30.0 (23.0, 35.0)	29.0 (23.0, 34.0)	30.0 (24.0, 35.0)	30.0 (24.0, 35.0)	0.056
In-hospital prognosis
Length of hospital stay (days)	19.0 (13.0, 30.0)	20.0 (13.0, 32.5)	19.0 (12.0, 29.0)	19.0 (12.5, 28.0)	20.0 (14.0, 30.0)	20.0 (13.0, 29.0)	19.0 (14.0, 30.0)	0.053
NYHA functional class III or IV at discharge, n (%)	519 (13.3)	59 (12.1)	113 (12.7)	84 (12.7)	72 (8.5)	67 (17.4)	124 (19.0)	<0.001
In-hospital death, n (%)	321 (7.4)	39 (7.7)	58 (6.1)	71 (9.1)	63 (7.0)	25 (5.6)	65 (8.8)	0.066
Data at discharge
BNP (pg/mL)	325.8 (156.2, 654.2)	384.5 (172.0, 713.4)	292.0 (156.7, 645.6)	290.4 (129.4, 605.7)	321.0 (159.2, 621.1)	283.3 (140.9, 554.1)	409.6 (190.9, 794.5)	0.013
Hemoglobin (g/dL)	12.2 (10.6, 13.9)	12.2 (10.6, 14.0)	12.3 (10.6, 14.0)	12.2 (10.6, 13.8)	12.2 (10.6, 13.9)	12.4 (11.0, 14.2)	11.9 (10.4, 13.8)	0.105
eGFR (mL/min/1.73 m2)	45.3 (30.5, 60.8)	45.1 (30.9, 59.5)	47.6 (31.7, 63.6)†	47.2 (31.7, 61.8)	44.3 (29.4, 59.7)*	43.6 (31.3, 59.6)	43.8 (28.0, 58.9)*	0.001
Sodium (mEq/L)	139.0 (136.0, 141.0)	139.0 (136.0, 141.0)	139.0 (136.0, 141.0)	139.0 (137.0, 141.0)†	138.0 (136.0, 141.0)	138.0 (136.0, 141.0)	139.0 (136.0, 141.0)†	0.002
Medication at discharge (n=3,901)
No. of cardioprotective drugs, n (%)								<0.001
0	212 (5.4)	29 (6.4)	51 (5.8)	44 (6.4)	30 (3.7)	29 (7.1)	29 (4.4)
1	711 (18.2)	93 (20.6)	161 (18.3)	143 (20.8)	134 (16.5)	85 (20.7)	95 (14.4)
2	1,537 (39.4)	168 (37.3)	341 (38.7)	278 (40.5)	354 (43.5)	161 (39.2)	235 (35.7)
3	1,441 (36.9)	161 (35.7)	328 (37.2)	222 (32.3)	295 (36.3)	136 (33.1)	299 (45.4)
RAS inhibitors, n (%)	2.788 (71.5)	290 (64.3)	633 (71.9)	466 (67.8)	610 (75.0)	268 (65.2)	521 (79.2)	<0.001
β-blockers, n (%)	3,040 (77.9)	355 (78.7)	680 (77.2)	507 (73.8)	666 (81.9)	318 (77.4)	514 (78.1)	0.011
MRAs, n (%)	2,280 (58.4)	267 (59.2)	514 (58.3)	392 (57.1)	451 (55.5)	229 (55.7)	427 (64.9)	0.006
Loop diuretics, n (%)	3,522 (90.3)	401 (88.9)	793 (90.0)	618 (90.0)	738 (90.8)	385 (93.7)	587 (89.2)	0.180
VRAs, n (%)	435 (11.2)	52 (11.5)	93 (10.6)	70 (10.2)	69 (8.5)	64 (15.6)	87 (13.2)	0.003
Digitalis, n (%)	537 (13.8)	54 (12.0)	121 (13.7)	104 (15.1)	105 (12.9)	51 (12.4)	102 (15.5)	0.402
Oral inotropes, n (%)	506 (13.0)	74 (16.4)	90 (10.2)	76 (11.1)	102 (12.5)	74 (18.0)	90 (13.7)	<0.001

*P<0.05 vs. Kanto region, ^†P<0.05 vs. Kinki region. BNP, B-type natriuretic peptide; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; HF, heart failure; LVEF, left ventricular ejection fraction; MRA, mineralocorticoid receptor antagonist; NYHA, New York Heart Association; PCI, percutaneous coronary intervention; RAS, renin-angiotensin system; SBP, systolic blood pressure; VRA, vasopressin receptor antagonist.

