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Won, Suh, Kim, Ko, and Hong: Clinical Impact of Beta Blockers in Patients with Myocardial Infarction from the Korean National Health Insurance Database
Original Article

Korean Circulation Journal 2020; 50(6): 499-508.

Published online: 6 January 2020

DOI: https://doi.org/10.4070/kcj.2019.0231

Clinical Impact of Beta Blockers in Patients with Myocardial Infarction from the Korean National Health Insurance Database

Hoyoun Won, MD, PhD1, Yongsung Suh, MD, PhD2, Gwang Sil Kim, MD3, Young-Guk Ko, MD, PhD4, 5, Myeong-Ki Hong, MD, PhD4, 5

1Cardiovascular & Arrhythmia Center, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea.

2Department of Cardiology, Myongji Hospital, Goyang, Korea.

3Department of Cardiology, Sanggye-Paik Hospital, Inje Universiy College of Medicine, Seoul, Korea.

4Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Korea.

5Cardiovascular Research Institute, Yonsei University College of Medicine, Seoul, Korea.

Correspondence to Myeong-Ki Hong, MD, PhD. Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1, Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea. mkhong61@yuhs.ac

Received 16 July 2019       Revised 29 October 2019       Accepted 4 December 2019

Copyright © 2020. The Korean Society of Cardiology

The Korean Society of Cardiology

(open-access, https://creativecommons.org/licenses/by-nc/4.0):

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background and Objectives

Whether beta blockers favorably impact the clinical outcome in patients with acute myocardial infarction (AMI) remains in debate. We investigated the impact of beta blocker on major clinical outcomes during 2 years after percutaneous coronary intervention (PCI) in patients with AMI.

Methods

All patients with the first AMI treated with PCI for the period of 2005 to 2014 from the Korean National Health Insurance Service claims database were enrolled. We defined the regular user as medication possession ratio (MPR) ≥80% and non-user as MPR=0%. We compared the occurrence of all cause death, myocardial infarction (MI) and stroke according to adherence of beta-blockers. A 1:1 propensity score-matching was conducted to adjust for between-group differences.

Results

We identified a total 81,752 patients with met eligible criteria. At discharge, 63,885 (78%) patients were prescribed beta blockers. For 2 years follow up period, regular users were 53,991 (66%) patients, non-users were 10,991 (13%). In the propensity score matched population, regular use of beta blocker was associated with a 36% reduced risk of composite adverse events (all death, MI or stroke) (hazard ratio [HR], 0.636; 95% confidence interval [CI], 0.555–0.728; p<0.001). Compared to no use of beta blocker, regular use significantly reduced all death (HR, 0.736; 95% CI, 0.668–0.812; p<0.001), MI (HR, 0.729; 95% CI, 0.611–0.803; p<0.001) and stroke (HR, 0.717; 95% CI, 0.650–0.791; p<0.001).

Conclusions

Prescription of beta blocker in patients with AMI after PCI was sequentially increased. Continuous regular use of beta blocker for 2 years after AMI reduced major adverse events compared to no use of beta blocker.

Keywords: Adrenergic beta-antagonists, Myocardial infarction, Secondary prevention

INTRODUCTION

Beta blockers have been the standard treatment for patients with acute myocardial infarction (AMI). Beta blockers have the beneficial effects which reduced ischemia, blood pressure, fatal arrhythmia, and thrombosis.1)234) Guidelines had been established mostly based on randomized trials before reperfusion era. In the era of percutaneous coronary intervention (PCI), there was no prospective randomized trial to show the efficacy of beta blocker therapy on clinical outcomes in AMI patients. In addition, several observational studies have showed inconsistent results.5)6) With evidences of accumulating recent evidences, practical guidelines differ in terms of recommendations regarding indication and duration of beta blockers. In addition, continuous use of beta blocker is often impossible due to adverse drug effect. There was remained unsolved issue whether beta blocker use beyond 1 year after AMI improved outcomes in the reperfusion era. Therefore, we investigated the association of beta blocker therapy with clinical outcomes in patients with AMI who underwent PCI, using a nationwide cohort study using an insurance claims database.

