Heart Vessels DOI 10.1007/s00380-014-0532-5
ORIGINAL ARTICLE
Risk factors for rehospitalization in heart failure with preserved ejection fraction compared with reduced ejection fraction Masahiko Setoguchi • Yuji Hashimoto • Taro Sasaoka • Takashi Ashikaga • Mitsuaki Isobe
Received: 28 October 2013 / Accepted: 30 May 2014 Ó Springer Japan 2014
Abstract Although there have been several studies regarding heart failure with preserved ejection fraction (HFpEF), investigations of the risk factors for readmission of Japanese patients with HFpEF remain scarce. Therefore, our goal was to identify the risk factors for readmission of Japanese patients with heart failure (HF), particularly those with HFpEF. We analyzed 310 patients who were hospitalized for the first time with HF. Preserved EF was defined EF C50 %, and reduced EF (rEF) was EF \50 %. The study endpoint was readmission for HF after discharge. Medical history, vital signs, electrocardiograms, chest radiographs, blood tests and echocardiograms were compared between patients with HFpEF and with HFrEF. Among the 142 patients who had HFpEF, 43 reached the endpoint within 1 year. Multivariate analysis revealed depression (HR: 7.185), high brain natriuretic peptide (BNP) levels at discharge (HR: 1.003), and dilated inferior vena cava (HR: 1.100) as independent risk factors for readmission. In contrast, 39 of the 168 patients with HFrEF reached the endpoint. Risk factors for readmission of HFrEF patients were low sodium (HR: 0.856), high blood urea nitrogen (HR: 1.045), high BNP levels at discharge (HR: 1.003) and absence of beta-blocker prescription (HR: 0.395). In conclusion, our study suggests that the predictors
M. Setoguchi (&) Y. Hashimoto Department of Cardiology, Kameda General Hospital, Kamogawa, Japan e-mail: [email protected] M. Setoguchi T. Sasaoka T. Ashikaga M. Isobe Department of Cardiovascular Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan e-mail: [email protected]
of HF readmission differ between HFpEF and HFrEF patients. Keywords Inferior vena cava Depression Heart failure with preserved ejection fraction Readmission
Introduction In recent years, it has been estimated that 30–50 % patients with heart failure (HF) have preserved ejection fraction (pEF). According to the JCARE-CARD study, the proportion of Japanese patients with HFpEF was 26 % [1], and with regard to the CHART-1 registry, it was 51.6 % [2]. HFpEF is clinically important because it has become a common disease. The number of patients with HFpEF has been increasing compared with those with HF and with decreased ejection fraction (HFrEF), and their prognosis is not good. Furthermore, despite advances in cardiology, no considerable improvement has been observed in the prognosis of patients with HFpEF [3, 4]. The treatment for HF has been changing annually because of the introduction of new drugs and new devices. Some studies stress importance of non-cardiac comorbidities of HFpEF patients and their management [5–8]. Therefore, although several studies have discussed the risk factors for readmission of patients with HFpEF, it is important to determine the specific risk factors for readmission of Japanese patients with HFpEF in community-based, countryside hospitals. By comparing the risk factors for readmission of patients with HFpEF and those with HFrEF, we may be able to identify characteristics specific to HFpEF; thus, we believe our study would provide clues to overcome this disease, and hence, we investigated the risk factors for readmission of patients with HFpEF.
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Subjects and methods Definition of HFpEF and HFrEF To diagnose HF, we used the Framingham criteria [9]. With regard to the definition of HFpEF, we employed the European Society of Cardiology (ESC) guidelines [10], and we used Doppler echocardiography to establish the diagnoses. Echocardiography was performed within 24 h after hospitalization. In clinical practice, the diagnosis is generally based on the observation of typical signs and symptoms in patients with HF with a normal left ventricular ejection fraction (LVEF) and no valvular abnormalities on echocardiography. In this study, we defined HFpEF according to the following criteria: (i) signs or symptoms of HF and (ii) LVEF C50 % as determined by echocardiography. Similarly, HFrEF was defined as (i) signs or symptoms of HF and (ii) LVEF \50 %. The modified Simpson’s method with 2D echo was used to measure LVEF. Subjects We retrospectively analyzed the information from a database of patients with new-onset HF who were admitted to Kameda General Hospital in Kamogawa City, Japan, between January 2008 and December 2010. All patients presented to the hospital with a primary diagnosis of HF. The study subjects were followed-up for 1 year after discharge. Patients were divided into two groups on the basis of EF status upon admission at the time of their first hospitalization for HF. Patients who were hospitalized primarily for acute coronary syndrome (ACS) with a secondary diagnosis of HF as well as those who were undergoing dialysis or who could not be followed-up until the study endpoint were excluded. The local ethics committee approved this study.
All depressive patients were followed-up by psychiatrists and used of antidepressant drugs. The estimated glomerular filtration rate (eGFR) was calculated as follows: eGFR = 186 9 [serum creatinine level (mg/dl)]-1.154 9 age-0.203 9 (male: 1, female: 0.742). The follow-up period was 1 year after discharge, and the study endpoint was readmission for HF, which met the Framingham criteria. Statistical analysis All the statistical analyses were conducted using the SPSS version 21.0 software. The Chi square test, Student’s t test and Kaplan–Meier survival curves were used to compare the appropriate categories. Univariate analysis was performed for all the items to determine those with statistical significance. To avoid multicollinearity, we calculated the coefficient of correlation (r) between two significant items of all the combinations, and items with r values \0.2 were selected for further scrutiny. Multivariate analysis was performed for those items using stepwise multiple regression analysis (step-up method). On multivariate analysis, the items with statistical significance were determined as risk factors. Receiver operating characteristic (ROC) curves were calculated to identify the cut-off values for quantitative risk factors. The Kaplan–Meier survival curves were calculated, and log-rank tests were performed to compare the categories. All the statistical analyses were two-sided, and p values \0.05 were considered statistically significant.
Results Altogether, there were 354 consecutive first-onset heart failure patients admitted to our hospital from 2008 to 2010,
Data collection The database contained 73 variables obtained from our hospital’s medical records, including signs and symptoms of HF, presence of coexisting cardiovascular and medical conditions, medications administered during hospitalization and those prescribed at discharge, laboratory test results, electrocardiogram, echocardiogram and chest radiographic data and vital signs at admission and discharge. Inferior vena cava (IVC) size was measured by echocardiography, and the maximum diameter was considered as the IVC size for the purpose of this study. In addition, depression was defined on the basis of patients’ medical records, using the Japanese version of the Center for Epidemiologic Studies Depression Scale (CES-D) [11].
