Beyond β-Blockade: ACE Inhibitors Reduce Non-Cardiac Mortality in High Killip Grade AMI Patients

Abstract

Objective

This study evaluates the 3-year clinical outcomes of high Killip grade (III/IV) acute myocardial infarction (AMI) patients treated with either β-blockers (BB) and angiotensin-converting enzyme inhibitors (ACEI) or BB and angiotensin receptor blockers (ARB).

Methods

A total of 13,105 patients were registered at the Korea Acute Myocardial Infarction Registry at the National Institute of Health (KAMIR-NIH). Among them, 871 patients with high Killip classification AMI were divided into the BB + ACEI group (n = 489) and the BB + ARB group (n = 381). Following propensity score matching, 343 patients were selected in each group. All patients completed a 3-year follow-up period.

Results

The results indicate no significant differences between the BB + ACEI group and BB + ARB group in terms of cardiac death, recurrent myocardial infarction, and the rate of repeat percutaneous coronary intervention. However, the BB + ACEI group exhibited significantly lower risks in major adverse cardiac events (HR = 0.574, 95% CI: 0.421–0.783, p < .001), all-cause mortality (HR = 0.561, 95% CI: 0.404–0.778, p = .001), and non-cardiac death (HR = 0.365, 95% CI: 0.208–0.639, p < .001) compared to the BB + ARB group.

Conclusion

Our results suggest that BB + ACEI treatment is more beneficial than BB + ARB for high Killip grade AMI patients. Additionally, the BB + ACEI group has a superior preventative effect on mortality compared to the BB + ARB group.

Keywords

Acute myocardial infarction High Killip grade β-blockers Angiotensin-converting enzyme inhibitors Angiotensin receptor blockers Major adverse cardiac events

Introduction

Acute myocardial infarction (AMI), a leading cardiovascular ailment, poses significant risks to global health, with numerous individuals grappling with its debilitating effects.^1,2 Despite groundbreaking advancements in medical science and technology, the mortality linked to AMI remains alarmingly high, underscoring the need for more effective interventions.³

One pivotal tool in assessing AMI prognosis is the Killip classification, which is ubiquitously adopted in the clinical landscape due to its diagnostic precision.^4,5 However, the prognosis darkens for patients falling within the higher echelons of this classification, namely Killip class III/IV. These patients experience a significant degradation in cardiac function, making their management clinically challenging.⁶ Addressing the treatment needs of this subset of AMI patients, and consequently elevating their quality of life and survival outcomes, stands as a pressing concern in contemporary cardiovascular research.

In the therapeutic arena, β-blockers (BB) have carved a niche for themselves, showcasing their potential in bolstering cardiac function and curtailing the incidence of undesirable events in the AMI context.^7–9 Parallelly, angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been championed for their efficacy in ameliorating blood pressure dynamics and fortifying cardiac performance.^10–13 While the merits of these drugs, when administered in isolation, are well-established, a lacuna exists in guiding their combined therapeutic application, especially for AMI patients characterized by elevated Killip classifications.

Despite the burgeoning evidence underscoring the virtues of BB, ACEI, and ARB in the AMI treatment paradigm, therapeutic strategies tailored for AMI patients within the high Killip class (III/IV) bracket are conspicuously scarce.¹⁴ This paucity is further accentuated by the dearth of expansive studies with an extended follow-up horizon targeting this specific patient cohort. While existing research might shed light on the immediate aftermath of such interventions or restrict their scope to particular pharmaceutical agents,^14,15 a comprehensive understanding of the long-term ramifications of concomitant BB and ACEI or ARB administration in high Killip class AMI patients remains elusive.

Motivated by these observations and existing lacunae, our study endeavors to juxtapose the clinical outcomes of BB + ACEI against BB + ARB regimens in AMI patients with elevated Killip classifications through an extended follow-up. Through this exploration, we aspire to furnish the medical community with a more nuanced, holistic, and evidence-backed treatment blueprint for this high-risk demographic. Beyond its immediate clinical ramifications, this study also holds the promise of enriching the foundational knowledge pool, thereby paving the way for innovative drug research and patient-centric therapeutic strategies, all aimed at enhancing the life quality and longevity of high-risk AMI patients.