METHODS

Study population

This study is designed as a retrospective cohort using claim data of Korean National Health Insurance Service (KNHIS). The KNHIS as the single insurer of Korean National Health Insurance Program (KNHIP) is currently operating a medical claim database including not only diagnosis, prescription and procedure but also personal data such as age, gender, residential area or the date of death. All of medical service providers and population in Korea have an obligation to join the KNHIP according to national acts. Therefore, the KNHIS database covers almost all of medical behaviors performed in the whole Korean population since 2002. The database is based on Korean Standard Classification of Disease (KCD) 7 code system which is very similar with the International Statistical Classification of Diseases and Related Health Problems (ICD) 10 code system. From 2005 to 2014, we included the lifetime-first users of coronary bare metal or drug eluting stent with diagnostic code of AMI (I21, I22 I23) using the KNHIS database. The exclusion criteria are as follows. 1) no coronary stent implantation, 2) cardiopulmonary resuscitation, 3) all death within 3 months, 4) chronic obstructive pulmonary disease, 5) previous diagnosis of metastatic cancer. In addition, we excluded the patients who never had any anti-platelet agents during follow-up in order to minimize the confounding factor related with the loss of follow-up. The study population was followed for 2 years or until primary end points after stent implantation.

Measurement of variables

The measurement of variables was performed analyzing diagnostic, prescription and procedural code in claim data. We used medical possession rate (MPR) which is calculated as dividing prescription duration by follow-up duration in order to identify long-term use pattern of beta blocker. We classified study population into regular users (MPR ≥80%), irregular users (1–79%), non-users (0%) according to MPR during follow up.7) Baseline characteristics of underlying disease were considered pre-diagnosed if individuals had two consequent diagnoses in out-patient clinic or a single diagnosis during hospitalization. We calculated Charlson comorbidity score which definition was following the Quan's previous study.8) The detailed working definitions of all variables in this study are listed in Supplementary Table 1. The primary end point of this study is the composite of all-cause death, followed myocardial infarction (MI) or all type of stroke. The definition of followed MI is the combination of the main diagnosis of AMI (diagnostic code: I21, I22, I23) confirmed by coronary angiography (procedure code: HA670) during rehospitalization or newly diagnosed sudden cardiac arrest (diagnostic code: I469). We used narrow definition of AMI in order to minimize false-positive detection related with misdiagnosis of previous old MI. All types of stroke include ischemic, hemorrhagic or unknown type of stroke (diagnostic code: I60–64) confirmed with imaging study (examination code: HE101, 201, 135, 235, 236, 451, 461) during hospitalization.

Statistical analysis

The χ2 test or Fisher's exact test were used to compare categorical variables. The student t-test was conducted to compare continuous variables. Univariate and distributional analysis included measures of clinical outcomes. For propensity score matching (PMS), we performed a 1:1 case-control match on the propensity score with a hierarchical sequence until no more matches made. SAS Logistic procedure code was used to create the propensity score. A multivariate Cox proportional-hazards regression model was used to determine the effect of beta blocker as an independent predictor of outcomes. Covariates for the adjustment were selected using multivariate regression analysis. The following variables were included in the Cox proportional-hazard regression model as confounding factors; age, sex, year of study enrollment, hypertension, diabetes mellitus, dyslipidemia, previous stroke, previous MI, heart failure, history of malignancy, stent type, number of stents, in hospital and followed medications (dual antiplatelet, angiotensin II receptor blockers [ARB] or angiotensin converting enzyme [ACE] inhibitor, calcium channel blocker, statin, loop diuretics, and spironolactone). Statistical analysis was performed using the SAS software (SAS institute, ver 9.1, Cary, NC, USA). The statistical significance level was p<0.05.