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Fig. 1 Study flow chart
Heart Vessels Table 1 Baseline characteristics HFpEF
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value 0.245
Age (years)
80 ± 9
80 ± 8
79 ± 12
0.515
71 ± 15
70 ± 15
73 ± 15
Male
60 (42)
45 (45)
15 (35)
0.271
101 (60)
79 (61)
22 (56)
0.709
Hospital stay (days) Right bundle branch block
15 ± 11 28 (20)
14 ± 7 20 (20)
19 ± 17 8 (19)
0.005 1.000
17 ± 12 21 (13)
17 ± 12 13 (10)
19 ± 13 8 (21)
0.317 0.100
Left bundle branch block
7 (5)
4 (4)
3 (7)
0.433
30 (18)
23 (18)
7 (18)
1.000
Hypertension
91 (64)
63 (64)
28 (65)
1.000
105 (63)
82 (64)
23 (59)
0.706
Diabetes mellitus
39 (27)
25 (25)
14 (33)
0.415
49 (29)
38 (29)
11 (28)
1.000
Hyperlipidemia
45 (32)
33 (33)
12 (28)
0.562
50 (30)
43 (33)
7 (18)
0.074
Smoking
41 (29)
30 (30)
11 (26)
0.688
85 (51)
60 (47)
25 (64)
0.068
Atrial fibrillation
77 (54)
48 (48)
29 (67)
0.045
61 (36)
48 (37)
13 (33)
0.708
Stroke
25 (18)
15 (15)
10 (23)
0.337
18 (11)
15 (12)
3 (8)
0.768
Pacemaker/ICD/CRT
3 (2)
3 (3)
0 (0)
0.554
6 (4)
4 (3)
2 (5)
0.624
History of PCI
15 (11)
8 (8)
7 (16)
0.151
9 (5)
5 (4)
4 (10)
0.215
History of CABG History of MI
11 (8) 19 (13)
9 (9) 9 (9)
2 (5) 10 (23)
0.504 0.032
13 (8) 37 (22)
11 (9) 26 (20)
2 (5) 11 (28)
0.735 0.281
Single life
12 (9)
9 (9)
3 (7)
1.000
16 (10)
12 (9)
4 (10)
1.000
Depression
12 (8)
4 (4)
9 (21)
0.003
13 (8)
9 (7)
4 (10)
0.502
Hypertensive
66 (46)
51 (52)
15 (35)
0.099
10 (6)
9 (7)
1 (3)
0.456
Dilated cardiomyopathy
0 (0)
0 (0)
0 (0)
n/a
99 (59)
77 (60)
22 (56)
0.715
Ischemic
12 (8)
7 (7)
5 (12)
0.512
33 (20)
24 (19)
9 (23)
0.655 0.619
Cause of heart failure
Undetermined
64 (45)
41 (41)
23 (53)
0.203
26 (15)
19 (15)
7 (18)
All-cause death
6 (4)
0 (0)
6 (14)
n/a
5 (3)
0 (0)
5 (13)
n/a
Cardiovascular-related death
6 (4)
0 (0)
6 (14)
n/a
5 (3)
0 (0)
5 (13)
n/a
Data are given as mean ± SD or n (%) PCI percutaneous coronary intervention, CABG coronary artery bypass graft, Single life person who is living alone, MI myocardial infarction
and 44 of them were excluded due to exclusion criteria (Fig. 1). Of the remaining 310 patients enrolled in this study, 142 (45.8 %) were categorized as HFpEF, and 168 (54.2 %) were categorized as HFrEF. Baseline characteristics of the HFpEF and HFrEF groups are summarized in Table 1. There were significant differences between patients without events and those readmitted, in terms of medical history of atrial fibrillation (AF), hospital stay, history of myocardial infarction (MI), and depression in the HFpEF group; in contrast, there were no significant differences with regard to these in the HFrEF group. The rates of allcause mortality within 1 year after discharge were 4.2 and 3 % in patients with HFpEF and HFrEF, respectively. Similarly, the rates of readmission within 1 year after discharge were 30 and 23 %, respectively. The prescribed drugs are presented in Table 2, and laboratory data and
vital signs at admission and discharge are presented in Table 3. There were significant differences in potassium (K), blood urea nitrogen (BUN), creatinine, brain natriuretic peptide (BNP) levels at admission, IVC size at admission, and albumin, hemoglobin and BNP levels at discharge in the HFpEF group. Further, in the HFrEF group, significant differences were observed in hemoglobin levels and eGFR at admission, and sodium (Na), hemoglobin, BUN and BNP levels at discharge. We performed univariate analysis on all the items and selected those with p values \0.05. BUN, creatinine, BNP levels, IVC size at admission along with albumin, hemoglobin and BNP levels at discharge, length of hospital stay, medical history of AF, history of MI and depression had p values \0.05 in the HFpEF group. With regard to the HFrEF group, hemoglobin levels at admission and Na, hemoglobin, BUN and BNP levels at discharge, eGFR and
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Heart Vessels Table 2 Drugs Prescribed at discharge HFpEF
Diuretic
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value 0.687
116 (82)
78 (79)
38 (88)
0.239
159 (95)
121 (94)
38 (97)
Spironolactone
57 (40)
42 (42)
15 (35)
0.459
96 (57)
74 (57)
22 (56)
1.000
Beta-blocker ACE inhibitor
57 (40) 20 (14)
36 (36) 12 (12)
21 (49) 8 (19)
0.194 0.307
109 (65) 51 (30)
89 (69) 41 (32)
20 (51) 10 (26)
0.055 0.553
ARB
59 (42)
40 (40)
19 (44)
0.713
81 (48)
64 (50)
17 (44)
0.585
Calcium channel blocker
62 (44)
43 (43)
19 (44)
0.713
46 (27)
39 (30)
7 (18)
0.155
Aspirin
59 (42)
36 (36)
23 (53)
0.066
52 (31)
37 (29)
15 (38)
0.323
Clopidogrel
12 (8)
7 (7)
5 (12)
0.512
5 (3)
3 (2)
2 (5)
0.329
Warfarin
62 (44)
43 (43)
19 (44)
1.000
64 (38)
50 (39)
14 (36)
0.851
Statin
48 (34)
34 (34)
14 (32)
1.000
54 (32)
44 (34)
10 (26)
0.434
4 (3)
1 (1)
3 (7)
0.083
5 (3)
4 (3)
1 (3)
1.000
Amiodarone Digoxin
12 (8)
9 (9)
3 (7)
1.000
19 (11)
17 (13)
2 (5)
0.249
Isosorbide dinitrate
17 (12)
11 (11)
6 (14)
0.779
15 (9)
13 (10)
2 (5)
0.524
Data are given as n (%) ACE angiotensin converting enzyme, ARB angiotensin receptor blocker
no use of beta-blocker had p values \0.05. We calculated the coefficient of correlation (r) among these items in each group and selected items with r values \0.2. As a result, AF, history of MI, BNP levels at discharge, IVC size at admission and depression remained significant in the HFpEF group, and Na, BUN and BNP levels at discharge and no use of beta-blockers remained significant in the HFrEF group. Multivariate analysis revealed that history of depression, BNP levels at discharge, and IVC size at admission were independent risk factors for readmission of patients with HFpEF (Table 4). Decreased serum Na levels and increased BUN and BNP levels at discharge and the absence of beta-blocker prescription were independent risk factors for readmission of patients with HFrEF (Table 5). We assessed ROC curves to estimate the optimal cut-off values for the various risk factors for hospital readmission of patients with HFpEF and HFrEF as determined by multivariate analysis. The BNP cut-off value in the HFpEF group was 195.2 pg/ml, sensitivity was 0.698, specificity was 0.707 and the area under the curve (AUC) was 0.727. Further, with regard to IVC size of HFpEF, the cut-off value, sensitivity, specificity and AUC were 16.5 mm, 0.512, 0.717 and 0.651, respectively. Moreover, with regard to the HFrEF group, the Na cut-off value was 137.5 mEq/l, that of BNP at discharge was 207.0 pg/ml and that of BUN was 30.5 mg/dl. For statistical purposes, we rounded the cut-off values for BNP of HFpEF to 200 pg/ml, IVC size to 17 mm and Na to 137 mEq/l and those for BNP of HFrEF to 200 pg/ml and BUN to 30 mg/ dl.
