Relationships Among Heart Rate, β-Blocker Dosage, and Prognosis in Patients With Coronary Artery Disease in a Real-World Database Using a Multimodal Data Acquisition System

Yusuke Oba; Tomoyuki Kabutoya; Takahide Kohro; Yasushi Imai; Kazuomi Kario; Hisahiko Sato; Kotaro Nochioka; Masaharu Nakayama; Hideo Fujita; Yoshiko Mizuno; Arihiro Kiyosue; Takamasa Iwai; Yoshihiro Miyamoto; Yasuhiro Nakano; Taishi Nakamura; Kenichi Tsujita; Tetsuya Matoba; Ryozo Nagai

doi:10.1253/circj.CJ-22-0314

Abstract

Background: The optimal heart rate (HR) and optimal dose of β-blockers (BBs) in patients with coronary artery disease (CAD) have been unclear. We sought to clarify the relationships among HR, BB dose, and prognosis in patients with CAD using a multimodal data acquisition system.

Methods and Results: We evaluated the data for 8,744 CAD patients who underwent cardiac catheterization from 6 university hospitals and the National Cerebral and Cardiovascular Center and who were registered using the Clinical Deep Data Accumulation System. Patients were divided into quartile groups based on their HR at discharge: Q1 (HR <60 beats/min), Q2 (HR 60–66 beats/min), Q3 (HR 67–74 beats/min), and Q4 (HR ≥75 beats/min). Among patients with acute coronary syndrome (ACS) and patients with chronic coronary syndrome (CCS), those in Q4 (HR ≥75 beats/min) had a significantly greater incidence of major adverse cardiac and cerebral events (MACCE) compared with those in Q1 (ACS patients: hazard ratio 1.65, P=0.001; CCS patients: hazard ratio 1.45, P=0.019). Regarding the use of BBs (n=4,964), low-dose administration was significantly associated with MACCE in the ACS group (hazard ratio 1.41, P=0.012), but not in patients with CCS after adjustment for covariates.

Conclusions: HR ≥75 beats/min was associated with worse outcomes in patients with CCS or ACS.

Increased heart rate (HR) is associated with cardiovascular events (CVE) not only in the general population and individuals with cardiovascular risk factors,¹^–⁶ but also in patients with coronary artery disease (CAD).⁷^,⁸

Editorial p 345

In patients with heart failure (HF), it is well established that low HR is associated with significantly lower rates of CVE.⁹ Current evidence strongly supports the use of β-blockers (BBs) in HF patients with reduced left ventricular ejection fraction (HFrEF). Although it is known that higher doses of BBs are associated with significantly lower rates of CVE,⁹^–¹¹ a low dose of β-blocker is also effective if the HR has been reduced.¹²^–¹⁵

Prior to the reperfusion era, most studies showed that BBs reduced CVE in patients with myocardial infarction (MI).¹⁶^,¹⁷ However, in the current reperfusion era, BBs have been associated with a lower mortality rate following MI only in patients with left ventricular systolic dysfunction.¹⁸^–²⁰ In patients with chronic coronary syndrome (CCS), there is also no evidence for BBs reducing CVE, although BBs are effective for managing angina symptoms. The optimal HR and optimal dose of BBs in patients with CAD who have undergone percutaneous coronary intervention (PCI) have not been established.

In the present study, therefore, we sought to clarify the relationships between HR and prognosis and between BB dosage and prognosis in patients with CAD using data accumulated at multiple facilities by a multimodal data acquisition system.

Methods

The Clinical Deep Data Accumulation System (CLIDAS) has been described in a previous report,²¹ and we used it in this study to collect data from 7 facilities. The CLIDAS uses 2 types of storage. The Standardized Structured Medical Information eXchange (SS-MIX2) standard storage collects basic patient information, prescriptions, and laboratory data from electronic medical records, whereas the SS-MIX2 extended storage collects the results of physiological tests, cardiac catheterization, and cardiac catheter intervention reports, which are often in non-standardized formats (Figure 1).²²

Figure 1.

Conceptual diagram of CLIDAS (The Clinical Deep Data Accumulation System). PCI, percutaneous coronary intervention.