Materials and Methods

Study Population and Data Collection

This investigation drew its patient data from the Korea Acute Myocardial Infarction-National Health Insurance (KAMIR-NIH) registry, which collected data from October 2011 through December 2015. The KAMIR-NIH stands as a pioneering, web-enabled, multi-center registry, collaboratively maintained by over 20 esteemed higher education institutions throughout Korea. These institutions possess the requisite infrastructure and state-of-the-art equipment, facilitating the successful execution of Percutaneous Coronary Intervention (PCI) and ensuring comprehensive surveillance of real-time treatment strategies and outcomes for acute myocardial infarction (AMI) patients.¹⁶

From the entire cohort of 13,105 enrolled patients, specific subsets were excluded based on the following criteria:

Non-usage of Beta-Blockers (BB) (n = 2511)

Non-usage of Angiotensin-converting enzyme inhibitors (ACEI) or Angiotensin II receptor blockers (ARB) (n = 1664)

Concurrent usage of ACEI and ARB (n = 64)

Classification under the low Killip class (I or II; n = 7955)

Loss to follow-up or having data incompleteness (n = 40)

This meticulous selection yielded a final dataset comprising 871 high Killip grade AMI patients. These individuals were stratified into two therapeutic arms: BB + ACEI (n = 489) and BB + ARB (n = 381) (Figure 1). To glean profound insights, the study engaged with these patients through structured interviews, exhaustive chart analyses, and periodic telephonic surveys for a duration of 3 years.

Figure 1.

Flowchart illustrating the process of data screening for the study.

Diagnostic Criteria and Clinical Endpoints

The confirmation of acute myocardial infarction (AMI) was anchored on a triad: clinical presentation, a spike in cardiac biomarkers, such as creatine kinase-MB (CK-MB), troponin I (Tn-I), or troponin T (Tn-T), and hallmark electrocardiogram (ECG) changes like ST-segment shifts and the emergence of pathological Q waves.^17,18

The severity of heart failure was gauged using the Killip classification. As delineated in existing literature,^4,19 Grade I represents an absence of overt heart failure symptoms. In contrast, Grade II manifests as mild to moderate symptoms, which may include clinical findings like an S3 gallop, mid-lung field rales, or a heightened jugular venous distention. Grade III is earmarked by the presence of pulmonary edema, while Grade IV is indicative of cardiogenic shock or pronounced hypotension.

The study was based on the prescriptions provided at discharge, with patients required to continue using the same medications after discharge. The primary clinical endpoint was the incidence of major adverse cardiac events (MACE) during a 3-year follow-up period, with MACE defined as all-cause mortality, recurrent myocardial infarction, and repeat percutaneous coronary intervention (PCI). Secondary endpoints included the rates of cardiac-related and non-cardiac-related deaths.

Statistical Analysis

Continuous variables were presented using means and standard deviations (SD) or medians (interquartile range, IQR). Categorical variables were expressed as numbers and percentages. Unpaired t-test or Mann-Whitney U test were employed for comparing continuous variables, while chi-square test or Fisher's exact test were used for comparing categorical variables. A comprehensive review of baseline clinical, laboratory, and medication variables was conducted. Propensity score matching (PSM) was utilized to adjust for potential confounders (selected based on previous literature, including age, gender, and etc). Matching was performed using a logistic regression model to estimate the propensity scores (C-statistic of 0.903). Based on the propensity scores, patients in the BB + ACEI and BB + ARB groups were matched using the nearest neighbor matching method. Baseline clinical data, test results, angiography, and medications were compared between the matched populations for these two groups, each consisting of 343 patients (Figure 1). Mortality rates were compared using Kaplan-Meier curves and Cox proportional hazards regression models. Cox proportional hazards regression models were used for both univariate and multivariate analyses, with a significance threshold set at a p-value of less than 0.10. In the multivariate analysis, a backward regression approach was adopted, adjusting for male gender, elderly (≥65 years), low hemoglobin levels (<12 g/dl), high heart rate (>100 beats/min), high body mass index (BMI > 25 kg/m2), hypertension, diabetes, dyslipidemia, smoking, history of myocardial infarction, high LDL-C (≥70 mg/dl), low glomerular filtration rate (GFR < 60 mL/min/1.73 m2), reduced left ventricular ejection fraction (LVEF < 40%), ACC/AHA B2/C lesion, non-stent implantation, non-drug eluting stent (DES) placement, and poor thrombolysis in myocardial infarction (TIMI) score (0/1). Adjusted survival analysis using multivariate Cox regression analysis was performed, resulting in hazard ratios (HR) and 95% confidence intervals (CI). Subgroup analyses were conducted post-PSM to evaluate if the correlation between medication treatment regimens and MACE risk differed based on gender, age, hypertension, diabetes, dyslipidemia, history of myocardial infarction, presence of vascular disease, and PCI status. Two-tailed analyses were carried out using SPSS Inc. version 25.0 (located in Chicago, Illinois), with statistical significance considered for p-values less than .05.