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Using these cut-off values, we calculated the Kaplan– Meier survival curves and compared them using the logrank tests (Figs. 2, 3). Significant differences were determined for all the factors.
Discussion Several previous studies have investigated the relationship between HFpEF and its prognosis; these reported that patients with HFpEF were mostly elderly individuals, female, hypertensive, and with AF [1, 3]. The same tendency was observed in the baseline characteristics of patients in our study. The rehospitalization and mortality rates of HFpEF in our study were 30.2 and 4.2 %, respectively, whereas these rates in the JCARE-CARD were 25.7 and 11.6 %, respectively [1, 12]. The difference in rehospitalization and mortality rate between our study and the JCARE-CARD registry may derive from the difference in definition of HFpEF and HFrEF, and the exclusion criteria of our study. Beta-blockers, angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) were similarly used between the patients with no events and those who were readmitted in the HFpEF group. The effects of ACEI, ARB and betablockers for HFpEF have been controversial. ACEI improved the short-term prognosis, including rehospitalization within 1 year in the PEP-CHF trial [13], and ARB had a moderate impact on preventing admission for HFpEF in the CHARM trial [14]. However, Massie BM et al. [15]
Heart Vessels Table 3 Laboratory data and vital signs at admission and discharge HFpEF
At admission Na (mEq/l) K (mEq/l) Albumin (g/dl) Hemoglobin (g/dl) Blood urea nitrogen (mg/dl) Creatinine (mg/dl) eGFR (ml/min/1.73 m2) BNP (pg/ml) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Heart rate (bpm) Ejection fraction (%) LVDD (mm) Inferior vena cava (mm) At discharge Na (mEq/l) K (mEq/l) Albumin (g/dl) Hemoglobin (g/dl) Blood urea nitrogen (mg/dl) Creatinine (mg/dl) eGFR (ml/min/1.73 m2) BNP (pg/ml) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Heart rate (bpm)
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value
139 4.3 3.5 11.6 25 1.1 50 674 147 76 84 63 47 15
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.7 0.4 2.0 13 0.6 20 485 32 23 29 9 7 6
140 4.3 3.5 11.8 23 1.0 51 612 149 74 82 65 46 14
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.6 0.5 2.1 10 0.5 19 435 30 22 30 10 7 6
139 4.5 3.5 11.1 29 1.3 48 811 143 80 90 58 49 17
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.7 0.4 1.9 15 0.7 22 562 36 24 28 6 7 5
0.164 0.036 0.799 0.053 0.004 0.027 0.435 0.024 0.325 0.136 0.127 \0.001 0.862 0.005
140 4.3 3.5 12.8 22 1.0 83 954 144 86 107 37 57 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.4 2.3 11 0.5 33 588 32 23 26 8 8 5
140 4.3 3.5 13.0 21 1.0 84 912 144 86 106 37 57 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.4 2.4 11 0.6 33 608 32 24 25 8 8 5
140 4.2 3.4 12.0 23 1.0 81 1091 146 88 108 36 56 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
3 0.6 0.5 1.8 11 0.5 35 499 31 21 27 8 8 6
0.503 0.348 0.411 0.024 0.438 0.846 0.550 0.095 0.733 0.561 0.764 0.791 0.747 0.917
140 4.4 3.6 11.7 28 1.1 70 245 118 61 74
± ± ± ± ± ± ± ± ± ± ±
4 0.5 0.4 2.0 13 0.6 29 236 18 11 14
140 4.4 3.6 12.1 27 1.1 72 208 119 61 73
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.4 2.0 12 0.6 28 200 18 10 13
140 4.5 3.4 11.0 29 1.2 68 343 117 61 75
± ± ± ± ± ± ± ± ± ± ±
5 0.5 0.4 1.9 15 0.6 30 265 20 11 16
0.936 0.806 0.022 0.004 0.335 0.439 0.431 0.001 0.625 0.961 0.414
139 4.5 3.6 12.9 25 1.0 70 316 115 61 75
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.5 2.5 12 0.5 29 290 15 12 13
139 4.4 3.6 13.1 23 1.0 71 260 116 62 75
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.5 2.5 10 0.5 29 219 16 12 13
137 4.6 3.4 12.2 32 1.1 60 499 112 60 76
± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.5 2.2 15 0.5 29 404 14 11 12
0.006 0.083 0.063 0.047 \0.001 0.141 0.180 \0.001 0.094 0.346 0.461
Data are given as mean ± SD LVDD left ventricular diastolic diameter, BNP brain natriuretic peptide, eGFR estimated glomerular filtration rate
Table 4 Univariate and multivariate analysis of HFpEF
HR hazard ratio, CI confidence interval, BNP brain natriuretic peptide, MI myocardial infarction
Univariate analysis
Stepwise multivariate analysis
HR (95 % CI)
p value
HR (95 % CI)
p value
BNP at discharge
1.003 (1.001–1.004)
0.002
1.003 (1.001–1.004)
0.003
Atrial fibrillation
2.201 (1.040–4.658)
0.039
History of MI
3.030 (1.132–8.114)
0.027
Depression
6.728 (1.818–21.751)
0.004
7.185 (1.722–29.976)
0.007
Inferior vena cava
1.098 (1.023–1.179)
0.010
1.100 (1.022–1.184)
0.011
reported that ARB did not decrease the risk of death and hospitalization. Further, with regard to beta-blockers, few studies have reported the effects of beta-blockers on HFpEF, and clinical trials investigating the role of betablockers for HFpEF are ongoing [16, 17]. Moreover, in our study, we could not determine whether the absence of
ACEI, ARB and beta-blocker use was a risk factor for readmission of patients with HFpEF. We determined three risk factors for HFpEF and four risk factors for HFrEF from our study population using multivariate analysis (Tables 4, 5). The results of risk factors for HFrEF in our study were in accordance with
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those of previous studies [18–21]. Kallistratos MS et al. [22] reported that low systolic blood pressure was related to poor prognosis in HFrEF patients, but vital signs including blood pressure were not related with cardiac event in our study. Table 5 Univariate and multivariate analysis of HFrEF Univariate analysis