The SS-MIX was developed in 2006 by the Ministry of Health, Labour, and Welfare (MHLW) of the Japanese government, in conjunction with their electronic medical examinations information exchange project. The MHLW project aimed to establish an environment in which medical information is exchanged in a standardized manner among patients, medical institutions, and other related facilities.²³ The SS-MIX2 extended storage accumulates virtually any additional electronic data related to medical activities and procedures in the form of text, audio, images, vector graphics, movies, and medical waveforms, including structured records of cardiac catheterization, cardiac catheter intervention, ECG, and ultrasound cardiography (UCG).

We enrolled 9,936 patients who underwent cardiac catheterization at 6 university hospitals and the National Cerebral and Cardiovascular Center in Japan and who were registered between April 2013 and March 2019 using the CLIDAS database (Supplementary Figure 1). Our baseline CLIDAS data set comprised 9,690 cases after excluding patients with missing background information or data on cardiovascular events. In Study 1, we excluded patients without data on HR at discharge, and in Study 2 we excluded those without data on carvedilol and bisoprolol intake and dose (Supplementary Figure 1). The Internal Review Board of the Jichi Medical University School of Medicine approved this study, which was performed in accordance with the Declaration of Helsinki, and informed consent was given by all subjects.

Study 1

We evaluated the relationship between HR at discharge following cardiac catheterization and prognosis in 8,744 patients divided into quartiles based on their HR at discharge: Q1 (HR <60 beats/min, n=1,932), Q2 (HR 60–66 beats/min, n=2,276), Q3 (HR 67–74 beats/min, n=2,370), and Q4 (HR ≥75 beats/min, n=2,166). The number of patients with acute coronary syndrome (ACS) was 3,756, and 4,988 had CCS. The patients with ACS included those with ST-segment-elevation MI (STEMI), non ACS included those with ST according to the JCS guideline.²⁴ The CCS group was defined as patients who had undergone PCI for significantly stenosed coronary lesions not caused by ACS.

Study 2

All patients in study 2 were taking carvedilol or bisoprolol at discharge. A standard dose of BB was defined as >10 mg/day of carvedilol or 2.5 mg/day of bisoprolol.⁹ We divided these patients into 2 groups according to their dose of BB: low-dose group (<10 mg/day of carvedilol or 2.5 mg/day of bisoprolol; n=2,676) and standard dose group (≥10 mg/day of carvedilol or 2.5 mg/day of bisoprolol n=2,288). We also divided the patients into 2 groups according to the duration of their coronary artery syndrome: an ACS group (n=2,654) and a CCS group (n=2,310). Finally, we categorized patients into 4 groups based on their BB use and HR (group 1: standard dose of BB and HR <75 beats/min (n=1,858); group 2: low dose of BB and HR <75 beats/min (n=2,019); group 3: standard dose of BB and HR ≥75 beats/min (n=430); and group 4: low dose of BB and HR ≥75 beats/min (n=657). We then analyzed the relationships between these groups and prognosis.

Outcomes

A major adverse cardiac and cerebral event (MACCE) was defined as the first occurrence of any of the following: cardiovascular death (MI, sudden cardiac death, stroke, cardiovascular hemorrhage, heart failure), nonfatal stroke, or nonfatal MI. The data managers at each facility obtained information on these events from the medical records. We defined non-fatal MI as surviving ACS with persistent ST-elevation or the absence of persistent ST-elevation but elevated cardiac markers.²⁴ Nonfatal stroke was defined as surviving a stroke (cerebral infarction, cerebral hemorrhage, or subarachnoid hemorrhage).

Statistical Analysis

Data are shown as the mean (±standard deviation [SD]) or percentage. We compared clinical characteristics across the 4 groups of interest using analysis of variance (ANOVA) for continuous variables. Multivariate Cox proportional hazards regression modelling was used to determine the hazard ratio for future MACCE after adjusting for age, male sex, hypertension (HT), diabetes mellitus (DM), dyslipidemia, prior MI, prior congestive heart failure, and prior stroke as traditional risk factors. The incidence of MACCE in the groups classified by HR or the dose of BB and HR was plotted as Kaplan-Meier curves, and the differences were assessed by log rank test. Associations/differences with a P value <0.05 (two-tailed) were considered significant. All statistical analyses were performed with IBM SPSS Statistics version 22 software (Chicago, IL, USA).

Results

The median follow-up was 2.5 years (interquartile range: 0.8–4.1 years). During follow-up, there were 701 MACCEs, 245 cardiovascular deaths, 215 nonfatal MIs, and 254 strokes.