Results

Demographic and Baseline Clinical Characteristics

This study enrolled a total of 870 patients with high Killip class. Table 1 summarizes the baseline clinical and laboratory characteristics of each patient. The BB + ACEI group consisted of 489 patients, while the BB + ARB group included 381 patients. In the BB + ACEI group, the average age of patients was higher than in the BB + ARB group (69.25 ± 11.96 years vs. 66.12 ± 12.34 years, p < .001), with 56.9% and 68.5% of patients aged 65 years or older in the BB + ACEI and BB + ARB groups, respectively. Additionally, the proportion of males was higher in the BB + ACEI group compared to the BB + ARB group (69.9% vs. 59.8%, p = .002). The BB + ACEI group had more smokers, typical chest pain patients, and Killip class IV patients than the BB + ARB group. However, there were fewer patients with hypertension or diabetes in the BB + ACEI group compared to the BB + ARB group. In contrast to the BB + ARB group, the BB + ACEI group had lower average levels of neutrophils, creatinine, N-terminal pro-brain natriuretic peptide (NT-pro-BNP), and platelet reaction unit (PRU), while levels of hemoglobin, total cholesterol (TC), LDL-C, glomerular filtration rate (GFR), CK-MB, and Tn-I were higher. After propensity score matching (PSM), apart from several key variables (chest pain, CK-MB, NT-pro-BNP, PRU, and aspirin reaction units (ARU)), the two groups did not exhibit significant differences in baseline clinical or laboratory indicators (Table 1).

Table 1.

Baseline Clinical and Laboratory Characteristics in Both Patient Groups.

