Correlation of Pre- and In-Hospital Systolic Blood Pressure in Acute Heart Failure Patients and the Prognostic Implications　– Report From the Tokyo Cardiac Care Unit Network Emergency Medical Service Database –

Abstract

Background: Systolic blood pressure (SBP) is an important prognostic indicator for patients with acute heart failure (AHF). However, its changes and the effects in the different phases of the acute management process are not well known.

Methods and Results: The Tokyo CCU Network prospectively collects on-site information about AHF from emergency medical services (EMS) and the emergency room (ER). The association between in-hospital death and SBP at 2 different time points (on-site SBP [measured by EMS] and in-hospital SBP [measured at the ER; ER-SBP]) was analyzed. From 2010 to 2012, a total of 5,669 patients were registered and stratified into groups according to both their on-site SBP and ER-SBP: >160 mmHg; 100–160 mmHg; and <100 mmHg. In-hospital mortality rates increased when both on-site SBP and ER-SBP were low. After multivariate adjustment, both SBPs were inversely associated with in-hospital death. Notably, the risk for patients with ER-SBP of 100–160 mmHg (intermediate risk) differed according to their on-site SBP; those with on-site SBP <100 or 100–160 mmHg were at higher risk (OR, 7.39; 95% CI, 4.00–13.6 and OR, 2.73; 95% CI, 1.83–4.08, respectively [P<0.001 for both]) than patients with on-site SBP >160 mmHg.

Conclusions: Monitoring changes in SBP assisted risk stratification of AHF patients, particularly patients with intermediate ER-SBP measurements. (Circ J 2016; 80: 2473–2481)

Acute heart failure (AHF) is frequently encountered by personnel of the emergency medical service (EMS) and in the emergency room (ER), and it is associated with several million hospitalizations worldwide each year, high mortality and morbidity rates, and high costs.^1,2 Despite the introduction of effective treatments for HF, 30-day mortality and readmission rates remain high,² and its management, particularly in the acute phase, remains a challenge.

Systolic blood pressure (SBP) is known to be an important prognostic indicator in patients with AHF.^3–8 The recent American College of Cardiology Foundation/American Heart Association (ACCF/AHA) heart failure guideline mentions the clinical application of several risk models, including one related to SBP, and further recommends that patients with clinically significant hypotension (SBP typically <90 mmHg or symptomatic low SBP) and/or worsening renal function during initial therapy might also benefit from invasive hemodynamic measurement.⁹ SBP is a benchmark for tailoring the treatment for AHF, such as vasodilators, diuretics, and inotropes.¹⁰ However, the prognostic implications of changes in SBP as measured during different stages of acute management for AHF are unknown. Typically, during the initial phase of AHF treatment, the patient’s overall condition is evaluated during different phases, and SBP is measured on-site by the EMS staff, on arrival at the ER, and at hospital admission. One study reported changes in SBP during the course of hospitalization,¹¹ but, to date, the value of measuring SBP during acute triage has not been thoroughly investigated.

In the present study, we aimed to evaluate the associations between SBP measured at 2 time points (pre-hospital [on-site by the EMS staff] and in hospital [at the ER]) and the clinical outcomes of patients with AHF. Monitoring alterations in SBP may provide additional information for tailoring the initial treatment strategy during acute triage of these patients. Additionally, assessing the prognostic implications may improve our understanding of AHF.

Methods

Study Design

The design of the Tokyo CCU Network (TCN) database has been previously reported.^12,13 Briefly, the TCN database is an ongoing multicenter registry that prospectively collects information from both EMS (Tokyo Metropolitan EMS) and investigators at participating hospitals on emergency admissions to acute cardiac facilities. Its aim is to describe the demographic and clinical characteristics of patients hospitalized with acute cardiovascular diseases. All patients admitted to cardiac care units (CCUs) whose information had been catalogued by the TCN were eligible for participation in the present study. By December 2015, 73 hospitals, serving a population of 1.3 million individuals in the metropolitan Tokyo area, were included in the TCN registry.