Study 1

Table 1 shows the baseline characteristics and comparisons of the 4 groups according to HR. Group Q4 (HR ≥75 beats/min) had younger patients, a greater percentage of females, and higher incidence of DM as compared with the other groups (all P<0.001).

Table 1. Baseline Characteristics of Groups According to Quartile of HR: Study 1

	Q1 (HR <60, n=1,932)	Q2 (HR 60–66, n=2,276)	Q3 (HR 67–74, n=2,370)	Q4 (HR ≥75, n=2,166)	ANOVA P value	Q1–Q3 (HR <75, n=6,578)	Q4 (HR ≥75, n=2,166)	P value
Age (years)	71.0±10.1	70.4±10.9	69.9±11.0	69.2±12.0	<0.001	70.4±10.7	69.2±12.0	<0.001
Male (%)	81	79	77	75	<0.001	79	75	<0.001
Hypertension (%)	84	84	82	81	0.004	84	81	0.002
Diabetes (%)	37	41	45	47	<0.001	41	47	<0.001
Dyslipidemia (%)	81	81	80	77	<0.001	81	77	<0.001
Smoking (%)	43	42	39	39	0.147	41	39	0.177
ACS (%)	43	44	40	44	0.020	43	44	0.183
SBP (mmHg)	120.0±16.3	119.4±15.7	119.3±16.0	118.2±17.3	0.004	119.6±16.0	118.2±17.3	0.001
DBP (mmHg)	63.4±10.1	65.1±9.6	66.2±9.9	67.2±10.7	<0.001	65.0±9.9	67.2±10.7	<0.001
HR (beats/min)	54.7±4.0	63.2±2.1	70.5±2.3	82.7±7.7	<0.001	63.3±6.9	82.7±7.7	<0.001
Prior PCI (%)	23	22	21	18	<0.001	22	18	<0.001
Prior CABG (%)	5	5	6	5	0.687	6	5	0.544
Prior MI (%)	16	17	16	14	0.040	16	14	0.009
Prior CHF (%)	4	7	6	9	<0.001	6	9	<0.001
Prior stroke (%)	10	10	11	12	0.243	10	12	0.080
CKD (%)	48	46	47	50	0.074	47	50	0.012
LMT or MVD (%)	56	57	54	54	0.281	55	54	0.294
Diuretics (%)	21	23	24	28	<0.001	23	28	<0.001
RAAS inhibitors (%)	69	69	64	62	<0.001	67	62	<0.001
Statins (%)	85	84	79	77	<0.001	82	77	<0.001
β-blockers (%)	69	66	58	53	<0.001	64	53	<0.001
LVEF (%)	59.2±12.3	57.8±13.6	57.5±13.9	54.7±14.8	<0.001	58.1±13.4	54.7±14.8	<0.001

Data are expressed as mean±SD or percentage. ANOVA, analysis of variance; ACS, acute coronary syndrome; CABG, coronary artery bypass grafting; CHF, congestive heart failure; CKD, chronic kidney disease; DBP, diastolic blood pressure; HR, heart rate; LMT, left main trunk; LVEF, left ventricular ejection fraction; MI, myocardial infarction; MVD, multivessel disease; PCI, percutaneous coronary intervention; RAAS, renin-angiotensin-aldosterone system; SBP, systolic blood pressure.

Figure 2 shows the Kaplan-Meier curves for MACCE among the 4 HR quartiles. Group Q4 (HR ≥75 beats/min) had the highest incidence of MACCE after PCI among the quartiles (log rank: 27.5; P<0.001) (Figure 2A). Q4 also had a significantly higher incidence of MACCE than the combined Q1–Q3 groups (HR <75) beats/min (log rank: 27.1; P<0.001) (Figure 2B). When we divided the patients into an ACS or CCS group, Q4 patients had significantly higher incidence of MACCE than Q1–Q3 patients in both the ACS (log rank: 22.1; P<0.001) (Figure 2C) and CCS (log rank: 7.0; P<0.008) groups (Figure 2D). After adjustment for age, male sex, HT, DM, dyslipidemia, prior MI, prior congestive HF, and prior stroke, Q4 patients had a significantly higher incidence of MACCE compared with Q1 patients in both the ACS and CCS groups (overall: hazard ratio 1.56, 95% confidence interval [CI] 1.25–1.93, P<0.001; ACS group: hazard ratio 1.65, 95% CI 1.22–2.24, P=0.001; CCS group: hazard ratio 1.45, 95% CI 1.06–1.98, P=0.019), but there was no association between MACCE incidence and either Q2 or Q3 (Table 2A). Q4 patients also had significantly more MACCE than patients in the combined Q1–Q3 groups (overall: hazard ratio 1.52, 95% CI 1.29–1.79, P<0.001; ACS group: hazard ratio 1.64, 95% CI 1.31–2.06, P<0.001; CCS group: hazard ratio 1.40, 95% CI 1.11–1.78, P=0.005, Table 2B).