During the post-discharge follow-up of median 1,101 days, a total of 1,699 patients experienced the composite endpoints (23.7 events per 100 person-years); there were 720 cardiac deaths (6.7 events per 100 person-years) and 1,478 HF hospitalizations (20.6 events per 100 person-years) recorded. Cardiac deaths consisted of 34 (4.7%) MIs, 592 (82.2%) HF cases, and 94 (13.1%) arrhythmias. In the Kaplan-Meier analysis, the occurrences of the composite endpoint, cardiac death, and HF hospitalization were comparable among the 6 regions (Figure 2, log-rank P=0.681, 0.119, and 0.585, respectively). In the Cox proportional hazard analysis, compared with the Kanto region as the reference, the hazard ratios of the remaining 5 regions were comparable regarding the post-discharge cardiospecific outcomes (Table 2). In addition, after adjustment for age, sex, and etiology of HF, statistical significance did not change among all the groups (Table 2). At 30, 90, and 180 days, as well as during overall follow-up after discharge, cardioprotective drugs at discharge were consistently or partly associated with favorable prognosis, whereas diuretics and oral inotropes were associated with adverse prognosis (Table 3). Additionally, there was no significant interaction between treatment effects of each drug on clinical outcomes across regions, except for an interaction between regions and use of mineralocorticoid receptor antagonists on HF hospitalization (Figures 3–5). Patients who were not taking cardioprotective drugs were older, with less cardiomyopathy and more valvular heart disease, and with more severe HF symptoms assessed by NYHA functional class. Length of hospital stay was shorter in patients without cardioprotective drugs (Supplementary Table). Multivariable logistic regression analysis revealed that age and NYHA functional class III or IV were positively while length of hospital stay was negatively associated with the non-use of cardioprotective drugs (Supplementary Table).

Figure 2.

As the post-discharge prognosis, the composite of cardiac death or HF hospitalization, cardiac death, and HF hospitalization were evaluated by Kaplan-Meier analysis. The curves of regions crossed and the log-rank test indicated that there were no statistical differences in any of the outcomes. HF, heart failure.

Table 2. Post-Discharge Prognosis (n=4,008)

	Univariable		Multivariable*
	HR (95% CI)	P value	HR (95% CI)	P value
Composite endpoint (23.7/100 person-years)
Kanto region (23.3/100 person-years)	(Ref.)	–	(Ref.)	–
Hokkaido-Tohoku region (24.9/100 person-years)	1.093 (0.922–1.296)	0.306	1.027 (0.864–1.220)	0.763
Chubu region (23.2/100 person-years)	1.026 (0.882–1.195)	0.739	0.963 (0.825–1.124)	0.632
Kinki region (23.6/100 person-years)	1.033 (0.892–1.196)	0.664	0.972 (0.837–1.130)	0.714
Chugoku-Shikoku region (21.5/100 person-years)	0.964 (0.804–1.155)	0.689	0.969 (0.807–1.164)	0.738
Kyushu region (25.7/100 person-years)	1.102 (0.945–1.286)	0.216	1.042 (0.890–1.219)	0.610
Cardiac death (6.7/100 person-years)
Kanto region (6.3/100 person-years)	(Ref.)	–	(Ref.)	–
Hokkaido-Tohoku region (7.8/100 person-years)	1.254 (0.971–1.619)	0.084	1.182 (0.912–1.532)	0.207
Chubu region (7.7/100 person-years)	1.225 (0.974–1.541)	0.082	1.140 (0.902–1.440)	0.273
Kinki region (6.0/100 person-years)	0.961 (0.760–1.215)	0.740	0.926 (0.729–1.176)	0.529
Chugoku-Shikoku region (5.9/100 person-years)	0.946 (0.709–1.262)	0.705	0.964 (0.719–1.292)	0.805
Kyushu region (7.1/100 person-years)	1.131 (0.890–1.437)	0.313	1.085 (0.850–1.385)	0.510
HF hospitalization (20.6/100 person-years)
Kanto region (19.9/100 person-years)	(Ref.)	–	(Ref.)	–
Hokkaido-Tohoku region (21.9/100 person-years)	1.125 (0.937–1.350)	0.206	1.051 (0.874–1.264)	0.599
Chubu region (19.7/100 person-years)	1.022 (0.867–1.204)	0.798	0.963 (0.815–1.139)	0.663
Kinki region (21.3/100 person-years)	1.088 (0.930–1.272)	0.292	1.023 (0.872–1.201)	0.780
Chugoku-Shikoku region (18.7/100 person-years)	0.979 (0.806–1.189)	0.828	0.980 (0.805–1.194)	0.842
Kyushu region (22.2/100 person-years)	1.111 (0.941–1.312)	0.213	1.049 (0.886–1.243)	0.576

*Adjusted for age, sex, and etiology of HF. CI, confidence interval; HF, heart failure; HR, hazard ratio.