Ethic statement

The study protocol was approved by Chung-Ang University Hospital Institutional Review Board (1601-005-254). Informed consent was waived by Institutional Review Board because this study was based on the KNHIS database which was fully anonymized.

RESULTS

Prescription rate of beta blocker

We identified a total of 81,752 patients that met eligible criteria for the period between January 2005 and December 2014. Overall, 63,885 (78%) patients were prescribed beta blockers and 17,867 (22%) were not prescribed at discharge (Tables 1 and 2). There was a trend of increase use of beta blockers from 70% in 2005 to 78% in 2014. Among prescribed beta blockers at discharge, the most commonly prescribed medication was carvedilol (52%), followed by bisoprolol (22%). Overall for 2 years, regular users were 53,991 (66%) of patients and non-users were 10,991 (13%). Regular use of beta blockers has been gradually increased from 57% in 2005 to 69% in 2014. During the follow-up, most commonly prescribed agent was carvedilol (45%), followed by bisoprolol (24%).
Table 1

Trends in the use of beta-blockers during hospitalization in patients with AMI underwent coronary stent insertion

kcj-50-499-i001
User types Overall 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
User 63,885 (78.14) 4,158 (69.65) 5,437 (71.56) 5,790 (74.59) 5,950 (77.62) 6,531 (81.66) 6,898 (85.6) 6,258 (78.18) 7,064 (81.06) 7,619 (80.17) 8,180 (78.07)
Non-user 17,867 (21.86) 1,812 (30.35) 2,161 (28.44) 1,972 (25.41) 1,716 (22.38) 1,467 (18.34) 1,160 (14.4) 1,747 (21.82) 1,650 (18.94) 1,884 (19.83) 2,298 (21.93)
Overall patients 81,752 5,970 7,598 7,762 7,666 7,998 8,058 8,005 8,714 9,503 10,478
Values are presented as number of patients (%).
AMI = acute myocardial infarction.
Table 2

Prescription pattern of beta-blockers in patients with AMI underwent coronary stent implantation

kcj-50-499-i002
User types Overall 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Regular user 53,991 (66.04) 3,398 (56.92) 4,447 (58.53) 4,846 (62.43) 4,938 (64.41) 5,313 (66.43) 5,625 (69.81) 5,539 (69.19) 6,180 (70.92) 6,523 (68.64) 7,182 (68.54)
Irregular user 16,770 (20.51) 1,329 (22.26) 1,689 (22.23) 1,634 (21.05) 1,577 (20.57) 1,706 (21.33) 1,642 (20.38) 1,597 (19.95) 1,674 (19.21) 1,952 (20.54) 1,970 (18.8)
Non-user 10,991 (13.44) 1,243 (20.82) 1,462 (19.24) 1,282 (16.52) 1,151 (15.01) 979 (12.24) 791 (9.82) 869 (10.86) 860 (9.87) 1,028 (10.82) 1,326 (12.66)
Values are presented as number of patients (%).
AMI = acute myocardial infarction.

Baseline characteristics

Overall, mean age was 60 years old and male was 76%. (Table 3) The second-generation drug eluting stent was deployed in 66% and bare metal stent was used in 4.4%. Single stent was implanted in 83% of patients. Prescription rate was 91% of dual antiplatelet therapy, 78% of ARB or ACE inhibitors and 82% of statin at discharge. Compared with no use of beta blockers, regular users were younger, treated more frequently with the second-generation drug eluting stent, had more hypertension and less diabetes mellitus and were prescribed less dual antiplatelet therapy, more ARBs or ACE inhibitors and statin, less spironolactone at discharge. During follow up, regular users were also prescribed more ARBs or ACE inhibitors, but less dual antiplatelet therapy and similar spironolactone.
Table 3