Figure 2.

Kaplan-Meier curves for (A) MACCE among patients into quartiles according to HR at discharge, (B) MACCE between patients in combined Q1–Q3 groups and Q4, (C) MACCE between patients in combined Q1–Q3 groups and Q4 in ACS, and (D) MACCE between patients in combined Q1–Q3 groups and Q4 in CCS. ACS, acute coronary syndrome; CCS, chronic coronary syndrome; HR, heart rate; MACCE, major adverse cardiac and cerebral events.

Table 2. Cox Proportional Hazard Models for MACCE in Study 1

(A) MACCE among patients in quartiles according to HR (beats/min) at discharge
	Q1 (HR <60, REF)	Q2 (HR 60–66)		Q3 (HR 67–74)		Q4 (HR ≥75)
	Q1 (HR <60, REF)	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value
Overall	1	1.01 (0.80–1.27)	0.939	1.06 (0.85–1.33)	0.594	1.56 (1.25–1.93)	<0.001
ACS	1	0.92 (0.67–1.27)	0.618	1.11 (0.80–1.52)	0.536	1.65 (1.22–2.24)	0.001
CCS	1	1.06 (0.77–1.46)	0.713	1.03 (0.75–1.41)	0.853	1.45 (1.06–1.98)	0.019
(B) MACCE between patients in combined Q1–Q3 groups and Q4
	Q1–3 (HR <75, REF)	Q4 (HR ≥75)
	Q1–3 (HR <75, REF)	Hazard ratio (95% CI)	P value
Overall	1	1.52 (1.29–1.79)	<0.001
ACS	1	1.64 (1.31–2.06)	<0.001
CCS	1	1.40 (1.11–1.78)	0.005

Adjusted for age, male sex, hypertension, diabetes mellitus, dyslipidemia, prior myocardial infarction, prior congestive heart failure, prior stroke. CCS, chronic coronary syndrome; CI, confidence interval; MACCE, major adverse cardiac and cerebral events. Other abbreviations as in Table 1.

In accordance with a prior report,⁷ we conducted a Cox hazard model of patients with HR ≥70 beats/min or HR <70 beats/min. After adjustment for age, male sex, HT, DM, dyslipidemia, prior MI, prior congestive HF, and prior stroke, the HR ≥70 beats/min patients had a significantly higher incidence of MACCE than the HR <70 beats/min patients in the ACS group but not in the CCS group (overall: hazard ratio 1.32, 95% CI: 1.13–1.54, P<0.001; ACS group: hazard ratio 1.44, 95% CI: 1.17–1.79, P=0.001; CCS group: hazard ratio 1.22, 95% CI: 0.98–1.51, P=0.073).

There were 5,340 (61%) patients taking BBs, including BBs other than carvedilol and bisoprolol. After adjustment for covariates, there was no significant difference in the incidence of MACCE between the patients taking BBs and those not taking them in both the ACS and CCS groups (ACS: hazard ratio 1.02. 95% CI 0.81–1.29, P=0.848; CCS: hazard ratio 1.23, 95% CI: 0.98–1.53, P=0.070).

Study 2

The mean dose in the carvedilol group (n=1,955) was 7.5±6.4 mg, and that in the bisoprolol group (n=3,009) was 2.4±1.8 mg. The rate of doses above the standard dose was significantly higher in the bisoprolol group compared with the carvedilol group (52.5% vs. 36.3%, P<0.001), and the HR values were significantly lower in the bisoprolol group compared with the carvedilol group (66.5±10.6 vs. 68.3±10.7 beats/min, P<0.001). The incidence of MACCE was not significantly different between the carvedilol and bisoprolol groups.