Stepwise multivariate analysis
HR (95 % CI)
HR (95 % CI)
p value 0.011
p value
Na at discharge BUN at discharge
0.862 0.008 (0.773–0.962) 1.059 \0.001 (1.027–1.092)
0.856 (0.760–0.965) 1.045 (1.010–1.081)
BNP at discharge
1.003 \0.001 (1.001–1.004)
1.003 \0.001 (1.001–1.004)
Beta-blocker
0.473 (0.228–0.982)
0.395 (0.169–0.921)
0.045
0.012
0.032
HR hazard ratio, CI confidence interval, BUN blood urea nitrogen, BNP brain natriuretic peptide
Fig. 2 The Kaplan–Meier survival curves for HFpEF
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According to a previous report, the prevalence rate of clinically significant depression with HF was 21.5 % [23]. With regard to the pathophysiological mechanisms in patients with HF with depression, neurohormonal activation, rhythm disturbances, inflammation and hypercoagulability are believed to play a major role in the development, progression and outcomes of HF [24]. In addition, it could be possible that poor adherence and lack of social support in patients with depression are related to readmission as psychosocial mechanisms. Furthermore, the side effects of antidepressant drugs may be related to readmission of patients with HFpEF. Kato et al. [25] reported that depressive symptoms are associated with adverse clinical outcomes in both HFrEF and HFpEF; however, in our study, depression was a readmission risk for patients with HFpEF but not for those with HFrEF. Further investigation is needed to resolve this inconsistency. Dilated IVC reflects volume overload of the right heart, pulmonary hypertension and elevated right atrial pressure.
Heart Vessels
Fig. 3 The Kaplan–Meier survival curves for HFrEF
Lam et al. [26] reported that pulmonary hypertension (PH) was highly prevalent in HFpEF (prevalence 25–44 %), and could contribute to progression of HFpEF. Nath et al. [27] reported that dilated inferior vena cava was a marker of poor prognosis of HF patients. Therefore, this result was consistent with past studies. To estimate the risk factors of HFpEF patients, the role of echocardiography is important and various parameters related to echocardiography have been proposed recently [28]. Other echocardiographic parameters except IVC should be investigated. Marechaux et al. [8] reported that anemia and eGFR were associated with a poor outcome. In our study, the p value of hemoglobin in univariate analysis was 0.059, therefore it may have achieved statistical significance, had we lengthened our follow-up period. Since hemoglobin was correlated with eGFR in our study, we could not include both hemoglobin and eGFR in multivariate analysis, and eGFR could not be identified as a risk factor. In general, renal function is often understandably correlated with anemia due to the fact that erythropoietin is produced in the kidneys, and we could not estimate these variables from our database. Therefore, further investigation is needed to confirm eGFR as a risk factor.
The cut-off values of Na and BNP at discharge for patients with HFrEF, which were derived from the ROC curves in the present study, were approximately the same as those reported in previous studies [18, 29, 30]. West et al. [31] reported that clinical characteristics, in-patient interventions, and discharge therapies for HFpEF vary significantly across various geographical regions. In fact, our results were derived from patient data from a rural, community-based hospital in Japan. Thus, the regional characteristics of HFpEF should be taken into account as well. As Ather et al. [5] pointed out, HFpEF is affected by non-cardiac comorbidities. Our results similarly suggest the importance of investigating relationships between HFpEF and non-cardiac comorbidities. Clinical implications There are no decisive approaches for treating HFpEF at this time. Therefore, preventing recurrence of HFpEF by managing the risk factors for readmission of patients with HFpEF is likely the best strategy. Our current results show that depression, dilated IVC at admission and higher BNP levels at discharge are risk factors for readmission in patients with
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HFpEF. Therefore, therapy specifically aimed at depression, meticulous monitoring of BNP levels, and assessment of IVC, may help reduce readmission for HFpEF.
6.
Limitations
7.
Our study had several limitations. Our event rates such as for cardiovascular-related death were smaller than in previous studies. We believe this was due to the difference in exclusion criteria, definition of HFpEF, and study population. Because the sample size in our study was small, our results must be confirmed by prospective studies involving larger patient samples. Items such as depression may not be reliably evaluated through retrospective data. The severity of depression was unknown in our study. Finally, it is possible that poor adherence to prescribed medications affected patient outcomes, but this information was not available in medical records, and was not something we were able to evaluate.
8.
9.
10.
Conclusion Our results suggest that depression, higher BNP level at discharge and dilated IVC size at admission are risk factors for readmission in Japanese patients with HFpEF. Therefore, when patients with HFpEF are evaluated, the possibility of the presence of these risk factors should be considered. 11. Conflict of interest The authors have no potential conflicts of interests to disclose.
12.
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16.
17.