Baseline characteristics according to pattern of beta blocker use

kcj-50-499-i003
Baseline characteristics Regular user (n=53,991) Irregular user (n=16,770) Non-user (n=10,991) p (all 3) p (1 vs.2) p (2 vs.3) p (1 vs.3)
Age (year) 60 (51–69) 61 (51–71) 62 (52–71) - - - -
Male 41,426 (76.73) 12,477 (74.40) 8,243 (75.00) <0.0001 <0.0001 0.2635 <0.0001
Study enrollment <0.0001 <0.0001 <0.0001 <0.0001
2005–2008 17,629 (32.65) 6,229 (37.14) 5,138 (46.75)
2009–2011 16,477 (30.52) 4,945 (29.49) 2,639 (24.01)
2012–2014 19,885 (36.83) 5,596 (33.37) 3,214 (29.24)
Underlying medical condition
Hypertension 26,685 (49.42) 7,944 (47.37) 5,135 (46.72) <0.0001 <0.0001 0.2885 <0.0001
DM 14,656 (27.15) 4,708 (28.07) 3,090 (28.11) 0.0164 0.0185 0.9422 0.0377
Dyslipidemia 14,653 (27.14) 4,494 (26.8) 3,094 (28.15) 0.0392 0.3841 0.0134 0.0302
Previous stroke, all type 3,968 (7.35) 1,564 (9.33) 1,024 (9.32) <0.0001 <0.0001 0.9788 <0.0001
Previous MI 1,728 (3.20) 705 (4.20) 526 (4.79) <0.0001 <0.0001 0.0213 <0.0001
CHF 2,340 (4.33) 912 (5.44) 563 (5.12) <0.0001 <0.0001 0.2511 0.0003
History of malignancy 1,363 (2.52) 518 (3.09) 317 (2.88) 0.0002 <0.0001 0.3289 0.0303
Charlson comorbidity score 1 (0–2) 1 (0–2) 1 (0–2) <0.0001 <0.0001 0.0265 0.0005
≤1 36,729 (68.03) 11,030 (65.77) 7,287 (66.30)
2–3 10,364 (19.20) 3,245 (19.35) 2,149 (19.55)
4–5 4,821 (8.93) 1,640 (9.78) 1,082 (9.84)
≥6 2,077 (3.85) 855 (5.10) 473 (4.30)
Type of stent <0.0001 <0.0001 <0.0001 <0.0001
BMS 2,262 (4.19) 766 (4.57) 592 (5.39)
1st generation DES 14,902 (27.60) 5,262 (31.38) 4,044 (36.79)
2nd generation DES 36,827 (68.21) 10,742 (64.05) 6,355 (57.82)
Number of stents 0.0288 0.0047 0.1918 0.7611
1 4,4670 (82.74) 13,922 (83.02) 9,088 (82.69)
2 6,096 (11.29) 1,770 (10.55) 1,228 (11.17)
≥3 3,225 (5.97) 1,078 (6.43) 675 (6.14)
In-hospital medication
Dual antiplatelet agent 48,896 (90.56) 15,261 (91.00) 10,044 (91.38) 0.0125 0.0881 0.2729 0.0069
RAAS blocker 43,658 (80.86) 12,835 (76.54) 7,149 (65.04) <0.0001 <0.0001 <0.0001 <0.0001
Beta-blocker 48,524 (89.87) 12,850 (76.62) 2,511 (22.85) <0.0001 <0.0001 <0.0001 <0.0001
CCB 2,021 (3.74) 786 (4.69) 630 (5.73) <0.0001 <0.0001 0.0001 <0.0001
Statin 44,834 (83.04) 1,692 (81.65) 8,733 (79.46) <0.0001 <0.0001 <0.0001 <0.0001
High intensity statin 14,755 (27.33) 4,125 (24.60) 2,073 (18.86) <0.0001 <0.0001 <0.0001 <0.0001
Thiazide 1,510 (2.80) 600 (3.58) 402 (3.66) <0.0001 <0.0001 0.7276 <0.0001
Loop diuretics 7,963 (14.75) 3,010 (17.95) 2,033 (18.50) <0.0001 <0.0001 0.2466 <0.0001
Spironolactone 5,683 (10.53) 2,085 (12.43) 1,272 (11.57) <0.0001 <0.0001 0.0316 0.0012
Vasodilators 27,255 (50.48) 8,619 (51.40) 5,935 (54.00) <0.0001 0.0385 <0.0001 <0.0001
Vasopressor 9,322 (17.27) 3,129 (18.66) 2,335 (21.24) <0.0001 <0.0001 <0.0001 <0.0001
Followed medication
Dual antiplatelet agent 31,584 (58.50) 8,369 (49.90) 6,745 (61.37) <0.0001 <0.0001 <0.0001 <0.0001
Aspirin users 15,556 (28.81) 4,276 (25.50) 2,693 (24.50)
Clopidogrel users 6,363 (11.79) 1,760 (10.49) 1,008 (9.17)
No antiplatelet agents 488 (0.90) 2,365 (14.10) 545 (4.96)
RAAS blocker 39,369 (72.92) 6,784 (40.45) 6,089 (55.40) <0.0001 <0.0001 <0.0001 <0.0001
CCB 4,192 (7.76) 967 (5.77) 1,026 (9.33) <0.0001 <0.0001 <0.0001 <0.0001
Statin 46,501 (86.13) 8,948 (53.36) 7,991 (72.70) <0.0001 <0.0001 <0.0001 <0.0001
High intensity statin 11,962 (22.16) 3,329 (19.85) 1,541 (14.02) <0.0001 <0.0001 <0.0001 <0.0001
Thiazide 2,580 (4.78) 498 (2.97) 569 (5.18) <0.0001 <0.0001 <0.0001 0.0762
Loop diuretics 5,535 (10.25) 1,287 (7.67) 1,195 (10.87) <0.0001 <0.0001 <0.0001 0.0515
Spironolactone 3,014 (5.58) 571 (3.40) 612 (5.57) <0.0001 <0.0001 <0.0001 0.9528
Vasodilators 18,320 (33.93) 3,999 (23.85) 4,088 (37.19) <0.0001 <0.0001 <0.0001 <0.0001
Number of antihypertensives 1.85±0.59 0.49±0.62 0.70±0.67 <0.0001 <0.0001 <0.0001 <0.0001
Number of antihypertensives 2 (2–2) 0 (0–1) 1 (0–1) - - - -
Values are expressed as median (interquartile range), number (%), or mean±standard deviation.
BMS = bare metal stent; CCB = calcium channel blocker; CHF = congestive heart failure; DES = drug-eluting stent; DM = diabetes mellitus; MI = myocardial infarction; RAAS = Renin-angiotensin-aldosterone system.