Variables	Entire patient population		p-value	Propensity score matching patients		p-value
Variables	BB + ACEI(n = 489)	BB + ARB(n = 381)	p-value	BB + ACEI(n = 343)	BB + ARB(n = 343)	p-value
Demographic
Age, mean (SD), year	69.25 ± 11.96	66.12 ± 12.34	<.001	68.93 ± 11.34	68.72 ± 11.87	.818
Age ≥65 (%)	278 (56.9)	261 (68.5)	<.001	233 (67.9)	228 (66.5)	.684
Male sex (%)	342 (69.9)	228 (59.8)	.002	219 (63.8)	210 (61.2)	.478
BMI, mean (SD), the	23.50 ± 3.16	23.60 ± 3.88	.667	23.32 ± 3.22	23.69 ± 3.90	.176
Clinical symptoms (%)
Dyspnea	238 (48.7)	182 (47.8)	.792	178 (51.9)	161 (46.9)	.223
Typical chest pain	363 (74.2)	233 (61.2)	<.001	248 (72.3)	208 (60.6)	.001
Cardiovascular risk factors (%)
Hypertension	269 (53.2)	256 (67.2)	<.001	200 (58.3)	224 (65.3)	.059
Diabetes mellitus	166 (33.9)	171 (44.9)	.001	141 (41.1)	144 (42.0)	.816
Dyslipidemia	51 (10.4)	28 (7.3)	.117	39 (11.4)	25 (7.3)	.066
Current smoking	185 (37.8)	104 (27.3)	.001	107 (31.2)	98 (28.6)	.453
Medical history (%)
Myocardial infarction	42 (8.6)	38 (10.0)	.483	31 (9.0)	30 (8.7)	.893
Angina	46 (9.4)	50 (13.1)	.083	31 (9.0)	44 (12.8)	.112
Heart failure	12 (2.5)	15 (3.9)	.213	10 (2.9)	14 (4.1)	.410
Cerebrovascular accident	51 (10.4)	34 (8.9)	.458	45 (13.1)	30 (8.7)	.066
Vital sign on admission
SBP, mean (SD), mmHg	112.93 ± 42.04	114.34 ± 41.76	.622	112.36 ± 40.85	113.20 ± 43.31	.792
DBP, mean (SD), mmHg	68.33 ± 25.55	69.14 ± 28.04	.655	67.83 ± 24.37	68.30 ± 29.00	.821
HR, mean (SD), beat/min	80.88 ± 30.11	83.69 ± 28.83	.165	83.36 ± 30.07	83.20 ± 29.60	.947
High Killip class (IV) (%)	205 (41.9)	125 (32.8)	.006	126 (36.7)	123 (35.9)	.812
LVEF, (%)	45.20 ± 12.88	46.36 ± 12.46	.183	44.43 ± 13.07	46.28 ± 12.63	.061
Laboratory findings
WBC, 10³/ul	12.13 ± 4.96	12.13 ± 5.13	.315	12.37 ± 5.25	12.21 ± 5.28	.687
Neutrophil	66.19 ± 17.35	70.96 ± 16.00	<.001	67.89 ± 16.66	70.15 ± 16.23	.072
Hb, g/dl	13.20 ± 2.26	12.42 ± 2.63	<.001	12.81 ± 2.29	12.60 ± 2.58	.252
Total cholesterol, mg/dl	172.96 ± 45.45	164.37 ± 45.44	.007	171.91 ± 46.71	165.23 ± 46.33	.065
Triglyceride, mg/dl	121.91 ± 83.66	115.43 ± 74.80	.254	120.25 ± 84.61	117.63 ± 76.58	.682
HDL-cholesterol, mg/dl	42.38 ± 11.59	40.97 ± 13.39	.110	42.17 ± 12.07	40.32 ± 12.34	.056
LDL-cholesterol, mg/dl	106.61 ± 38.78	100.57 ± 40.36	.042	104.89 ± 37.99	101.97 ± 41.06	.387
Glucose	212.87 ± 109.52	218.27 ± 112.08	.480	215.79 ± 110.61	214.57 ± 107.51	.885
Creatinine, mg/dl	1.24 ± 0.88	1.48 ± 1.39	.002	1.32 ± 0.97	1.35 ± 1.08	.691
GFR, mL/min/1.73 m²	71.12 ± 27.76	66.04 ± 35.77	.019	67.15 ± 27.95	68.64 ± 35.19	.540
Hs-CRP, mg/dl	2.09 ± 4.27	2.78 ± 4.88	.074	2.49 ± 4.58	2.69 ± 4.93	.649
Peak CK-MB, ng/ml	154.96 ± 257.81	94.59 ± 116.72	<.001	142.73 ± 260.62	101.09 ± 119.93	.008
Peak Troponin-I, ng/ml	60.97 ± 120.00	41.89 ± 68.14	.008	51.78 ± 97.10	43.82 ± 69.64	.239
NT-pro-BNP	3670.67 ± 6354.60	7702.33 ± 10565.69	<.001	4563.41 ± 7048.96	7152.48 ± 10294.50	.001
HbA1c, (%)	6.61 ± 1.55	6.73 ± 1.39	.319	6.72 ± 1.51	6.70 ± 1.40	.888
PRU	201.41 ± 107.59	264.03 ± 114.41	<.001	203.57 ± 111.52	263.76 ± 117.44	.002
ARU	454.61 ± 73.66	488.61 ± 74.83	.183	451.74 ± 67.86	490.69 ± 74.29	.004

Data are expressed as number (%) unless otherwise indicated.

Abbreviations: ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; ARU, aspirin reaction units; BB, beta-blocker; BMI, body mass index; BNP, brain natriuretic peptide; CK, creatine kinase; DBP, diastolic blood pressure; GFR, glomerular filtration rate; Hb, hemoglobin; HDL, high-density lipoprotein; HR, heart rate; Hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein; LVEF, left ventricular ejection fraction; NT-pro-BNP, N-terminal pro-brain natriuretic peptide; PRU, P2Y12 reaction units; SBP, systolic blood pressure; WBC, white blood cell.