Table 3. Association Between Medical Treatment and Post-Discharge Prognosis (n=4,008): Logistic Regression Analysis

	30 days		90 days		180 days
	OR (95% CI)	P value	OR (95% CI)	P value	OR (95% CI)	P value
Composite endpoint	Event n=347		Event n=670		Event n=910
RAS inhibitors	0.665 (0.526–0.841)	<0.001	0.666 (0.557–0.796)	<0.001	0.725 (0.617–0.852)	<0.001
β-blockers	0.825 (0.636–1.070)	0.147	0.922 (0.754–1.127)	0.427	0.940 (0.785–1.125)	0.498
MRAs	0.740 (0.591–0.927)	0.009	0.920 (0.775–1.091)	0.337	0.951 (0.817–1.108)	0.521
Loop diuretics	1.494 (0.965–2.314)	0.072	1.445 (1.051–1.985)	0.023	1.187 (0.911–1.547)	0.203
VRAs	2.238 (1.679–2.984)	<0.001	2.475 (1.976–3.100)	<0.001	2.521 (2.044–3.109)	<0.001
Digitalis	0.767 (0.538–1.093)	0.143	0.853 (0.661–1.101)	0.221	0.998 (0.802–1.242)	0.984
Oral inotropes	2.332 (1.779–3.058)	<0.001	2.711 (2.195–3.348)	<0.001	3.073 (2.527–3.738)	<0.001
Cardiac death	Event n=35		Event n=102		Event n=182
RAS inhibitors	0.372 (0.187–0.739)	0.005	0.440 (0.295–0.655)	<0.001	0.465 (0.343–0.631)	<0.001
β-blockers	0.492 (0.241–1.004)	0.051	0.622 (0.404–0.957)	0.031	0.630 (0.453–0.876)	0.006
MRAs	1.246 (0.612–2.541)	0.544	1.164 (0.774–1.753)	0.466	1.118 (0.821–1.523)	0.478
Loop diuretics	1.674 (0.399–7.022)	0.481	2.074 (0.838–5.129)	0.114	1.655 (0.891–3.075)	0.111
VRAs	2.164 (0.934–5.015)	0.072	2.457 (1.525–3.958)	<0.001	3.208 (2.266–4.543)	<0.001
Digitalis	1.397 (0.574–3.398)	0.462	0.851 (0.462–1.566)	0.604	1.083 (0.707–1.658)	0.715
Oral inotropes	2.544 (1.175–5.504)	0.018	2.704 (1.729–4.227)	<0.001	3.465 (2.490–4.821)	<0.001
HF hospitalization	Event n=321		Event n=614		Event n=831
RAS inhibitors	0.680 (0.533–0.867)	0.002	0.681 (0.566–0.819)	<0.001	0.755 (0.638–0.892)	<0.001
β-blockers	0.857 (0.654–1.124)	0.265	0.949 (0.770–1.170)	0.624	0.946 (0.786–1.140)	0.560
MRAs	0.725 (0.574–0.915)	0.007	0.911 (0.763–1.087)	0.301	0.938 (0.802–1.098)	0.429
Loop diuretics	1.518 (0.962–2.396)	0.073	1.400 (1.009–1.942)	0.044	1.171 (0.891–1.539)	0.259
VRAs	2.268 (1.688–3.047)	<0.001	2.560 (2.035–3.222)	<0.001	2.406 (1.942–2.981)	<0.001
Digitalis	0.680 (0.464–0.997)	0.048	0.788 (0.601–1.033)	0.084	0.926 (0.736–1.165)	0.510
Oral inotropes	2.351 (1.779–3.107)	<0.001	2.689 (2.165–3.339)	<0.001	2.849 (2.333–3.479)	<0.001

OR, odds ratio. Other abbreviations as in Tables 1,2.

Figure 3.