Figure 3 shows the Kaplan-Meier curves for MACCE in the low-dose and standard-dose BB groups. The low-dose group had significantly higher incidence of MACCE than the standard-dose group (log rank: 5.7; P=0.017). When we divided patients into ACS and CCS groups, the low-dose BB group had significantly higher incidence of MACCE than the standard-dose BB group among patients with ACS (log rank: 7.3; P=0.007), whereas in the patients with CCS there was no association between BB dose and MACCE incidence (log rank: 0.02; P=0.887). Table 3 shows the baseline characteristics of the patients and their categorization according to BB dose and HR. Figure 4 shows the Kaplan-Meier curves for MACCE among the 4 groups according to the HR and dose of BB. Group 4 (low dose of BB, HR ≥75 beats/min) had the highest incidence of MACCE (log rank: 16.4; P=0.001) (Figure 4A). When we divided the patients into ACS and CCS groups, group 4 (low dose of BB, HR ≥75 beats/min) had the highest incidence among the 4 groups of patients with ACS (log rank 13.0, P=0.005) (Figure 4B), whereas there was no association between the BB dose/HR combination and outcomes in patients with CCS (log rank: 4.8; P=0.184) (Figure 4C). We performed Cox analyses among the 4 groups according to BB dose and HR. After adjustment for covariates, the patients in the group with low-dose BB and HR ≥75 beats/min showed a significantly higher incidence of MACCE than those with standard-dose BB and HR <75 beats/min in the ACS group but not the CCS group (overall: hazard ratio 1.72, 95% CI: 1.27–2.32, P<0.001; ACS group: hazard ratio 1.97, 95% CI: 1.33–2.92, P=0.001; CCS group: hazard ratio 1.35, 95% CI: 0.83–2.19, P=0.229).

Figure 3.

Kaplan-Meier curves for (A) MACCE between the low-dose and standard-dose β-blocker groups, (B) MACCE between the low-dose and standard-dose β-blocker groups in ACS, and (C) MACCE between the low-dose and standard-dose β-blocker groups in CCS. ACS, acute coronary syndrome; CCS, chronic coronary syndrome; LD-β, low dose of β-blocker; MACCE, major adverse cardiac and cerebral events; SD-β, standard dose of β-blocker.

Table 3. Baseline Characteristics of Groups According to β-Blocker Dosage and HR: Study 2

	Standard-dose β-blocker HR <75 beats/min (n=1,858)	Low-dose β-blocker HR <75 beats/min (n=2,019)	Standard-dose β-blocker HR ≥75 beats/min (n=430)	Low-dose β-blocker HR ≥75 beats/min (n=657)	P value	Standard-dose β-blocker (n=2,288)	Low-dose β-blocker (n=2,676)	P value
Age (years)	68.8±11.0	71.2±10.9	66.0±12.4	70.2±12.2	<0.001	68.3±11.3	70.1±11.3	<0.001
Male (%)	80	77	77	74	0.007	79	76	0.007
Hypertension (%)	87	85	85	84	0.495	86	85	0.220
Diabetes (%)	42	39	49	45	<0.001	43	40	0.072
Dyslipidemia (%)	85	82	81	78	0.004	84	81	0.022
Smoking (%)	42	43	39	43	0.735	41	43	0.479
ACS (%)	47	58	50	60	<0.001	48	58	<0.001
SBP (mmHg)	120.0±16.8	117.0±16.3	118.6±17.3	114.0±16.9	<0.001	119.4±16.9	116.3±16.5	<0.001
DBP (mmHg)	65.3±10.4	64.3±9.8	68.9±10.4	66.0±10.6	<0.001	66.0±10.5	64.7±10.0	<0.001
HR (beats/min)	62.7±6.8	63.1±6.9	82.4±7.5	82.5±7.1	<0.001	66.4±10.3	67.9±10.9	<0.001
Prior PCI (%)	21	17	16	15	0.001	20	17	0.003
Prior CABG (%)	8	4	7	5	<0.001	7	4	<0.001
Prior MI (%)	20	17	18	17	0.056	20	17	0.012
Prior CHF (%)	6	7	11	11	<0.001	7	8	0.459
Prior stroke (%)	10	12	14	12	0.057	11	12	0.206
CKD (%)	51	45	51	50	0.001	51	46	0.001
LMT or MVD (%)	59	56	57	55	0.223	59	56	0.057
Diuretics (%)	28	27	36	40	<0.001	29	30	0.357
RAAS inhibitors (%)	77	79	73	76	0.042	76	78	0.122
Statins (%)	89	94	85	91	<0.001	88	93	<0.001
LVEF (%)	56.8±13.4	55.3±13.8	52.7±14.5	50.2±14.9	<0.001	56.0±13.7	54.0±14.3	<0.001

Data are expressed as mean±SD or percentage. Abbreviations as in Table 1.