Each TCN hospital is accredited by the Metropolitan Tokyo Government and participates in the Tokyo citywide system of acute cardiac care (acute myocardial infarction, unstable angina, arrhythmia, AHF, aortic dissection, and pulmonary embolism). Written or oral informed consent was given in all cases by the patients, if appropriate, and/or by legal representative during their hospital admission according to the institution’s protocol. Both types of informed consent were approved by the TCN Scientific Committee, as the study did not identify individual patients. In addition, the TCN registry conducts an annual epidemiological survey supported by the Tokyo Metropolitan Government. Individual clinical information is recorded into the database by TCN members at each institution, and the final datasets are collected by the TCN Scientific Committee under conditions of anonymity, according to the ethical guidelines on epidemiological surveys released from the Japanese Ministry of Health, Labor, and Welfare. The protocol of the current study was approved by the Institutional Review Board of Keio University School of Medicine and the study was conducted in accordance with the Declaration of Helsinki.

Study Sample

For the present analysis, data for consecutive patients registered in the AHF dataset were extracted from the TCN database; patients presenting with acute coronary syndrome were registered in a separate dataset and were therefore not included in this analysis. We identified 6,232 AHF patients who were transferred via ambulance to a participating hospital between 2010 and 2012. Patients who presented with out-of-hospital cardiac arrest (n=90; 1.4%) and those with missing data for SBP measured in the ER (ER-SBP; n=473; 7.6%) were excluded. Their main clinical characteristics did not differ from those of the patients included in the final analysis, other than for ischemic etiology (30.1% vs. 21.1% in the excluded patients) and prior admissions for HF (31.9% vs. 15.6% in the excluded patients) (Table S1). Finally, data from 5,669 patients were analyzed in the present study (Figure 1).

Figure 1.

Flow chart for study of acute heart failure patients in metropolitan Tokyo. ER-SBP, systolic blood pressure measured on presentation to the emergency room.

EMS in Japan and BP Measurement

In Japan, non-private municipal emergency operation systems provide EMS through 800 fire stations via dispatching centers. The paramedics, similar to those in the Western system, provide medical care at an advanced life support level, though they have some limitations (eg, they are unable to use non-invasive positive airway pressure ventilation [NIPPV] or to administer drugs to patients, except for adrenalin in the case of cardiopulmonary arrest).^14,15 Pre-hospital SBP was measured on-site by the EMS team (on-site SBP), and the in-hospital SBP was measured in the emergency room (ER-SBP) by hospital triage staff. The on-site SBP was defined as SBP measured by EMS on arrival at the scene. ER-SBP was defined as SBP assessed before the initiation of HF therapy. The distribution of SBP in the AHF patients is shown in Figure 2.

Figure 2.

Distribution of on-site SBP and SBP measured in the emergency room (ER-SBP). SBP, systolic blood pressure.

Outcomes and Definitions of Variables

In the present study, the primary outcome was all-cause in-hospital death. All AHF patients were diagnosed using variables estimated on admission using the Framingham criteria.¹⁶ The estimated glomerular filtration rate (eGFR) was calculated using serum creatinine levels and the Modification of Diet in Renal Disease study equation.¹⁷ Anemia was defined as hemoglobin level <13 g/dl for men and <12 g/dl for women, according to the World Health Organization criteria.¹⁸ When N-terminal pro-B-type natriuretic peptide (NT-proBNP) was measured instead of BNP, the NT-proBNP value was converted to the BNP values using an equation established in a previous study.¹⁹

Statistical Analysis

Results are expressed as mean±standard deviation or median with interquartile range (IQR) for continuous variables and as percentages for categorical variables, as appropriate. Statistical comparisons were performed using analysis of variance or Kruskal-Wallis tests for continuous variables and the Pearson’s chi-squared test for categorical variables. Missing data were rare (<5%) for all variables, except for left ventricular ejection fraction (LVEF) (10.0%) and BNP levels (23.8%). Missing values were imputed as follows: (1) for variables pertaining to comorbidity and medical treatment during hospitalization, missing data were imputed to “no”; (2) for body mass index, missing values were imputed to the sex-specific median; (3) for LVEF, missing values were imputed to the median value of the entire cohort; and (4) for serum creatinine, missing values were imputed to the sex- and prior renal failure-specific medians.