Association between medical treatment and post-discharge composite endpoint (event n=1,699/4,008): Cox proportional hazard analysis. The prognostic impact of the medications at discharge on the composite endpoint was assessed across the 6 regions with a forest plot, which revealed a similar trend across the regions. MRA, mineralocorticoid receptor antagonist; RAS, renin-angiotensin system; VRA, vasopressin receptor antagonist.

Figure 4.

Association between medical treatment and post-discharge cardiac death (event n=720/4,008): Cox proportional hazard analysis. The prognostic impact of the medications at discharge on cardiac death was assessed across the 6 regions with a forest plot, which revealed a similar trend across the regions. MRA, mineralocorticoid receptor antagonist; RAS, renin-angiotensin system; VRA, vasopressin receptor antagonist.

Figure 5.

Association between medical treatment and post-discharge HF hospitalization (event n=1,478/4,008): Cox proportional hazard analysis. The prognostic impact of the medications at discharge on HF hospitalization was assessed was assessed across the 6 regions with a forest plot, which revealed a significant interaction between the use of MRAs and regions. HF, heart failure; MRA, mineralocorticoid receptor antagonist; RAS, renin-angiotensin system; VRA, vasopressin receptor antagonist.

Discussion

Our post-hoc analyses of JROADHF firstly revealed regional variations in the HFrEF patients’ characteristics, treatments, and prognoses throughout Japan. In this aging society, there are variations, including age, etiology of HF, precipitating factors, and medications. On the other hand, comorbidities and prognoses were comparable among the 6 regions.

Previous subnational observational studies have revealed variations of non-communicable diseases, including IHD, cancer, cerebrovascular disease, and chronic obstructive pulmonary disease, in the UK,²² Mexico,²³ and China.²⁴ These findings are important for policy makers to understand the health needs of each region and to improve domestic health conditions. As for Japan, where life expectancy has been increasing,²⁵ the decrease in cardiovascular deaths is one of the leading causes of the increase in life expectancy.²⁵ However, the decrease in cardiovascular deaths has been mostly driven by the reduction of cerebrovascular diseases and IHD, and HF deaths have not changed dramatically.^25,26

There are several plausible mechanisms of these variations in etiology and precipitating factors of HF. First, age was lowest in the regions with more urban areas (the Kanto and Kinki regions). As aging of the population progresses, the etiology of HF often tends to be more multifactorial and includes more valvular diseases (e.g., aortic stenosis).^27,28 Second, regarding IHD, which accounted for approximately one-third of the etiology of HF, the use of PCI for angina and MI differed among the prefectures.²⁹ More specifically, the PCI rate for MI was higher in western Japan.²⁹ Because PCI reduces HF after MI,^28,30 the application rate of PCI for MI may have affected the prevalence of consequent HF. Similarly, although catheter ablation for atrial fibrillation can reduce HF hospitalization in patients with HFrEF,^28,31 a wide regional variation in the use of catheter ablation in Japan has been reported.³² According to the Japanese Diagnosis Procedure Combination/Per-Diem Payment System database, 7 of the top 10 prefectures with the highest catheter ablation rates are in the Kinki and Kyushu regions,³² which is consistent with our finding of the relatively low rate of arrhythmia as the etiology of HF in these regions. Although the prevalence of each comorbidity was equivalent in this study, these underlying variations in therapeutic procedures may have existed and affected the etiology of HF. Third, there are variations in lifestyle-associated behaviors, including salt intake and smoking, among the prefectures,²⁵ which may affect precipitating factors such as dietary non-compliance and uncontrolled hypertension.³³ These findings suggest that recognizing the risk factors and optimizing their management based on the characteristics of each region or prefecture could potentially reduce the HF burden nationwide.

Although there were wide variations in the patients’ characteristics, length of hospital stay and in-hospital mortality rates were comparable. To date, studies based on the Japanese Diagnosis Procedure Combination/Per-Diem Payment System database have revealed several therapeutic and institutional factors that are related to in-hospital prognosis.^34–38 Our results suggested that several patients’ characteristics and prognostic factors may have offset each other and resulted in comparable in-hospital mortality rates. Thus, adjusting patient care in each region may improve in-hospital prognoses throughout Japan.