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24. Joynt KE, Whellan DJ, O’Connor CM (2004) Why is depression bad for the failing heart? A review of the mechanistic relationship between depression and heart failure. J Card Fail 10:258–271 25. Kato N, Kinugawa K, Shiga T, Hatano M, Takeda N, Imai Y, Watanabe M, Yao A, Hirata Y, Kazuma K, Nagai R (2012) Depressive symptoms are common and associated with adverse clinical outcomes in heart failure with reduced and preserved ejection fraction. J Cardiol 60:23–30 26. Lam CS, Roger VL, Rodeheffer RJ, Borlaug BA, Enders FT, Redfield MM (2009) Pulmonary hypertension in heart failure with preserved ejection fraction. A community-based study. J Am Coll Cardiol 53:1119–1126 27. Nath J, Vacek JL, Heidenreich PA (2006) A dilated inferior vena cava is a marker of poor survival. Am Heart J 151:730–735 28. Tanaka Y, Taniguchi M, Sugawara M, Nobusada S, Kusano K, Akagi T, Ito H (2013) Evaluation of exercise capacity using wave intensity in chronic heart failure with normal ejection fraction. Heart Vessels 28:179–187 29. Cournot M, Mourre F, Castel F, Ferrieres J, Destrac S (2008) Optimization of the use of b-type natriuretic peptide levels for risk stratification at discharge in elderly patients with decompensated heart failure. Am Heart J 155:986–991 30. Valle R, Aspromonte N, Feola M, Milli M, Canali C, Giovinazzo P, Carbonieri E, Ceci V, Cerisano S, Barro S, Milani L (2005) B-type natriuretic peptide can predict the medium-term risk in patients with acute heart failure and preserved systolic function. J Card Fail 11:498–503 31. West R, Liang L, Fonarow GC, Kociol R, Mills RM, O’Connor CM, Hernandez F (2011) Characteristics of heart failure patients with preserved ejection fraction: a comparison between ADHERE-US registry and ADHERE-international registry. Eur J Heart Fail 13:945–952
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ORIGINAL ARTICLE
Risk factors for rehospitalization in heart failure with preserved ejection fraction compared with reduced ejection fraction Masahiko Setoguchi • Yuji Hashimoto • Taro Sasaoka • Takashi Ashikaga • Mitsuaki Isobe
Received: 28 October 2013 / Accepted: 30 May 2014 Ó Springer Japan 2014
Abstract Although there have been several studies regarding heart failure with preserved ejection fraction (HFpEF), investigations of the risk factors for readmission of Japanese patients with HFpEF remain scarce. Therefore, our goal was to identify the risk factors for readmission of Japanese patients with heart failure (HF), particularly those with HFpEF. We analyzed 310 patients who were hospitalized for the first time with HF. Preserved EF was defined EF C50 %, and reduced EF (rEF) was EF \50 %. The study endpoint was readmission for HF after discharge. Medical history, vital signs, electrocardiograms, chest radiographs, blood tests and echocardiograms were compared between patients with HFpEF and with HFrEF. Among the 142 patients who had HFpEF, 43 reached the endpoint within 1 year. Multivariate analysis revealed depression (HR: 7.185), high brain natriuretic peptide (BNP) levels at discharge (HR: 1.003), and dilated inferior vena cava (HR: 1.100) as independent risk factors for readmission. In contrast, 39 of the 168 patients with HFrEF reached the endpoint. Risk factors for readmission of HFrEF patients were low sodium (HR: 0.856), high blood urea nitrogen (HR: 1.045), high BNP levels at discharge (HR: 1.003) and absence of beta-blocker prescription (HR: 0.395). In conclusion, our study suggests that the predictors
M. Setoguchi (&) Y. Hashimoto Department of Cardiology, Kameda General Hospital, Kamogawa, Japan e-mail: [email protected] M. Setoguchi T. Sasaoka T. Ashikaga M. Isobe Department of Cardiovascular Medicine, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan e-mail: [email protected]
of HF readmission differ between HFpEF and HFrEF patients. Keywords Inferior vena cava Depression Heart failure with preserved ejection fraction Readmission
Introduction In recent years, it has been estimated that 30–50 % patients with heart failure (HF) have preserved ejection fraction (pEF). According to the JCARE-CARD study, the proportion of Japanese patients with HFpEF was 26 % [1], and with regard to the CHART-1 registry, it was 51.6 % [2]. HFpEF is clinically important because it has become a common disease. The number of patients with HFpEF has been increasing compared with those with HF and with decreased ejection fraction (HFrEF), and their prognosis is not good. Furthermore, despite advances in cardiology, no considerable improvement has been observed in the prognosis of patients with HFpEF [3, 4]. The treatment for HF has been changing annually because of the introduction of new drugs and new devices. Some studies stress importance of non-cardiac comorbidities of HFpEF patients and their management [5–8]. Therefore, although several studies have discussed the risk factors for readmission of patients with HFpEF, it is important to determine the specific risk factors for readmission of Japanese patients with HFpEF in community-based, countryside hospitals. By comparing the risk factors for readmission of patients with HFpEF and those with HFrEF, we may be able to identify characteristics specific to HFpEF; thus, we believe our study would provide clues to overcome this disease, and hence, we investigated the risk factors for readmission of patients with HFpEF.
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Heart Vessels
Subjects and methods Definition of HFpEF and HFrEF To diagnose HF, we used the Framingham criteria [9]. With regard to the definition of HFpEF, we employed the European Society of Cardiology (ESC) guidelines [10], and we used Doppler echocardiography to establish the diagnoses. Echocardiography was performed within 24 h after hospitalization. In clinical practice, the diagnosis is generally based on the observation of typical signs and symptoms in patients with HF with a normal left ventricular ejection fraction (LVEF) and no valvular abnormalities on echocardiography. In this study, we defined HFpEF according to the following criteria: (i) signs or symptoms of HF and (ii) LVEF C50 % as determined by echocardiography. Similarly, HFrEF was defined as (i) signs or symptoms of HF and (ii) LVEF \50 %. The modified Simpson’s method with 2D echo was used to measure LVEF. Subjects We retrospectively analyzed the information from a database of patients with new-onset HF who were admitted to Kameda General Hospital in Kamogawa City, Japan, between January 2008 and December 2010. All patients presented to the hospital with a primary diagnosis of HF. The study subjects were followed-up for 1 year after discharge. Patients were divided into two groups on the basis of EF status upon admission at the time of their first hospitalization for HF. Patients who were hospitalized primarily for acute coronary syndrome (ACS) with a secondary diagnosis of HF as well as those who were undergoing dialysis or who could not be followed-up until the study endpoint were excluded. The local ethics committee approved this study.
All depressive patients were followed-up by psychiatrists and used of antidepressant drugs. The estimated glomerular filtration rate (eGFR) was calculated as follows: eGFR = 186 9 [serum creatinine level (mg/dl)]-1.154 9 age-0.203 9 (male: 1, female: 0.742). The follow-up period was 1 year after discharge, and the study endpoint was readmission for HF, which met the Framingham criteria. Statistical analysis All the statistical analyses were conducted using the SPSS version 21.0 software. The Chi square test, Student’s t test and Kaplan–Meier survival curves were used to compare the appropriate categories. Univariate analysis was performed for all the items to determine those with statistical significance. To avoid multicollinearity, we calculated the coefficient of correlation (r) between two significant items of all the combinations, and items with r values \0.2 were selected for further scrutiny. Multivariate analysis was performed for those items using stepwise multiple regression analysis (step-up method). On multivariate analysis, the items with statistical significance were determined as risk factors. Receiver operating characteristic (ROC) curves were calculated to identify the cut-off values for quantitative risk factors. The Kaplan–Meier survival curves were calculated, and log-rank tests were performed to compare the categories. All the statistical analyses were two-sided, and p values \0.05 were considered statistically significant.