We subdivided the patients by 20-mmHg strata of ER-SBP, and the distribution of in-hospital mortality rates was evaluated to determine whether the relationship was linear (Figure 3A). A similar presentation was prepared for the on-site SBP values (Figure 3B). Based on the patients’ mortality risk in the SBP groups, we categorized the patients into 9 groups by on-site SBP and ER-SBP: (1) low risk (mortality rate <5%), SBP >160 mmHg; (2) intermediate risk (mortality rate 5–15%), SBP 100–160 mmHg; and (3) high risk (mortality rate >15%), SBP <100 mmHg. We then evaluated the unadjusted and adjusted relationships between SBP and in-hospital deaths using logistic regression models. The multivariate model was adjusted for age, sex, prior admissions for HF, chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CVD), atrial fibrillation (AF), anemia, eGFR, and LVEF using a logistic regression model with a backward step-down variable deletion, removing terms with P>0.2. All probability values were 2-tailed, and P<0.05 was considered to be statistically significant. All statistical analyses were performed with SPSS version 19.0 (SPSS Inc, Chicago, IL, USA).

Figure 3.

In-hospital mortality rates according to SBP in the emergency room (ER-SBP) (A) and on-site SBP (B). SBP, systolic blood pressure.

Results

Patients’ Characteristics

The baseline characteristics of the study patients based on ER-SBP are summarized in Table 1. The patients were predominantly male (56.7%), with an average age of 75.9±12.3 years. Patients with both higher on-site SBP and ER-SBP had higher heart rates and worse respiratory conditions, as suggested by respiratory rates and oxygen saturation. Among the patients with ER-SBP <100 mmHg, prior admissions for HF, CVD, and AF were more frequent than in patients with ER-SBP >160 mmHg (all P<0.001). Laboratory findings revealed lower hemoglobin levels, poorer renal function, and higher C-reactive protein and BNP levels in patients with ER-SBP <100 mmHg than in those with ER-SBP >160 mmHg or 100–160 mmHg. With regard to LVEF, it was likely to be lower in patients with ER-SBP <100 mmHg.

Table 1. AHF Patients’ Characteristics Based on SBP in the ER (ER-SBP)