Figure 4.

Kaplan-Meier curves for (A) MACCE among the 4 groups according to HR and dose of β-blocker, (B) MACCE among the 4 groups according to HR and dose of β-blocker in ACS, and (C) MACCE among the 4 groups according to HR and dose of β-blocker in CCS. ACS, acute coronary syndrome; CCS, chronic coronary syndrome; HR, heart rate; LD-β, low dose of β-blocker; MACCE, major adverse cardiac and cerebral events; SD-β, standard dose of β-blocker.

After adjustment for age, male sex, HT, DM, dyslipidemia, prior MI, prior congestive HF, and prior stroke, HR ≥75 beats/min was significantly associated with the incidence of MACCE in both the ACS and CCS groups (overall: hazard ratio 1.46, 95% CI 1.17–1.83, P=0.001; ACS group: hazard ratio 1.41, 95% CI 1.05–1.89, P=0.021; CCS group: hazard ratio 1.51, 95% CI 1.05–2.16, P=0.024). Low-dose BB use was significantly associated with MACCE incidence in the ACS group (hazard ratio 1.41, 95% CI 1.08–1.85, P=0.012), but there was no association in patients with CCS (hazard ratio 0.89, 95% CI 0.66–1.22 P=0.894) (Table 4).

Table 4. Cox Proportional Hazard Model for MACCE in Study 2

	Heart rate ≥75 beats/min		Low-dose β-blocker
	Hazard ratio (95% CI)	P value	Hazard ratio (95% CI)	P value
Overall	1.46 (1.17–1.83)	0.001	1.20 (0.98–1.46)	0.075
ACS	1.41 (1.05–1.89)	0.021	1.41 (1.08–1.85)	0.012
CCS	1.51 (1.05–2.16)	0.024	0.89 (0.66–1.22)	0.894

Adjusted for age, male sex, hypertension, diabetes mellitus, dyslipidemia, prior MI, prior CHF, prior stroke. Abbreviations as in Tables 1,2.

We analyzed the association between each of the MACCEs examined (i.e., cardiovascular death, nonfatal MI, and stroke) and BB dose. After adjustment for the above-mentioned covariates, there was no significant difference in the incidence of cardiovascular death (ACS: hazard ratio 1.51, 95% CI: 0.87–2.61, P=0.141; CCS: hazard ratio 1.51, 95% CI: 0.91–2.50, P=0.110) and non-fatal stroke (ACS: hazard ratio 1.40, 95% CI: 0.90–2.18, P=0.138; CCS: hazard ratio 0.66, 95% CI: 0.39–1.10, P=0.171) between patients using a low-dose BB and those using a standard-dose BB in either the ACS group or CCS group. In addition, after adjustment for the same covariates, there was no significant difference in the incidence of non-fatal MI between patients using a low-dose BB and those using a standard-dose BB in either the ACS or CCS group (ACS: hazard ratio 1.32 95% CI: 0.88–1.96, P=0.181; CCS: hazard ratio 0.68, 95% CI: 0.35–1.32, P=0.257).

We conducted a subgroup analysis of MACCEs using the patients’ baseline characteristics, and it revealed no significant differences in MACCE, HR, or BB dose by patient background except for HT (Supplementary Figures 2,3).

Discussion

The main findings of this study were that HR ≥75 beats/min was independently associated with MACCE in patients with CAD, and that ACS patients treated with a low dose of BB had a significantly higher incidence of MACCE than ACS patients treated with a standard dose, but no association between BB dose and MACCE incidence in patients with CCS.

Diaz et al reported that CAD patients with HR >77 beats/min were significantly more likely to have CVE or to die from any cause compared with CAD patients with HR ≤62 beats/min.⁸ In a subgroup analysis of the BEAUTIFUL trial, HR ≥70 beats/min was associated with CVE in patients with CAD and left ventricular systolic dysfunction.⁷ In the present study, HR ≥75 beats/min was associated with MACCE, consistent with the findings of the other studies.⁷^,⁸ Our analyses also revealed that HR ≥70 beats/min was associated with MACCE in ACS patients, but not in CCS patients. There may be a difference in the association between HR and prognosis in both ACS and CCS if the HR threshold is changed. In addition, the question of whether a high HR is harmful in patients with HF is controversial,²⁵^,²⁶ and more research is necessary to determine the optimal HR in CAD patients.