Clinical outcomes

A total of 10,624 patients at each group were matched on the basis of propensity score (Table 4). The baseline characteristics after matching were well balanced. In multivariate regression analysis, age, sex, underlying disease, type of stents, and medications were independent predictors (Table 5). In the matched population, regular beta blocker use was associated with a 29% reduced risk of composite adverse events (all death, MI or stroke) (hazard ratio [HR], 0.717; 95% confidence interval [CI], 0.650–0.791; p<0.001; Table 6). Compared to no use of beta blocker, regular use significantly reduced all death (HR, 0.622; 95% CI, 0.543–0.714; p<0.001) and MI (HR, 0.705; 95% CI, 0.059–0.842; p=0.001), but did not reduce stroke (HR, 1.05; 95% CI, 0.847–1.303; p=0.654).
Table 4

Baseline characteristics before and after propensity score matching

kcj-50-499-i004
Risk factors Before matching (n=64,982) After matching (n=21,248)
Regular user (n=53,991) Non-user (n=10,991) SD p Regular user (n=10,624) Non-user (n=10,624) SD p
Followed duration (month) 24.33 (21.43–24.33) 24.33 (18.03–24.33) 0.14 - 24.33 (21.53–24.33) 24.33 (18.07–24.33) 0.11 -
Age (year) 60 (51–69) 62 (52–71) −0.15 - 62 (52–71) 61 (52–71) −0.01 -
Male 41,426 (76.73) 8,243 (75.00) 0.03 <0.0001 7,988 (75.19) 7,991 (75.22) 0.00 <0.0001
Study enrollment <0.0001 0.8109
2005–2008 17,629 (32.65) 5,138 (46.75) −0.24 4,886 (45.99) 4,930 (46.40) −0.01
2009–2011 16,477 (30.52) 2,639 (24.01) 0.12 2,589 (24.37) 2,557 (24.07) 0.01
2012–2014 19,885 (36.83) 3,214 (29.24) 0.13 3,149 (29.64) 3,137 (29.53) 0.00
Underlying medical condition
Hypertension 26,685 (49.42) 5,135 (46.72) 0.04 <0.0001 5,058 (47.61) 4,989 (46.96) 0.01 <0.0001
DM 14,656 (27.15) 3,090 (28.11) −0.02 0.0377 2,993 (28.17) 2,975 (28.00) 0.00 <0.0001
Dyslipidemia 14,653 (27.14) 3,094 (28.15) −0.02 0.0302 3,041 (28.62) 3,006 (28.29) 0.01 <0.0001
Previous stroke, all type 3,968 (7.35) 1,024 (9.32) −0.06 <0.0001 993 (9.35) 969 (9.12) 0.02 <0.0001
CHF 1,728 (3.20) 526 (4.79) −0.07 <0.0001 505 (4.75) 493 (4.64) 0.02 <0.0001
ESRD 2,340 (4.33) 563 (5.12) −0.03 0.0003 532 (5.01) 538 (5.06) −0.01 <0.0001
History of malignancy 1,363 (2.52) 317 (2.88) −0.02 0.0303 312 (2.94) 304 (2.86) 0.02 <0.0001