Variable	All patients (n=5,669)	SBP >160 mmHg (n=2,142)	SBP 100–160 mmHg (n=3,090)	SBP <100 mmHg (n=437)	P value
Age, year	75.9±12.3	75.3±12.1	76.3±12.9	73.3±13.4	<0.001
Male, %	56.7	58.5	55.7	55.9	0.133
BMI, kg/m2	22.3±4.3	22.9±4.4	22.0±4.3	21.1±3.7	<0.001
Time from EMS call to ER arrival, min#	35 (26–47)	34 (27–46)	35 (26–46)	37 (27–50)	<0.001
EMS call to scene, min#	8 (6–10)	8 (6–10)	8 (6–10)	8 (6–10)	0.207
Scene time, min#	17 (13–23)	17 (14–23)	17 (13–22)	18 (14–24)	0.182
Transportation time, min#	10 (7–14)	9 (7–13)	10 (7–14)	11 (7–16)	<0.001
Vital signs on-site
SBP, mmHg	149±38	178±33	136±28	103±30	<0.001
DBP, mmHg	85±34	99±43	79±23	62±19	<0.001
Pulse pressure, mmHg	65±36	79±45	58±25	43±19	<0.001
HR, beats/min	102±34	108±26	100±39	95±30	<0.001
Respiratory rate, /min	25±8	27±7	24±8	23±6	<0.001
Oxygen saturation (SpO2), %	91 (82–96)	88 (79–94)	92 (85–96)	94 (86–97)	<0.001
Vital signs at the ER
SBP, mmHg	151±39	191±25	133±17	86±12	<0.001
DBP, mmHg	86±25	105±24	78±17	54±12	<0.001
Pulse pressure, mmHg	65±27	87±25	55±18	33±12	<0.001
Heart rate, beats/min	102±28	109±28	98±27	94±29	<0.001
Respiratory rate, /min	25±8	28±8	24±8	23±8	<0.001
Oxygen saturation (SpO2), %	96 (91–98)	95 (90–98)	96 (93–99)	97 (93–99)	<0.001
Comorbidities, %
Ischemic etiology	30.1	28.5	31.4	28.0	0.055
Prior admissions for HF	31.9	26.4	33.0	47.7	<0.001
Hypertension	61.9	72.5	58.2	42.1	<0.001
Diabetes	32.4	34.4	31.7	29.4	0.048
Dyslipidemia	23.3	24.9	23.1	18.5	0.012
CVD	10.4	9.0	10.7	13.8	0.007
COPD	6.2	5.3	6.7	6.7	0.131
AF	31.6	24.8	34.4	40.2	<0.001
Laboratory findings
Hemoglobin, g/dl	11.9±3.1	12.2±3.9	11.7±2.5	11.3±2.6	<0.001
Serum creatinine, g/dl	1.10 (0.80–1.70)	1.10 (0.81–1.70)	1.10 (0.81–1.61)	1.33 (0.96–2.10)	<0.001
C-reactive protein, g/dl	0.70 (0.20–2.40)	0.50 (0.19–1.58)	0.83 (0.30–3.00)	1.30 (0.30–4.30)	<0.001
BNP, pg/ml†	768 (386–1,447)	745 (375–1,364)	768 (387–1,477)	899 (440–1,623)	<0.001
LVEF, %	43±16	45±15	42±17	37±18	<0.001
Treatment for HF in-hospital admission
NIPPV, %	24.1	30.3	20.8	16.8	<0.001
Tracheal intubation, %	10.6	9.7	9.8	21.0	<0.001
Dialysis, %	6.4	7.1	5.2	10.8	<0.001
IABP, %	2.3	1.5	2.3	6.6	<0.001
PCPS, %	0.9	0.7	0.7	2.4	0.002
Dobutamine IV, %	13.9	6.7	15.6	38.0	<0.001
Dopamine IV, %	10.7	6.2	11.3	28.2	<0.001
Noradrenalin IV, %	7.0	5.1	6.3	21.1	<0.001
Digoxin IV, %	11.0	7.8	12.8	14.2	<0.001
Furosemide IV, %	86.9	85.8	88.6	80.4	<0.001
Carperitide IV, %	48.6	52.4	48.4	31.1	<0.001
ACEI and/or ARB PO, %	53.5	62.1	50.0	35.3	<0.001
β-blocker PO, %	42.3	45.0	40.9	38.2	0.004
Aldosterone antagonist PO, %	34.3	33.4	35.2	32.1	0.253
Warfarin PO, %	33.6	26.3	37.1	43.5	<0.001
Hospitalization, days	15 (8–25)	14 (8–22)	15 (8–26)	17 (7–30)	<0.001

Data are reported as % for binary variables and as mean±standard deviation or median (quartile 1 to quartile 3) for continuous variables. ^#EMS time data were missing for 1,845 patients (32.5%). ^†Data for 4,321 patients (76.2%) were available. ACEI, angiotensin-converting enzyme inhibitor; AF, atrial fibrillation; AHF, acute heart failure; ARB, angiotensin receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; COPD, chronic obstructive pulmonary disease; CVD, cerebrovascular disease; DBP, diastolic blood pressure; EMS, emergency medical service; ER, emergency room; HF, heart failure; HR, heart rate; IABP, intra-aortic balloon pumping; IV, intravenous; LVEF, left ventricular ejection fraction; NIPPV, non-invasive positive airway pressure ventilation; PO, per os; PCPS, percutaneous cardiopulmonary support; SBP, systolic blood pressure.