Results Altogether, there were 354 consecutive first-onset heart failure patients admitted to our hospital from 2008 to 2010,
Data collection The database contained 73 variables obtained from our hospital’s medical records, including signs and symptoms of HF, presence of coexisting cardiovascular and medical conditions, medications administered during hospitalization and those prescribed at discharge, laboratory test results, electrocardiogram, echocardiogram and chest radiographic data and vital signs at admission and discharge. Inferior vena cava (IVC) size was measured by echocardiography, and the maximum diameter was considered as the IVC size for the purpose of this study. In addition, depression was defined on the basis of patients’ medical records, using the Japanese version of the Center for Epidemiologic Studies Depression Scale (CES-D) [11].
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Fig. 1 Study flow chart
Heart Vessels Table 1 Baseline characteristics HFpEF
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value 0.245
Age (years)
80 ± 9
80 ± 8
79 ± 12
0.515
71 ± 15
70 ± 15
73 ± 15
Male
60 (42)
45 (45)
15 (35)
0.271
101 (60)
79 (61)
22 (56)
0.709
Hospital stay (days) Right bundle branch block
15 ± 11 28 (20)
14 ± 7 20 (20)
19 ± 17 8 (19)
0.005 1.000
17 ± 12 21 (13)
17 ± 12 13 (10)
19 ± 13 8 (21)
0.317 0.100
Left bundle branch block
7 (5)
4 (4)
3 (7)
0.433
30 (18)
23 (18)
7 (18)
1.000
Hypertension
91 (64)
63 (64)
28 (65)
1.000
105 (63)
82 (64)
23 (59)
0.706
Diabetes mellitus
39 (27)
25 (25)
14 (33)
0.415
49 (29)
38 (29)
11 (28)
1.000
Hyperlipidemia
45 (32)
33 (33)
12 (28)
0.562
50 (30)
43 (33)
7 (18)
0.074
Smoking
41 (29)
30 (30)
11 (26)
0.688
85 (51)
60 (47)
25 (64)
0.068
Atrial fibrillation
77 (54)
48 (48)
29 (67)
0.045
61 (36)
48 (37)
13 (33)
0.708
Stroke
25 (18)
15 (15)
10 (23)
0.337
18 (11)
15 (12)
3 (8)
0.768
Pacemaker/ICD/CRT
3 (2)
3 (3)
0 (0)
0.554
6 (4)
4 (3)
2 (5)
0.624
History of PCI
15 (11)
8 (8)
7 (16)
0.151
9 (5)
5 (4)
4 (10)
0.215
History of CABG History of MI
11 (8) 19 (13)
9 (9) 9 (9)
2 (5) 10 (23)
0.504 0.032
13 (8) 37 (22)
11 (9) 26 (20)
2 (5) 11 (28)
0.735 0.281
Single life
12 (9)
9 (9)
3 (7)
1.000
16 (10)
12 (9)
4 (10)
1.000
Depression
12 (8)
4 (4)
9 (21)
0.003
13 (8)
9 (7)
4 (10)
0.502
Hypertensive
66 (46)
51 (52)
15 (35)
0.099
10 (6)
9 (7)
1 (3)
0.456
Dilated cardiomyopathy
0 (0)
0 (0)
0 (0)
n/a
99 (59)
77 (60)
22 (56)
0.715
Ischemic
12 (8)
7 (7)
5 (12)
0.512
33 (20)
24 (19)
9 (23)
0.655 0.619
Cause of heart failure
Undetermined
64 (45)
41 (41)
23 (53)
0.203
26 (15)
19 (15)
7 (18)
All-cause death
6 (4)
0 (0)
6 (14)
n/a
5 (3)
0 (0)
5 (13)
n/a
Cardiovascular-related death
6 (4)
0 (0)
6 (14)
n/a
5 (3)
0 (0)
5 (13)
n/a
Data are given as mean ± SD or n (%) PCI percutaneous coronary intervention, CABG coronary artery bypass graft, Single life person who is living alone, MI myocardial infarction
and 44 of them were excluded due to exclusion criteria (Fig. 1). Of the remaining 310 patients enrolled in this study, 142 (45.8 %) were categorized as HFpEF, and 168 (54.2 %) were categorized as HFrEF. Baseline characteristics of the HFpEF and HFrEF groups are summarized in Table 1. There were significant differences between patients without events and those readmitted, in terms of medical history of atrial fibrillation (AF), hospital stay, history of myocardial infarction (MI), and depression in the HFpEF group; in contrast, there were no significant differences with regard to these in the HFrEF group. The rates of allcause mortality within 1 year after discharge were 4.2 and 3 % in patients with HFpEF and HFrEF, respectively. Similarly, the rates of readmission within 1 year after discharge were 30 and 23 %, respectively. The prescribed drugs are presented in Table 2, and laboratory data and
vital signs at admission and discharge are presented in Table 3. There were significant differences in potassium (K), blood urea nitrogen (BUN), creatinine, brain natriuretic peptide (BNP) levels at admission, IVC size at admission, and albumin, hemoglobin and BNP levels at discharge in the HFpEF group. Further, in the HFrEF group, significant differences were observed in hemoglobin levels and eGFR at admission, and sodium (Na), hemoglobin, BUN and BNP levels at discharge. We performed univariate analysis on all the items and selected those with p values \0.05. BUN, creatinine, BNP levels, IVC size at admission along with albumin, hemoglobin and BNP levels at discharge, length of hospital stay, medical history of AF, history of MI and depression had p values \0.05 in the HFpEF group. With regard to the HFrEF group, hemoglobin levels at admission and Na, hemoglobin, BUN and BNP levels at discharge, eGFR and
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Heart Vessels Table 2 Drugs Prescribed at discharge HFpEF
Diuretic
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value 0.687
116 (82)
78 (79)
38 (88)
0.239
159 (95)
121 (94)
38 (97)
Spironolactone
57 (40)
42 (42)
15 (35)
0.459
96 (57)
74 (57)
22 (56)
1.000
Beta-blocker ACE inhibitor
57 (40) 20 (14)
36 (36) 12 (12)
21 (49) 8 (19)
0.194 0.307
109 (65) 51 (30)
89 (69) 41 (32)
20 (51) 10 (26)
0.055 0.553
ARB
59 (42)
40 (40)
19 (44)
0.713
81 (48)
64 (50)
17 (44)
0.585
Calcium channel blocker
62 (44)
43 (43)
19 (44)
0.713
46 (27)
39 (30)
7 (18)
0.155
Aspirin
59 (42)
36 (36)
23 (53)
0.066
52 (31)
37 (29)
15 (38)
0.323
Clopidogrel
12 (8)
7 (7)
5 (12)
0.512
5 (3)
3 (2)
2 (5)
0.329
Warfarin
62 (44)
43 (43)
19 (44)
1.000
64 (38)
50 (39)
14 (36)
0.851
Statin
48 (34)
34 (34)
14 (32)
1.000
54 (32)
44 (34)
10 (26)
0.434
4 (3)
1 (1)
3 (7)
0.083
5 (3)
4 (3)
1 (3)
1.000
Amiodarone Digoxin
12 (8)
9 (9)
3 (7)
1.000
19 (11)
17 (13)
2 (5)
0.249
Isosorbide dinitrate
17 (12)
11 (11)
6 (14)
0.779
15 (9)
13 (10)
2 (5)
0.524
Data are given as n (%) ACE angiotensin converting enzyme, ARB angiotensin receptor blocker