Coronary Angiography and Interventional Outcomes

Subsequently, we evaluated the outcomes of coronary angiography and interventional treatment as presented in Table 2. Following coronary angiography, patients in the BB + ACEI group exhibited lower incidences of ACC/AHA B2/C lesions (84.8% vs. 92.3%) and multi-vessel PCI (14.1% vs. 19.1%) compared to those in the BB + ARB group. Moreover, there was a higher proportion of patients receiving drug-eluting stents (DES) in the BB + ACEI group in contrast to the BB + ARB group (95.5% vs. 90.9%). In terms of hemodynamics, the BB + ACEI group demonstrated superior performance in both initial TIMI flow grade (0 or 1) (65.2% vs. 54.6%) and final TIMI flow grade (3) (97.5% vs. 94.4%) when compared to the BB + ARB group. Following discharge, the frequency of calcium channel blocker (CCB) usage was lower in the BB + ACEI group than in the BB + ARB group (3.1% vs. 8.7%). Post propensity score matching (PSM), significant differences were also observed in ACC/AHA B2/C lesions, multi-vessel disease, final TIMI flow grade 3, DES implantation, and CCB usage, while there were no significant differences between the two groups in terms of other medications and vascular imaging results.

Table 2.

Summary of Procedures and Medications in Both Patient Groups.

Variables	Entire patient population		p-value	Propensity score matching patients		p-value
Variables	BB + ACEI(n = 489)	BB + ARB(n = 381)	p-value	BB + ACEI(n = 343)	BB + ARB(n = 343)	p-value
Procedure in Cath-room (%)	448 (91.6)	337 (88.5)	.119	306 (89.2)	312 (91.0)	.443
Target vessel in coronary artery			.652			.959
Left main	18 (3.7)	13 (3.4)		12 (1.7)	13 (1.9)
Left anterior descending	184 (37.6)	139 (36.5)		125 (36.4)	129 (37.6)
Left circumflex	64 (13.1)	49 (12.9)		44 (12.8)	44 (12.8)
Right coronary artery	182 (37.2)	136 (35.7)		125 (36.4)	126 (36.7)
ACC/AHA B2/C lesion	379 (84.8)	311 (92.3)	.001	260 (85.2)	290 (92.9)	.002
Multivessel lesion	258 (52.8)	180 (47.2)	.234	191 (57.7)	155 (46.0)	.002
Multivessel PCI	69 (14.1)	75 (19.1)	.015	52 (15.2)	68 (19.8)	.239
Stepwise PCI	49 (10.0)	38 (10.0)	.293	33 (9.6)	37 (10.8)	.682
Implanted stent	423 (94.4)	308 (91.4)	.097	287 (93.8)	287 (92.0)	.383
Implanted DES	408 (95.5)	280 (90.9)	.002	277 (96.5)	262 (91.3)	.009
TIMI flow grade
Initial TIMI flow 0/1	292 (65.2)	184 (54.6)	.003	192 (62.7)	179 (57.4)	.173
Final TIMI flow 3	437 (97.5)	318 (94.4)	.021	299 (97.7)	294 (94.2)	.028
Coronary artery bypass graft	3 (0.6)	3 (0.8)	.758	3 (0.9)	3 (0.9)	1.000
TPM insertion	46 (9.4)	33 (8.7)	.704	26 (7.6)	33 (9.6)	.340
ECMO	9 (1.8)	2 (0.5)	.085	5 (1.5)	2 (0.6)	.254
Medical treatment (%)
Aspirin	489 (100.0)	381 (100.0)	1.000	343 (100.0)	343 (100.0)	1.000
P2Y12 receptor inhibitor
Clopidogrel	418 (85.5)	308 (80.8)	.068	293 (85.4)	274 (79.9)	.055
Ticagrelor or Prasugrel	45 (9.2)	44 (11.5)	.257	29 (8.5)	42 (12.2)	.103
Statin	438 (89.6)	351(92.1)	.198	302 (88.0)	316 (92.1)	.074
Calcium channel blocker	15 (3.1)	33 (8.7)	<.001	13 (3.8)	26 (7.6)	.032

Data are expressed as number (%) unless otherwise indicated.

Abbreviations: ACC, American College of Cardiology; ACEI, angiotensin converting enzyme inhibitors; AHA, American Heart Association; ARB, angiotensin receptor blocker; BB, beta blocker; DES, dual eluting stent; ECMO, extracorporeal membrane oxygenation; PCI, percutaneous coronary intervention; TIMI, Thrombolysis In Myocardial Infarction; TPM, temporary pacemakers.