Among patients with ER-SBP >160 mmHg, NIPPV was used more frequently, whereas tracheal intubation was performed more frequently in those with ER-SBP <100 mmHg. In addition, the use of assisted circulation devices, such as intra-aortic balloon pumping and percutaneous cardiopulmonary support, and inotropes occurred frequently in patients with ER-SBP <100 mmHg. No differences were observed in the prescription rate of aldosterone antagonist, but there were significant differences in prescription rates for angiotensin-converting enzyme inhibitors (ACEI) and/or angiotensin receptor blockers (ARB) and β-blockers (BB); either ACEI/ARB or BB were more frequently prescribed in patients with ER-SBP >160 mmHg (P<0.001 and 0.004, respectively).

SBP and In-Hospital Deaths

Overall, 432 (7.7%) patients died during hospitalization (64 [3.0%] in the ER-SBP >160 mmHg group; 274 [8.9%] in the ER-SBP 100–160 mmHg group; and 94 [21.5%] in the ER-SBP <100 mmHg group), with a lower ER-SBP being significantly associated with increased in-hospital mortality rates in the univariate logistic regression analysis (odds ratio [OR] for each 10-mmHg increment, 0.83; 95% confidence interval [CI], 0.80–0.85; P<0.001). Similarly, on-site SBP was also significantly associated with in-hospital mortality (OR for each 10-mmHg increment, 0.81; 95% CI, 0.78–0.83; P<0.001).

We then evaluated the prognostic value of on-site SBP within the 3 subgroups stratified by ER-SBP (<100, 100–160, and >160 mmHg). Among the patients with intermediate ER-SBP (100–160 mmHg), on-site SBP was significantly and linearly associated with in-hospital death (OR for each 10-mmHg increment, 0.83; 95% CI, 0.79–0.88; P<0.001). On-site SBP also showed a similar association in patients with high ER-SBP (>160 mmHg), but the relationship was not linear, but spline. There was no association between on-site SBP and in-hospital death in the low ER-SBP (<100 mmHg) subgroup.

We further stratified the patients into 9 groups based on the combination of on-site SBP with ER-SBP and evaluated the in-hospital mortality rates (Figure 4). After multivariate adjustment for age, sex, and other significant variables (Table 2), on-site SBP remained associated with in-hospital death, particularly in patients with ER-SBP between 100 and 160 mmHg (Figure 5).

Figure 4.

Relationship between on-site SBP and SBP in the emergency room (ER-SBP) and in-hospital death. SBP, systolic blood pressure.

Table 2. Covariates Other Than SBP in a Logistic Regression Analysis for In-Hospital Death of AHF Patients

	Univariate analysis		Multivariate analysis
	OR (95% CI)	P value	OR (95% CI)	P value
Age (1-year increments)	1.04 (1.03–1.05)	<0.001	1.04 (1.02–1.05)	<0.001
Female	1.20 (0.99–1.46)	0.069
Prior admissions for HF	1.61 (1.32–1.97)	<0.001	1.25 (0.97–1.60)	0.084
CVD	1.50 (1.12–2.00)	0.006	1.36 (0.95–1.93)	0.093
COPD	2.15 (1.55–2.98)	<0.001	2.01 (1.35–2.99)	0.001
AF	1.20 (0.98–1.48)	0.083
Anemia	1.96 (1.57–2.46)	<0.001	1.33 (0.99–1.77)	0.054
eGFR (1 ml/min/1.73 m2 decrements)	0.98 (0.98–0.99)	<0.001	0.99 (0.98–1.00)	0.030
LVEF	0.99 (0.99–1.00)	0.070

CI, confidence interval; eGFR, estimated glomerular filtration rate; OR, odds ratio. Other abbreviations as in Table 1.

Figure 5.

Forrest plots. Among patients with ER-SBP ranging from 100 to 160 mmHg, the on-site SBP was independently associated with in-hospital death, even after adjustment for age, prior admissions for heart failure, cerebrovascular disease, chronic obstructive pulmonary disease, anemia, estimated glomerular filtration rate, and left ventricular ejection fraction. CI, confidence interval; SBP, systolic blood pressure.