Charlson comorbidity score 1 (0–2) 1 (0–2) −0.04 - 1 (0–2) 1 (0–2) 0.01 -
≤1 36,729 (68.03) 7,287 (66.3) 0.03 0.0005 7,006 (65.95) 7,054 (66.40) −0.01 0.8917
2–3 10,364 (19.20) 2,149 (19.55) −0.01 2,091 (19.68) 2,078 (19.56) 0.00
4–5 4,821 (8.93) 1,082 (9.84) −0.03 1,068 (10.05) 1,041 (9.80) 0.01
≥6 2,077 (3.85) 473 (4.30) −0.02 459 (4.32) 451 (4.25) 0.00
Type of stent <0.0001 0.1590
BMS 2,262 (4.19) 592 (5.39) −0.05 514 (4.84) 573 (5.39) −0.02
1st generation DES 14,902 (27.60) 4,044 (36.79) −0.16 3,948 (37.16) 3,887 (36.59) 0.01
2nd generation DES 36,827 (68.21) 6,355 (57.82) 0.18 6,162 (58.00) 6,164 (58.02) 0.00
Number of stents 0.7611 0.4762
1 44,670 (82.74) 9,088 (82.69) 0.00 8,736 (82.23) 8,786 (82.70) −0.01
2 6,096 (11.29) 1,228 (11.17) 0.00 1,196 (11.26) 1,188 (11.18) 0.00
≥3 3,225 (5.97) 675 (6.14) −0.01 692 (6.51) 650 (6.12) 0.01
Followed medication
Dual antiplatelet agent 31,584 (58.50) 6,745 (61.37) −0.05 <0.0001 6,686 (62.93) 6,725 (63.30) −0.01 0.0001
Aspirin users 15,556 (28.81) 2,693 (24.50) 0.08 2,653 (24.97) 2,690 (25.32) −0.01
Clopidogrel users 6,363 (11.79) 1,008 (9.17) 0.07 983 (9.25) 1,007 (9.48) −0.01
No antiplatelet agents 488 (0.90) 545 (4.96) −0.23 302 (2.84) 202 (1.90) 0.05
RAAS blocker 39,369 (72.92) 6,089 (55.40) 0.31 <0.0001 6,163 (58.01) 6,082 (57.25) 0.01 <0.0001
CCB 4,192 (7.76) 1,026 (9.33) −0.05 <0.0001 1,024 (9.64) 1,015 (9.55) 0.01 <0.0001
Statin 46,501 (86.13) 7,991 (72.70) 0.29 <0.0001 8,061 (75.88) 7,979 (75.10) 0.01 <0.0001
High intensity statin 11,962 (22.16) 1,541 (14.02) 0.17 <0.0001 1,505 (14.17) 1,521 (14.32) −0.01 <0.0001
Thiazide 2,580 (4.78) 569 (5.18) −0.02 0.0762 598 (5.63) 561 (5.28) 0.05 <0.0001
Loop diuretics 5,535 (10.25) 1,195 (10.87) −0.02 0.0515 1,232 (11.60) 1,184 (11.14) 0.03 <0.0001
Spironolactone 3,014 (5.58) 612 (5.57) 0.00 0.9528 609 (5.73) 604 (5.69) 0.01 <0.0001
Vasodilators 18,320 (33.93) 4,088 (37.19) −0.06 <0.0001 4,069 (38.30) 4,035 (37.98) 0.01 <0.0001
Values are expressed as median (interquartile range) or number (%).
BMS = bare metal stent; CCB = calcium channel blocker; CHF = congestive heart failure; DES = drug-eluting stent; DM = diabetes mellitus; ESRD = end-stage renal disease; RAAS = Renin-angiotensin-aldosterone system; SD = standard deviation.
Table 5