Clinical Outcomes

According to the Kaplan-Meier curves and Cox proportional hazards regression model (Table 3), it was found that the cumulative incidence of Major Adverse Cardiovascular Events (MACE) was lower in the BB + ACEI group (n = 77) compared to the BB + ARB group (n = 119) (15.7% vs. 31.2%, log-rank test p < .001; HR = 0.597; 95% CI, 0.415–0.859; p = .005). Furthermore, similar trends were observed in overall mortality and non-cardiac mortality. The all-cause mortality rate was lower in the BB + ACEI group (n = 64) than in the BB + ARB group (n = 109) (13.1% vs. 28.6%, log-rank test p < .001; HR = 0.549; 95% CI, 0.369–0.816; p = .003). The non-cardiac mortality rate in the BB + ACEI group (n = 19) was also lower than in the BB + ARB group (n = 48) (3.9% vs. 12.6%, log-rank test p < .001; HR = 0.479; 95% CI, 0.254–0.902; p = .023).

Table 3.

Comparison of Unadjusted and Adjusted Clinical Outcomes at 3 Years Between Two Patient Groups.

Variables	BB + ACEI	BB + ARB	UnadjustedHR (95% CI)	p-value	AdjustedHR (95% CI)	p-value
Clinical outcomes
All-cause death	64 (13.1)	109 (28.6)	0.427 (0.313–0.581)	<.001	0.549 (0.369–0.816)	.003
Cardiac death	45 (9.2)	61 (16.0)	0.544 (0.370–0.799)	.002	0.606 (0.364–1.010)	.055
Non-cardiac death	19 (3.9)	48 (12.6)	0.282 (0.116–0.480)	<.001	0.479 (0.254–0.902)	.023
Recurrent MI	10 (2.0)	15 (3.9)	0.485 (0.218–1.080)	.077	0.702 (0.247–1.997)	.507
Repeat PCI	14 (2.9)	9 (2.4)	1.090 (0.471–2.518)	.841	1.108 (0.422–2.909)	.835
MACE	77 (15.7)	119 (31.2)	0.467 (0.350–0.622)	<.001	0.597 (0.415–0.859)	.005
Propensity score matched
All-cause death	57 (16.6)	97 (28.3)	0.561 (0.404–0.778)	.001	0.573 (0.375–0.875)	.010
Cardiac death	40 (11.7)	53 (15.5)	0.727 (0.482–1.096)	.127	0.621 (0.359–1.075)	.089
Non-cardiac death	17 (5.0)	44 (12.8)	0.365 (0.208–0.639)	<.001	0.505 (0.257–0.994)	.048
Recurrent MI	8 (2.3)	13 (3.8)	0.595 (0.247–1.436)	.248	0.636 (0.206–1.963)	.431
Repeat PCI	8 (2.3)	9 (2.6)	0.841 (0.325–2.181)	.722	0.902 (0.291–2.801)	.859
MACE	64 (18.7)	106 (30.9)	0.574 (0.421–0.783)	<.001	0.585 (0.393–0.872)	.008

Data are expressed as number (%) unless otherwise indicated.

Adjusted for age, sex, diabetes, hypertension, dyslipidemia, GFR, smoking, LVEF, previous MI, and anemia.

Abbreviations: ACEI, angiotensin converting enzyme inhibitor; ARB, angiotensin receptor blocker; BB, beta blocker; MI, myocardial infarction; MACE, major adverse cardiac events; PCI, percutaneous coronary intervention.

Propensity score matching (PSM) analysis further confirmed that the cumulative incidence rates of MACE, overall mortality, and non-cardiac mortality were all lower in the BB + ACEI group compared to the BB + ARB group (18.7% vs. 30.9%, HR = 0.585; 95% CI, 0.393–0.872, p = .008; 16.6% vs. 28.3%, HR = 0.573; 95% CI, 0.375–0.875; p = .010; 5.0% vs. 12.8%, HR = 0.505; 95% CI, 0.257–0.994; p = .048) (Table 3; Figure 2). Table 4 summarizes the Cox regression multivariable analysis of MACE predictive factors in the PSM analysis. Advanced age (≥65 years; HR = 1.786; 95% CI, 1.015–3.143; p = .044), low glomerular filtration rate (GFR; < 60 mL/min/1.73 m²; HR = 1.733; 95% CI, 1.122–2.677; p = .013), low left ventricular ejection fraction (LVEF; < 40%; HR = 1.506; 95% CI, 0.989–2.291; p = .046), and absence of drug-eluting stent implantation (HR = 3.004; 95% CI, 1.768–5.105; p < .001) were identified as predictive factors for 3-year MACE. Figure 3 illustrates the subgroup analysis of 3-year MACE in the follow-up after PSM. Factors such as gender, age, hypertension, diabetes, dyslipidemia, history of myocardial infarction, vascular disease status, and PCI status did not alter the association between the two drug treatments and MACE risk.