Among the patients with ER-SBP between 100 and 160 mmHg, a higher proportion of prior admissions for HF, lower hemoglobin levels, higher BNP levels, and worse renal function was noted for patients with on-site SBP <100 mmHg (Table S2). We also constructed an additional model including BNP level as a covariate, for there was a significant difference in its value among the 3 ER-SBP subgroups. Although there were a modest number of patients without BNP measurement data at the time of admission (23.8%), on-site SBP remained a significant predictor of in-hospital death within the intermediate ER-SBP subgroup (Table S3).

Discussion

In the present AHF dataset, constructed in collaboration with EMS and CCU services in metropolitan Tokyo, both the on-site SBP and the ER-SBP were powerful prognostic indicators for patients with AHF. Measuring the change in SBP while patients were in the acute setting enabled us to precisely discriminate those at high or low risk. Specifically, among patients with ER-SBP between 100 and 160 mmHg, on-site SBP added an additional value for predicting in-hospital death, even after adjustment for known predictors. To our knowledge, this is the first study to investigate the relationship of the change in on-site SBP (assessed on-site by the EMS) and ER-SBP and its association with in-hospital death of patients with AHF.

SBP is a well-known powerful prognostic indicator in patients with HF, to the same extent in both the acute and chronic phases.^3–8 SBP is included in several risk stratification models for HF recommended in the ACCF/AHA guideline for the management of heart failure:⁹ the Acute Decompensated Heart Failure National Registry (ADHERE) risk tree,³ the Get-With-The-Guideline Heart-Failure (GWTG-HF) Model,⁶ and the Seattle Heart Failure Model (SHFM).⁷ Ambrosy et al previously demonstrated, from the Efficacy of Vasopressin Antagonism in Heart Failure (EVEREST) trial, that both the SBP after initial HF therapy during hospitalization and the SBP at discharge were independent clinical predictors of morbidity and mortality in patients hospitalized for AHF.¹¹ To date, the clinical significance of the change in SBP during acute management of AHF has been understudied.

Unlike the previous study,¹¹ our study focused less on the absolute change in SBP, as a result of the response to treatment, by nature of the study’s design. In the present study, pre-hospital intervention for AHF patients was oxygenation only; neither drugs nor NIPPV was used. Therefore, our results indicate that the monitoring of changes in SBP itself is important for AHF patients as part of the natural course, rather than during medical intervention in the pre-hospital phase or during hospitalization. The change in SBP from pre-hospital to ER triage can provide new insights into the natural history of early AHF, and acute cardiopulmonary edema. Although the results of the present study demonstrated that the time interval between the EMS call and ER arrival was relatively short (median, 35 min) and subsequently that advanced treatment in the ER begins early in the metropolitan Tokyo area, the on-site SBP is more important in rural regions, where it takes much longer to transfer patients to hospital.

As our results described, several important differences were observed among patients with ER-SBP between 100 and 160 mmHg. These factors are known to be associated with prognosis in patients with HF: prior admissions for HF;²⁰ anemia;^7,21,22 and BNP level.^23–26 In particular, renal impairment is a powerful prognostic factor in patients with AHF.³ In addition, Mitsnefes et al have reported that patients with chronic renal impairment, particularly those on dialysis, have significantly low contractile reserve.²⁷ In the present analysis, our results indicated that a change in SBP during patient stay in the acute setting was not associated with renal function or other factors, although a change in SBP itself does not reflect cardiac contractile reserve; therefore, SBP change should be considered a useful clinical predictor in patients with AHF.