no use of beta-blocker had p values \0.05. We calculated the coefficient of correlation (r) among these items in each group and selected items with r values \0.2. As a result, AF, history of MI, BNP levels at discharge, IVC size at admission and depression remained significant in the HFpEF group, and Na, BUN and BNP levels at discharge and no use of beta-blockers remained significant in the HFrEF group. Multivariate analysis revealed that history of depression, BNP levels at discharge, and IVC size at admission were independent risk factors for readmission of patients with HFpEF (Table 4). Decreased serum Na levels and increased BUN and BNP levels at discharge and the absence of beta-blocker prescription were independent risk factors for readmission of patients with HFrEF (Table 5). We assessed ROC curves to estimate the optimal cut-off values for the various risk factors for hospital readmission of patients with HFpEF and HFrEF as determined by multivariate analysis. The BNP cut-off value in the HFpEF group was 195.2 pg/ml, sensitivity was 0.698, specificity was 0.707 and the area under the curve (AUC) was 0.727. Further, with regard to IVC size of HFpEF, the cut-off value, sensitivity, specificity and AUC were 16.5 mm, 0.512, 0.717 and 0.651, respectively. Moreover, with regard to the HFrEF group, the Na cut-off value was 137.5 mEq/l, that of BNP at discharge was 207.0 pg/ml and that of BUN was 30.5 mg/dl. For statistical purposes, we rounded the cut-off values for BNP of HFpEF to 200 pg/ml, IVC size to 17 mm and Na to 137 mEq/l and those for BNP of HFrEF to 200 pg/ml and BUN to 30 mg/ dl.
123
Using these cut-off values, we calculated the Kaplan– Meier survival curves and compared them using the logrank tests (Figs. 2, 3). Significant differences were determined for all the factors.
Discussion Several previous studies have investigated the relationship between HFpEF and its prognosis; these reported that patients with HFpEF were mostly elderly individuals, female, hypertensive, and with AF [1, 3]. The same tendency was observed in the baseline characteristics of patients in our study. The rehospitalization and mortality rates of HFpEF in our study were 30.2 and 4.2 %, respectively, whereas these rates in the JCARE-CARD were 25.7 and 11.6 %, respectively [1, 12]. The difference in rehospitalization and mortality rate between our study and the JCARE-CARD registry may derive from the difference in definition of HFpEF and HFrEF, and the exclusion criteria of our study. Beta-blockers, angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) were similarly used between the patients with no events and those who were readmitted in the HFpEF group. The effects of ACEI, ARB and betablockers for HFpEF have been controversial. ACEI improved the short-term prognosis, including rehospitalization within 1 year in the PEP-CHF trial [13], and ARB had a moderate impact on preventing admission for HFpEF in the CHARM trial [14]. However, Massie BM et al. [15]
Heart Vessels Table 3 Laboratory data and vital signs at admission and discharge HFpEF
At admission Na (mEq/l) K (mEq/l) Albumin (g/dl) Hemoglobin (g/dl) Blood urea nitrogen (mg/dl) Creatinine (mg/dl) eGFR (ml/min/1.73 m2) BNP (pg/ml) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Heart rate (bpm) Ejection fraction (%) LVDD (mm) Inferior vena cava (mm) At discharge Na (mEq/l) K (mEq/l) Albumin (g/dl) Hemoglobin (g/dl) Blood urea nitrogen (mg/dl) Creatinine (mg/dl) eGFR (ml/min/1.73 m2) BNP (pg/ml) Systolic blood pressure (mmHg) Diastolic blood pressure (mmHg) Heart rate (bpm)
HFrEF
Total (n = 142)
No event (n = 99)
Event (n = 43)
p value
Total (n = 168)
No event (n = 129)
Event (n = 39)
p value
139 4.3 3.5 11.6 25 1.1 50 674 147 76 84 63 47 15
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.7 0.4 2.0 13 0.6 20 485 32 23 29 9 7 6
140 4.3 3.5 11.8 23 1.0 51 612 149 74 82 65 46 14
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.6 0.5 2.1 10 0.5 19 435 30 22 30 10 7 6
139 4.5 3.5 11.1 29 1.3 48 811 143 80 90 58 49 17
± ± ± ± ± ± ± ± ± ± ± ± ± ±
5 0.7 0.4 1.9 15 0.7 22 562 36 24 28 6 7 5
0.164 0.036 0.799 0.053 0.004 0.027 0.435 0.024 0.325 0.136 0.127 \0.001 0.862 0.005
140 4.3 3.5 12.8 22 1.0 83 954 144 86 107 37 57 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.4 2.3 11 0.5 33 588 32 23 26 8 8 5
140 4.3 3.5 13.0 21 1.0 84 912 144 86 106 37 57 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.4 2.4 11 0.6 33 608 32 24 25 8 8 5
140 4.2 3.4 12.0 23 1.0 81 1091 146 88 108 36 56 16
± ± ± ± ± ± ± ± ± ± ± ± ± ±
3 0.6 0.5 1.8 11 0.5 35 499 31 21 27 8 8 6
0.503 0.348 0.411 0.024 0.438 0.846 0.550 0.095 0.733 0.561 0.764 0.791 0.747 0.917
140 4.4 3.6 11.7 28 1.1 70 245 118 61 74
± ± ± ± ± ± ± ± ± ± ±
4 0.5 0.4 2.0 13 0.6 29 236 18 11 14
140 4.4 3.6 12.1 27 1.1 72 208 119 61 73
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.4 2.0 12 0.6 28 200 18 10 13
140 4.5 3.4 11.0 29 1.2 68 343 117 61 75
± ± ± ± ± ± ± ± ± ± ±
5 0.5 0.4 1.9 15 0.6 30 265 20 11 16
0.936 0.806 0.022 0.004 0.335 0.439 0.431 0.001 0.625 0.961 0.414
139 4.5 3.6 12.9 25 1.0 70 316 115 61 75
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.5 2.5 12 0.5 29 290 15 12 13
139 4.4 3.6 13.1 23 1.0 71 260 116 62 75
± ± ± ± ± ± ± ± ± ± ±
3 0.5 0.5 2.5 10 0.5 29 219 16 12 13
137 4.6 3.4 12.2 32 1.1 60 499 112 60 76
± ± ± ± ± ± ± ± ± ± ±
4 0.6 0.5 2.2 15 0.5 29 404 14 11 12
0.006 0.083 0.063 0.047 \0.001 0.141 0.180 \0.001 0.094 0.346 0.461
Data are given as mean ± SD LVDD left ventricular diastolic diameter, BNP brain natriuretic peptide, eGFR estimated glomerular filtration rate
Table 4 Univariate and multivariate analysis of HFpEF
HR hazard ratio, CI confidence interval, BNP brain natriuretic peptide, MI myocardial infarction
Univariate analysis
Stepwise multivariate analysis
HR (95 % CI)
p value
HR (95 % CI)
p value
BNP at discharge
1.003 (1.001–1.004)
0.002
1.003 (1.001–1.004)
0.003
Atrial fibrillation
2.201 (1.040–4.658)
0.039
History of MI
3.030 (1.132–8.114)
0.027
Depression
6.728 (1.818–21.751)
0.004
7.185 (1.722–29.976)
0.007
Inferior vena cava
1.098 (1.023–1.179)
0.010
1.100 (1.022–1.184)
0.011
reported that ARB did not decrease the risk of death and hospitalization. Further, with regard to beta-blockers, few studies have reported the effects of beta-blockers on HFpEF, and clinical trials investigating the role of betablockers for HFpEF are ongoing [16, 17]. Moreover, in our study, we could not determine whether the absence of