Figure 2.

Cumulative incidence rates of major adverse cardiovascular events (MACE), all-cause mortality, cardiovascular mortality, and non-cardiovascular mortality in the BB + ACEI and BB + ARB groups.

Figure 3.

Subgroup analysis of MACE during the 3-year follow-up after propensity score matching (PSM).

Table 4.

Univariate and Multivariate Analysis for Predictors of MACE in PSM Patients.

	Univariate analysis		Multivariate analysis
	HR (95% CI)	p-value	HR (95% CI)	p-value
Male	0.624 (0.461–0.843)	.002	0.891 (0.466–1.394)	.691
Age ≥65 years	3.386 (2.198–5.215)	<.001	1.786 (1.015–3.143)	.044
Hb <12 g/dL	2.039 (1.509–2.754)	<.001	1.059 (0.669–1.677)	.805
Heart rate >100 beats/min	1.760 (1.283–2.414)	<.001	1.379 (0.886–2.146)	.155
BMI ≥25 kg/m²	0.731 (0.531–1.007)	.055	0.851 (0.552–1.313)	.446
Hypertension	1.607 (1.155–2.235)	.005	1.199 (0.764–1.880)	.430
Diabetes mellitus	1.829 (1.353–2.474)	<.001	1.100 (0.716–1.691)	.663
Dyslipidemia	0.585 (0.309–1.109)	.101
Smoker	0.600 (0.415–0.867)	.006	0.812 (0.471–1.398)	.452
Previous MI	1.682 (1.083–2.611)	.020	1.242 (0.630–2.449)	.531
LDL-cholesterol >70 mg/dl	0.579 (0.409–0.819)	.002	0.729 (0.466–1.140)	.166
GFR <60 mL/min/1.73 m²	2.691 (1.972–3.672)	<.001	1.733 (1.122–2.677)	.013
LVEF <40%	2.043 (1.510–2.766)	<.001	1.506 (0.989–2.291)	.046
ACC/AHA B2/C lesion	1.265 (0.699–2.289)	.437
Non-implanted stent	1.169 (0.631–2.166)	.620
Non-implanted DES	4.971 (3.156–7.829)	<.001	3.004 (1.768–5.105)	<.001
Post TIMI flow 0/1	0.941 (0.385–2.300)	.895

Abbreviations: ACC, American College of Cardiology; AHA, American Heart Association; BMI, body mass index; CI, confidence interval; DES, dual eluting stent; GFR, glomerular filtration rate; Hb, hemoglobin; HR, Hazard ratio; LDL, low-density lipoprotein; LVEF; left ventricular ejection fraction; TIMI, Thrombolysis In Myocardial Infarction.

In conclusion, our study results suggest that the combination of BB + ACEI may be a superior therapeutic approach for reducing MACE in high Killip class acute myocardial infarction (AMI) patients.

Discussion

Our comprehensive study sheds light on the comparative efficacy of combination treatments involving beta-blockers (BB) with angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) for patients diagnosed with acute myocardial infarction (AMI) who also present with a high Killip class. The pivotal role of BBs in managing ischemic heart failure has been previously highlighted by numerous studies.²⁰ Their mechanism of action, which encompasses reducing heart rate, moderating myocardial oxygen consumption, and suppressing sympathetic nerve stimulation, results in effective blood pressure regulation.²¹ Despite these benefits, it is essential to recognize their potential to amplify β receptor numbers, thereby increasing receptor sensitivity to catecholamines.²² This mechanism confers myocardial protection and, combined with the anti-arrhythmic properties of BBs, offers robust protection against arrhythmic events.²³

Simultaneously, the favorable impact of ACE inhibitors on cardiovascular health, including their role in promoting endothelial function and inhibiting atherosclerosis progression, is well-documented.^24–28 ARBs, on the other hand, work by selectively targeting the angiotensin II type 1 receptor, effectively mitigating the detrimental effects of angiotensin II.²⁹ Nonetheless, they also carry the potential to stimulate angiotensin II type 2 receptors, a mechanism that is twofold in nature. While it can foster vasodilation and prevent unwarranted cell proliferation, it may also induce hypertrophy, inflammation, and cellular apoptosis.^30,31