EMS systems are different in each country or can also vary within regions of the same country, with respect to the expertise of paramedics, availability of diagnostic and therapeutic equipment, and ability to administer drugs. In Japan, paramedics have several limitations, including the inability to use NIPPV and to administer drugs, except for adrenalin in the case of cardiopulmonary arrest.^14,15 As our results demonstrated that on-site SBP was associated with the in-hospital death of AHF patients, early treatment initiation, such as fluid infusion, should be considered to improve prognosis, especially among high-risk patients presenting with hypotension and hypoperfusion. Patients in a critical condition may even benefit from administration of pre-hospital drugs during EMS transfer.²⁸ Hemodynamic improvement has been an important target in contemporary AHF therapy, although little evidence exists in this area. Paramedics with sufficient training for HF care and with the ability to provide appropriate management under physicians’ control may be needed to accurately assess the benefit of these interventions.

Study Limitations

The present study using the TCN database was limited by several factors. First, the data were obtained from an observational study, and unmeasured factors may have influenced the clinical outcomes. We had no information regarding ER management. Furthermore, there were substantial numbers of patients who did not have their BNP level measured at the time of hospital admission. It is possible that patients with typical AHF symptoms frequently do not have BNP measured, and this may lead to bias on the predictive value of SBP. Second, this registry is geographically limited to the metropolitan Tokyo area, where there is a dense network of hospitals and EMS.

Conclusions

In our study, both on-site SBP and ER-SBP were independent predictors in patients with AHF; in particular, among patients with ER-SBP between 100 and 160 mmHg, on-site SBP provided an additional value for identifying high-risk patients. Monitoring alterations in SBP aided the stratification of AHF patients by risk.

Acknowledgments

We thank Ms Nobuko Yoshida, and other staff of the Tokyo CCU Network Scientific Committee for their important contributions.

Conflict of Interest

The authors have stated that no such relationships exist and provide the following details: S.K. received lecture fees from Pfizer Japan Inc, and an unrestricted research grant for the Department of Cardiology, Keio University School of Medicine from Bayer Pharmaceutical Co, Ltd. Other authors have no conflicts of interest to disclose. There are no patents, products in development or marketed products to declare.

Funding

This research received no grants from any funding agency in the public, commercial or not-for-profit sectors.

Appendix 1

Participating Hospitals and the Leading Members of the Tokyo CCU Network Scientific Committee