This observational study revealed that the use of cardioprotective drugs for HFrEF at discharge was not equal or enough among the 6 regions despite being a Class I recommendation in major HF guidelines.^3–5,39 In addition, we confirmed the favorable prognostic effects of these cardioprotective drugs and the adverse effects of diuretics and oral inotropes. A prior study reported that prescription rates of cardioprotective drugs varied widely among hospitals.¹¹ In addition, considering the patients’ characteristics, there were several factors potentially associated with the prescription rate of cardioprotective drugs, such as age and NYHA functional class III or IV,^40–43 which were consistent with this study. Although loop diuretics can relieve signs and symptoms of congestion, their effects on prognosis are controversial.^4–6 One meta-analysis revealed that loop diuretics reduce deaths and worsening HF compared with placebo.⁴⁴ On the other hand, loop diuretics induce electrolyte disorders,^3,5,6 and observational studies have reported that use of loop diuretics, especially at high dose, are associated with impaired survival.^45,46 As to vasopressin receptor antagonists, this study demonstrated poor prognosis in patients who received these drugs. Considering the fact that randomized control trials have shown that these drugs have neutral effects on mortality rates,^47–49 patients who received these drugs in this study may have had more congestion and diuretic resistance, which result in deteriorated outcomes. To maintain euvolemia, the treatment goal of diuretic therapy, with the lowest dose of diuretics,^5,6 the volume status in patients with HF should be evaluated non-invasively using reliable tools.^50–52 Similar to previous studies,^53,54 oral inotropes were associated with unfavorable outcomes in this study, which indicated that patients on oral inotropes had advanced HF requiring inotropic agents to improve hypoperfusion and exercise capacity.^3,5,6,55,56 The usefulness of digitalis, which did not worsen the prognosis, should be reevaluated.^57,58 Despite these variations at discharge, post-discharge cardiospecific outcomes were comparable among the 6 regions. As with in-hospital prognosis, patients’ characteristics and treatment variations may have offset each other, leading to similar prognosis after discharge. Optimizing patient care in each region, including initiating and up-titrating cardioprotective drugs, may improve the overall prognosis of patients with HFrEF in Japan.^3–5,39

Study Limitations

Although this study was based on national big data, there are some limitations. First, because the JROADHF is based on patients’ records from 2013, pharmacological treatment at that time in Japan was, in some ways, different from how it is currently. Novel cardioprotective drugs for HFrEF, such as sodium-glucose cotransporter 2 inhibitors, angiotensin receptor-neprilysin inhibitors, I_f-channel inhibitors, and soluble guanylate cyclase stimulators, are discussed or recommended in the later HF guidelines.^3,4 The regional variations in the use of these drugs require future research. Second, the JROADHF data were collected by 128 institutions chosen by cluster random sampling.¹⁶ The patients’ characteristics may have been partly affected by institutional characteristics. Third, it was difficult to pursue detailed changes in post-discharge prescription rates of medications in the JROADHF. Fourth, the underlying mechanisms of an interaction found between the use of mineralocorticoid receptor antagonists and region remain unclear because this was an observational study. Differences in several factors, including doses, patients’ characteristics, and length of follow-up, may have affected the results.

Conclusions

There were no differences in the cardiospecific prognoses of patients with HFrEF across 6 regions in Japan.

Acknowledgments

The authors thank all participating institutions and investigators of the JROADHF.¹⁶ The authors thank Fumika Yamashita (Kyushu University Hospital, Japan), Makoto Yokobori (Suxac Inc., Japan), Tomoe Mashiko (Suxac Inc., Japan), Go Ichien (HuBit Genomix Inc., Japan), Masako Terauchi (HuBit Genomix Inc., Japan), Mao Kakinoki (HuBit Genomix Inc., Japan), Sachiko Matsuoka (HuBit Genomix Inc., Japan), Satoko Ishihara (G-ONE Inc., Japan) and Keigo Mori (G-ONE Inc., Japan) for their precious support of the JROADHF registry.¹⁶ The authors thank Hajime Iwasa (Fukushima Medical University, Japan) for his statistical support. The details of grant support have been described previously.¹⁶

This work was supported by the Japan Agency for Medical Research and Development grant (19ek0210097 h0003, 19ek0109339 h0002, 19ek0210080 h0003), Grants-in-Aid for Scientific Research from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (17K09582, 15H04815), and Health Labour Sciences Research Grant (20FC1051).

Disclosures

T.I., H.T., and Y.T. are members of Circulation Journal’s Editorial Team.

IRB Information

The original study protocol was approved by the institutional review boards of Kyushu University (2019-569), the Japanese Circulation Society (2017. No. 3) and all of the 128 participating hospitals.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-22-0774

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