Univariate and multivariate predictors of composite outcomes (all-cause mortality, MI or stroke) after coronary stenting in MI

kcj-50-499-i005
Risk factors Univariate Multivariate
HR 95% CI p HR 95% CI p
Age 1.057 1.055–1.059 <0.0001 1.045 1.042–1.047 <0.0001
Male 0.580 0.549–0.612 <0.0001 1.168 1.099–1.241 <0.0001
Study enrollment
2005–2008 1 - - 1 - -
2009–2011 0.845 0.794–0.901 <0.0001 1.155 1.063–1.254 0.0006
2012–2014 0.746 0.700–0.794 <0.0001 1.050 0.955–1.153 0.3122
Underlying medical condition
Hypertension 1.987 1.881–2.099 <0.0001 1.167 1.095–1.245 <0.0001
DM 1.867 1.770–1.969 <0.0001 1.215 1.131–1.304 <0.0001
Dyslipidemia 1.239 1.171–1.311 <0.0001 0.895 0.840–0.952 0.0005
Previous stroke, all type 2.956 2.767–3.158 <0.0001 1.498 1.388–1.616 <0.0001
Previous MI 2.239 2.027–2.473 <0.0001 1.246 1.124–1.380 <0.0001
CHF 2.761 2.542–2.999 <0.0001 1.327 1.212–1.453 <0.0001
History of malignancy 2.190 1.952–2.457 <0.0001 1.293 1.133–1.476 0.0001
Charlson comorbidity score 1.214 1.202–1.227 <0.0001 1.038 0.994–1.083 0.0905
≤1 1 - - 1 - -
2–3 1.663 1.557–1.776 <0.0001 1.065 0.957–1.185 0.2465
4–5 2.435 2.259–2.625 <0.0001 1.115 0.935–1.330 0.2252
≥6 3.565 3.260–3.899 <0.0001 1.191 0.894–1.589 0.2327
Type of stent
BMS 1 - - 1 - -
1st generation DES 0.853 0.760–0.956 0.0063 0.824 0.731–0.928 0.0014
2nd generation DES 0.624 0.558–0.697 <0.0001 0.634 0.563–0.715 <0.0001
Number of stents
1 1 - - 1 - -
2 1.047 0.964–1.138 0.2731 0.913 0.840–0.992 0.0323
≥3 1.187 1.072–1.314 0.0010 0.925 0.828–1.034 0.1698
Followed medication
Dual antiplatelet agent 3.949 3.622–4.306 <0.0001 3.657 3.352–3.99 <0.0001
Aspirin users 1 - - 1 - -
Clopidogrel users 1.284 1.118–1.474 0.0004 1.155 1.005–1.327 0.0418
No antiplatelet agents 6.430 5.715–7.233 <0.0001 2.847 2.513–3.224 <0.0001
RAAS blocker 0.561 0.532–0.591 <0.0001 0.733 0.692–0.777 <0.0001
CCB 0.789 0.708–0.879 <0.0001 0.693 0.621–0.774 <0.0001
Statin 0.360 0.341–0.379 <0.0001 0.502 0.473–0.534 <0.0001
High intensity statin 0.799 0.745–0.857 <0.0001 1.187 1.102–1.278 <0.0001
Thiazide 0.907 0.795–1.035 0.1458 0.826 0.722–0.944 0.0051
Loop diuretics 2.294 2.146–2.452 <0.0001 1.349 1.250–1.457 <0.0001
Spironolactone 1.948 1.778–2.135 <0.0001 1.278 1.154–1.416 <0.0001
Vasodilators 1.076 1.018–1.138 0.0096 1.009 0.953–1.069 0.7480
Regular user 1 - - 1 - -
Irregular user 1.983 1.867–2.105 <0.0001 1.316 1.230–1.407 <0.0001
No user 1.853 1.726–1.990 <0.0001 1.380 1.282–1.485 <0.0001
BMS = bare metal stent; CI = confidence interval; CCB = calcium channel blocker; CHF = congestive heart failure; DES = drug-eluting stent; DM = diabetes mellitus; ESRD = end-stage renal disease; HR = hazard ratio; MI = myocardial infarction; RAAS = Renin-angiotensin-aldosterone system; SD = standard deviation.
Table 6