Mitsui Memorial Hospital, Kazuhiro Hara; Nihon University Itabashi Hospital, Tadateru Takayama; Juntendo University Hospital, Hiroyuki Daida; Toho University Ohashi Medical Center, Masato Nakamura; Saiseikai Central Hospital, Shin Nakagawa; Showa University Hospital, Youichi Kobayashi; Sakakibara Heart Institute, Tetsuya Sumiyoshi; Kosei General Hospital, Masao Kawaguchi; St.Luke’s International Hospital, Yutaro Nishi; Tokyo Women’s Medical University Hospital, Nobuhisa Hagiwara; Nishiarai Heart Center Hospital, Katsumi Saito; Teikyo University Hospital, Takaaki Isshiki; The Cardiovascular Institute, Akira Koike; Toranomon Hospital, Haruo Mitani; Toho University Omori Medical Center, Nobuya Koyama; Surugadai Nihon University Hospital, Ken Nagao; Tokyo Medical University Hachioji Medical Center, Hiroshi Kobayashi; Kyorin University Hospital, Hideaki Yoshino; Tokyo Metropolitan Geriatric Hospital, Kazumasa Harada; Tokyo Metropolitan Hiroo Hospital, Harumizu Sakurada; Nippon Medical School Hospital, Keiji Tanaka; Tokyo Women’s Medical University Medical Center East, Kuniaki Otsuka; Bokutoh Metropolitan General Hospital, Toru Iwama; Tobu Chiiki Hospital, Takashi Tamura; Musashino Red Cross Hospital, Tohru Obayashi; Showa General Hospital, Yuji Kira; Tokyo Metropolitan Tama Medical Center, Tetsuro Ueda; Disaster Medical Center, Yasuhiro Satoh; Ome Municipal General Hospital, Shigeo Shimizu; Edogawa Hospital, Yoji Oohira; Tokyo Rinkai Hospital, Toru Kohno; Jikei University Katsushika Medical Center, Shingo Seki; IMS Katsushika Heart Center, Shigehiko Yoshida; Ayase Heart Hospital, Imun Tei; Hakujikai Memorial Hospital, Kunio Tanaka; The Jikei University Hospital, Michihiro Yoshimura; Senpo Tokyo Takanawa Hospital, Masato Yamamoto; NTT Medical Center Tokyo, Masao Yamazaki; Ikegami General Hospital, Takao Machimura; The University of Tokyo Hospital, Issei Komuro; Tokyo Metropolitan Police Hospital, Tetsuro Shirai; Kohseichuo General Hospital, Akio Hirai; Mishuku Hospital, Akimi Uehata; Keio University Hospital, Keiichi Fukuda; Tokyo Medical University Hospital, Akira Yamashina; National Center for Global Health and Medicine, Hisao Hara; Kawakita General Hospital, Yoichi Sugimura; Itabashi Chuo Medical Center, Hiroshi Ota; Toshima Hospital, Takashi Shibui; Nishitokyo Central General Hospital, Hiroyuki Suesada; Higashiyamato Hospital, Masao Kuwada; Tokai University Hachioji-hospital, Yoshinori Kobayashi; Nippon Medical School Tama-Nagayama Hospital, Hirotsugu Atarashi; Tama Nambu Chiiki Hospital, Tatenori Suzuki; Tokyo Medical and Dental University, Mitsuaki Isobe; Japanese Red Cross Medical Center, Hiroshi Ikenouchi; Kanto Central Hospital, Akira Nozaki; National Hospital Organization Tokyo Medical Center, Yukihiko Momiyama; Social Insurance Central General Hospital, Makoto Noda; Tokyo Kosei Nenkin Hospital, Seiji Ayabe; Nihon University Nerima Hikarigaoka hospital, Seiji Fukushima; Jikei University Daisan Hospital, Takahiro Shibata; Tokyo-kita Social Insurance Hospital, Yoshio Tsuruya; Kasai Cardiology & Neurosurgery Hospital, Akihiro Hata; Tokyo Heart Center, Joji Hosokawa; Ogikubo Hospital, Yasuhiro Ishii; Tama-Hokubu Medical Center, Satoshi Murasaki (lead author, Morimasa Takayama [[e-mail]]).

Appendix 2

Affiliations of Each Author Member of the Tokyo CCU Network Scientific Committee

• Kazumasa Harada, Tokyo Metropolitan Geriatric Hospital, Tokyo, Japan

• Takamichi Miyamoto, Musashino Red Cross Hospital, Tokyo, Japan

• Shuzou Tanimoto, Mitsui Memorial Hospital, Tokyo, Japan

• Kiyoshi Iida, Nihon University Surugadai Hospital, Tokyo, Japan

• Tetsuro Sakai, Showa University school of Medicine, Tokyo, Japan

• Tetsuro Miyazaki, Juntendo University Graduate School of Medicine, Tokyo, Japan

• Mayuko Yagawa, Sakakibara Heart Institute, Tokyo, Japan

• Kenichi Matsushita, Kyorin University School of Medicine, Tokyo, Japan

• Shuta Furihata, Omori Red Cross Hospital, Tokyo, Japan

• Naoki Sato, Nippon Medical School Musashi-Kosugi Hospital, Kanagawa, Japan

• Keiichi Fukuda, Keio University School of Medicine, Tokyo, Japan

• Takeshi Yamamoto, Nippon Medical School Hospital, Tokyo, Japan

• Ken Nagao, Nihon University Surugadai Hospital, Tokyo, Japan

• Morimasa Takayama, Sakakibara Heart Institute, Tokyo, Japan

Supplementary Files

Supplementary File 1

Table S1. Characteristics of included and excluded patients in a study of AHF

Table S2. Characteristics of the AHF patients with ER-SBP ranging from 100 to 160 mmHg according to on-site SBP

Table S3. Covariates of logistic regression model including BNP in a study of AHF

Please find supplementary file(s);

http://dx.doi.org/10.1253/circj.CJ-16-0837

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