The following mechanisms have been postulated to explain the event-suppressing effect of HR reduction. Reduced HR prolongs the diastolic time, which could improve left ventricular filling and increase stroke volume (SV), according to the Frank-Starling law.²⁷^–³⁰ HR reduction also increases coronary perfusion, showing anti-ischemic effects and improving exercise capacity.³¹ Afterload reduction based on the mutual interaction of HR and effective arterial elastance, resulting in increased SV, has been reported,²⁷^–³⁰. For these reasons, reduced HR may induce cardiac reverse remodeling and contribute to improved prognosis in HFrEF cases.³²^–³⁴ Based on our real-world data, increased HR is a poor prognostic factor in CAD patients with either ACS or CCS. In the future, it is expected that HR-targeting therapy will be given to CAD patients as well as to HFrEF patients.

In patients with ACS, the incidence of MACCE was significantly higher in the low-dose BB group than in the standard-dose group. The benefit of using BBs in doses greater than the standard dose in patients with HFrEF is well established.⁹^–¹¹ Kato et al showed that HR ≤71 beats/min and carvedilol ≥10 mg/day could be surrogate markers when titrating BB in patients with HFrEF.⁹ On the other hand, although some studies have examined the benefit of BBs after MI, most were conducted in the pre-reperfusion era, and there are no reports of the optimal dose of BBs. Studies demonstrated that BBs reduce mortality by approximately 20% and recurrent MI by 23%.¹⁶^,¹⁷ A meta-analysis by Huang et al showed that in the modern era of revascularization, BBs were beneficial only in patients with MI and impaired cardiac function (24% reduction in post-MI deaths).¹⁸ Our study showed the importance of a standard dose of BB for patients with ACS even in the reperfusion era. Further high-quality clinical studies, such as those examining patients with and without impaired cardiac function, are needed.

In patients with CCS, a low dose of BBs was not significantly associated with MACCE. BBs are effective in improving angina symptoms in patients with CCS, but we failed to demonstrate an event-suppressing effect in patients with CCS, who are more likely to have preserved cardiac function. In CCS patients, BBs for MI and statins are recommended by the Japanese Circulation Society/Japanese Society for Cardiovascular Surgery guideline,³⁵ and additional studies are needed to assess the optimal dose of BBs.

The higher HR in the carvedilol group was due to the lower dose of carvedilol, as in the CIBIS study,³⁶ and the fact that compared with bisoprolol (a pure BB), carvedilol (an α-BB) has a weaker HR-lowering effect through blocking of the β-receptors.

Study Limitations

This study was performed exclusively in facilities in Japan. The optimal dose of BBs may vary by race, and thus additional international studies are warranted. The physicians at each institution involved in the present study made guideline-based diagnoses (STEMI, NSTEMI and unstable angina) using the patients’ medical records, but they did not confirm the patients’ primary information (elevated myocardial markers or ECG findings). The possibility that the diagnosis differs from the universal definition of MI³⁷ thus cannot be ruled out. We did not obtain the information about the patients’ use of BBs during the follow-up period. The possibility that changes in BB doses during that affected the incidence of MACCEs cannot be ruled out. Differences in liposolubility and the intrinsic sympathetic activity of BBs are also important and might affect the MACCE incidence. There were few BBs other than bisoprolol and carvedilol used in the present population, and we were thus unable to analyze other BBs in this study.

Conclusions

In a real-world database using a multimodal data acquisition system, HR ≥75 beats/min was independently associated with worse outcome in Japanese patients with CCS or ACS.

Acknowledgments

This work was supported by Kowa Company, Ltd. Health Labour Sciences Research Grant (22FA1016), and a Sakakibara Memorial Research Grant from The Sakakibara Heart Foundation.

Disclosures

R.N., K.K., K.T. are members of Circulation Journal’s Editorial Team.