In our most recent investigation, we observed that, although the revascularization rate was higher among non-ST segment elevation myocardial infarction (MI) patients in the BB + ARB group in prior studies, such a disparity did not prevail in our high Killip-grade cohort.³² Distinctly, the BB + ACEI group exhibited a reduced mortality rate, especially concerning non-cardiac deaths. This observation led us to postulate that heightened activation of angiotensin II type 2 receptors might be the underlying culprit, increasing cellular apoptosis and vulnerability to infections.

Existing literature presents a mixed picture. Some suggest that AMI patients undergoing combined therapy with BB and either ACEI or ARB have a more pronounced reduction in major adverse cardiovascular events (MACE) than those administered renin-angiotensin system inhibitors alone.³³ However, there are also conflicting reports where ACEIs and ARBs did not exhibit significant differences in MACE occurrence within two years among STEMI patients with diabetes.³⁴ A different study hinted at a superior survival advantage with ACEIs over ARBs post-AMI.³⁵ Two recent papers authored by Kim et al. reported that clinical outcomes were superior in AMI patients receiving BB and ACEI treatment compared to those receiving BB and ARB therapy.^36,37

Our subgroup analysis, which encompassed diverse demographics and primary disease characteristics, indicated that the BB + ACEI combination was more efficacious than BB + ARB, especially in preventing MACE. Through analysis using Kaplan-Meier curves and Cox proportional hazards regression models, it was observed that the BB + ACEI combination exerted a significant effect in reducing the cumulative rate of major adverse cardiac events (MACE) in high Killip patients. Furthermore, risk factors such as advanced age (≥65 years), diminished glomerular filtration rate (GFR) (<60 mL/min/1.73 m²), lowered left ventricular ejection fraction (LVEF) (<40%), and the lack of drug-eluting stent (DES) implantation (Figure 4) were predictive of MACE occurrence in our high Killip class AMI patients.

Figure 4.

Conceptual diagram comparing the three-year clinical efficacy of BB + ACEI and BB + ARB treatments in patients with high Killip classification acute myocardial infarction (AMI).

While this study possesses distinct advantages and value, there are areas that require improvement. For instance, limitations exist in sample size and study design. Additionally, there are certain constraints in data collection, particularly the lack of information regarding the timing of initial ACEI or ARB use, specific dosages, and detailed information on statin therapy. These data gaps restrict our ability to conduct a thorough analysis on treatment timing windows and dose effects. Although these limitations may have impacted the depth of our analysis, the study results still offer crucial insights into the treatment of high Killip-level AMI patients and provide guidance for future research directions. Conclusively, our findings underscore the potential superiority of the BB + ACEI regimen over BB + ARB in high Killip-grade AMI patients, especially in mortality reduction. We strongly advocate for the integration of our results into clinical practice, emphasizing the BB + ACEI combination for those without contraindications like persistent cough. As the scientific community aims to refine treatment guidelines, our study's contribution in addressing the high Killip grade AMI patients’ therapeutic needs is undeniable. Yet, future endeavors should pivot towards larger, multi-center randomized controlled trials to bolster the generalizability and applicability of our findings.

Footnotes

Abbreviations

Acknowledgements

None.

Authors’ Contributions

Simei Sun conceived and designed the research. Xiongyi Han performed experiments. Liyan Bai interpreted results of experiments. Myung Ho Jeong analyzed data. Cheng Jin prepared figures, drafted the paper, and edited and revised the manuscript. All authors read and approved the final version of the manuscript.

Ethical/Legal Considerations

Ethical considerations were taken into account throughout the study, including obtaining informed consent from the participants, ensuring patient privacy and confidentiality, and adhering to the guidelines and regulations set forth by the Korean Acute Myocardial Infarction National Institutes of Health (KAMIR-NIH) registry. The study was conducted in accordance with the Declaration of Helsinki and all relevant ethical standards of Chonnam National University Hospital, Gwangju, Korea.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Research of Korea Centers for Disease Control and Prevention (2016-ER6304-02).

ORCID iD

Cheng Jin

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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