ACEI, ARB and beta-blocker use was a risk factor for readmission of patients with HFpEF. We determined three risk factors for HFpEF and four risk factors for HFrEF from our study population using multivariate analysis (Tables 4, 5). The results of risk factors for HFrEF in our study were in accordance with
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those of previous studies [18–21]. Kallistratos MS et al. [22] reported that low systolic blood pressure was related to poor prognosis in HFrEF patients, but vital signs including blood pressure were not related with cardiac event in our study. Table 5 Univariate and multivariate analysis of HFrEF Univariate analysis
Stepwise multivariate analysis
HR (95 % CI)
HR (95 % CI)
p value 0.011
p value
Na at discharge BUN at discharge
0.862 0.008 (0.773–0.962) 1.059 \0.001 (1.027–1.092)
0.856 (0.760–0.965) 1.045 (1.010–1.081)
BNP at discharge
1.003 \0.001 (1.001–1.004)
1.003 \0.001 (1.001–1.004)
Beta-blocker
0.473 (0.228–0.982)
0.395 (0.169–0.921)
0.045
0.012
0.032
HR hazard ratio, CI confidence interval, BUN blood urea nitrogen, BNP brain natriuretic peptide
Fig. 2 The Kaplan–Meier survival curves for HFpEF
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According to a previous report, the prevalence rate of clinically significant depression with HF was 21.5 % [23]. With regard to the pathophysiological mechanisms in patients with HF with depression, neurohormonal activation, rhythm disturbances, inflammation and hypercoagulability are believed to play a major role in the development, progression and outcomes of HF [24]. In addition, it could be possible that poor adherence and lack of social support in patients with depression are related to readmission as psychosocial mechanisms. Furthermore, the side effects of antidepressant drugs may be related to readmission of patients with HFpEF. Kato et al. [25] reported that depressive symptoms are associated with adverse clinical outcomes in both HFrEF and HFpEF; however, in our study, depression was a readmission risk for patients with HFpEF but not for those with HFrEF. Further investigation is needed to resolve this inconsistency. Dilated IVC reflects volume overload of the right heart, pulmonary hypertension and elevated right atrial pressure.
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Fig. 3 The Kaplan–Meier survival curves for HFrEF
Lam et al. [26] reported that pulmonary hypertension (PH) was highly prevalent in HFpEF (prevalence 25–44 %), and could contribute to progression of HFpEF. Nath et al. [27] reported that dilated inferior vena cava was a marker of poor prognosis of HF patients. Therefore, this result was consistent with past studies. To estimate the risk factors of HFpEF patients, the role of echocardiography is important and various parameters related to echocardiography have been proposed recently [28]. Other echocardiographic parameters except IVC should be investigated. Marechaux et al. [8] reported that anemia and eGFR were associated with a poor outcome. In our study, the p value of hemoglobin in univariate analysis was 0.059, therefore it may have achieved statistical significance, had we lengthened our follow-up period. Since hemoglobin was correlated with eGFR in our study, we could not include both hemoglobin and eGFR in multivariate analysis, and eGFR could not be identified as a risk factor. In general, renal function is often understandably correlated with anemia due to the fact that erythropoietin is produced in the kidneys, and we could not estimate these variables from our database. Therefore, further investigation is needed to confirm eGFR as a risk factor.
The cut-off values of Na and BNP at discharge for patients with HFrEF, which were derived from the ROC curves in the present study, were approximately the same as those reported in previous studies [18, 29, 30]. West et al. [31] reported that clinical characteristics, in-patient interventions, and discharge therapies for HFpEF vary significantly across various geographical regions. In fact, our results were derived from patient data from a rural, community-based hospital in Japan. Thus, the regional characteristics of HFpEF should be taken into account as well. As Ather et al. [5] pointed out, HFpEF is affected by non-cardiac comorbidities. Our results similarly suggest the importance of investigating relationships between HFpEF and non-cardiac comorbidities. Clinical implications There are no decisive approaches for treating HFpEF at this time. Therefore, preventing recurrence of HFpEF by managing the risk factors for readmission of patients with HFpEF is likely the best strategy. Our current results show that depression, dilated IVC at admission and higher BNP levels at discharge are risk factors for readmission in patients with
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HFpEF. Therefore, therapy specifically aimed at depression, meticulous monitoring of BNP levels, and assessment of IVC, may help reduce readmission for HFpEF.
6.
Limitations
7.
Our study had several limitations. Our event rates such as for cardiovascular-related death were smaller than in previous studies. We believe this was due to the difference in exclusion criteria, definition of HFpEF, and study population. Because the sample size in our study was small, our results must be confirmed by prospective studies involving larger patient samples. Items such as depression may not be reliably evaluated through retrospective data. The severity of depression was unknown in our study. Finally, it is possible that poor adherence to prescribed medications affected patient outcomes, but this information was not available in medical records, and was not something we were able to evaluate.
8.
9.
10.
Conclusion Our results suggest that depression, higher BNP level at discharge and dilated IVC size at admission are risk factors for readmission in Japanese patients with HFpEF. Therefore, when patients with HFpEF are evaluated, the possibility of the presence of these risk factors should be considered. 11. Conflict of interest The authors have no potential conflicts of interests to disclose.
12.
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