T. Kabutoya has received scholarship funding from Abbott. H.S. owns stock in Precision Inc. Y.I. has received lecture fees from Toa Eiyo Ltd. and Daiichi Sankyo. K.K. has received research grants from Otsuka Pharmaceutical, Sanwa Kagaku Kenkyusho, Daiichi Sankyo, MSD, Astellas Pharma, Eisai, Taisho Pharmaceutical, Sumitomo Dainippon Pharma, Takeda Pharmaceutical, Mitsubishi Tanabe Pharma, Teijin Pharma, Boehringer Ingelheim Japan, Bristol-Myers Squibb, Mochida Pharmaceutical; Consulting fees from Kyowa Kirin, Sanwa Kagaku Kenkyusho, Mochida Pharmaceutical; honoraria from Otsuka Pharmaceuticals, Daiichi Sankyo, Novartis Pharma, Mylan EPD; participated on advisory boards of Daiichi Sankyo, Novartis Pharma. H.F. received scholarship funds from Abbott Vascular, speaking honoraria from Novartis and Otsuka Pharmaceutical Co. Ltd, and served as a consultant for Mehergen Group Holdings, Inc. K.T. has received personal fees from Abbott Medical Co., Ltd., Amgen K.K., AstraZeneca K.K., Bayer Yakuhin, Ltd., Daiichi Sankyo Co., Ltd., Medtoronic Japan Co., Ltd., Kowa Pharmaceutical Co. Ltd., Novartis Pharma K.K., Otsuka Pharmaceutical Co., Ltd., Pfizer Japan Inc., Janssen Pharmaceutical K.K.; grants from PPD-Shin Nippon Biomedical Laboratories K.K., Alexion Pharmaceuticals, Inc., Abbott Medical Co., Ltd., Bayer Yakuhin, Ltd., Boehringer Ingelheim Japan, Daiichi Sankyo Co., Ltd., ITI Co., Ltd., Ono Pharmaceutical Co., Ltd., Otsuka Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd.; other funding from Abbott Japan Co., Ltd., Boston Scientific Japan K.K., Fides-one, Inc., GM Medical Co., Ltd., ITI Co., Ltd., Kaneka Medix Co., Ltd., Nipro Corporation, Terumo Co, Ltd., Abbott Medical Co., Ltd., Boston Scientific Japan K.K., Cardinal Health Japan, Fukuda Denshi Co., Ltd., Japan Lifeline Co., Ltd., Medical Appliance Co., Ltd., Medtronic Japan Co., Ltd., outside of the submitted work. K.T. reports personal fees from Abbott Medical Co., Ltd., Amgen K.K., AstraZeneca K.K., Bayer Yakuhin, Ltd., Daiichi Sankyo Co., Ltd., Medtronic Japan Co., Ltd., Kowa Pharmaceutical Co. Ltd., Novartis Pharma K.K., Otsuka Pharmaceutical Co., Ltd., Pfizer Japan Inc., Janssen Pharmaceutical K.K.; grants from PPD-Shin Nippon Biomedical Laboratories K.K., Alexion Pharmaceuticals, Inc., Abbott Medical Co., Ltd., Bayer Yakuhin, Ltd., Boehringer Ingelheim Japan, Daiichi Sankyo Co., Ltd., ITI Co., Ltd., Ono Pharmaceutical Co., Ltd., Otsuka Pharmaceutical Co., Ltd., Takeda Pharmaceutical Co., Ltd.; other funding from Abbott Japan Co., Ltd., Boston Scientific Japan K.K., Fides-one, Inc., GM Medical Co., Ltd., ITI Co., Ltd., Kaneka Medix Co., Ltd., Nipro Corporation, Terumo Co., Ltd., Abbott Medical Co., Ltd., Boston Scientific Japan K.K., Cardinal Health Japan, Fukuda Denshi Co., Ltd., Japan Lifeline Co., Ltd., Medical Appliance Co., Ltd., Medtronic Japan Co., Ltd., outside the submitted work. T.M. has received lecture fees (Abbott, Bayer Yakuhin, and MSD) and research funding (Amgen, Bayer Yakuhin, and Kowa). Y. Miyamoto has received research funds from Kowa Company, Ltd. within the submitted work and from Tokyo Marine and Nichido Fire Insurance Co., Ltd., Fujitsu Co., Ltd., Softbank Co., Ltd., Saraya Co., Ltd., and Meiji Yasuda Life Insurance Company outside of the submitted work. R.N. has received lecture fees from Kowa Company, Ltd. The remaining authors have nothing to disclose.

IRB Information

This study was approved by the Ethics Committee of the Jichi Medical University School of Medicine (approval no. 14-113).

Data Availability

Deidentified participant data will not be shared.

Supplementary Files

Please find supplementary file(s);

https://doi.org/10.1253/circj.CJ-22-0314

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