Outcomes after matching

kcj-50-499-i006
Patterns of beta blocking Regular user Non-user HR of regular user 95% CI p
Patients-year Number of events 2-year predicted event rate Patients-year Number of events 2-year predicted event rate
All death 1,873.32 345 3.70 2,952.40 525 5.53 0.825 0.720–0.946 0.0060
Followed MI 1,151.14 212 2.22 1,608.35 286 3.02 0.900 0.836–0.969 0.0052
Followed stroke 955.67 176 1.88 894.15 159 1.72 0.903 0.839–0.972 0.0068
Composite of MI or stroke 2,095.95 386 4.04 2,496.88 444 4.67 0.897 0.833–0.966 0.0038
Composite of all death, MI or stroke 3,871.53 713 7.41 5,269.33 937 9.62 0.965 0.926–1.006 0.0938
Revascularization 7,422.70 1,367 13.36 8,261.09 1,469 14.61 0.960 0.921–1.000 0.0508
All re-hospitalization 24,733.27 4,555 46.91 25,396.24 4,516 46.69 0.951 0.913–0.991 0.0173
CI = confidence interval; HR = hazard ratio; MI = myocardial infarction.

DISCUSSION

The present study was designed to evaluate whether regular beta blocker use might be associated with improved clinical outcome compared with no beta blocker use in patients with AMI treated with PCI. In this nationwide ischemic cohort study, regular beta blocker prescription improved 2 years clinical outcomes.
Beta-blocker have been reported to reduce fatal arrhythmia, ischemia or infarct size and mortality including sudden cardiac death in AMI patients, but most studies had performed in the pre reperfusion era.4)9)10111213) Current guidelines differ in their recommendations for the use of beta blocker after AMI. 2014 American Heart Association (AHA)/American College of Cardiology (ACC) guideline for non-ST elevation acute coronary syndrome suggests that beta blocker therapy is recommended in patients with reduced systolic function as class I, level of evidence C and in patients with normal left ventricular (LV) function as class IIa, level of evidence C.14) 2013 AHA/ACC guideline for ST-elevation myocardial infarction (STEMI) suggests that beta blocker should be continued during and after hospitalization for all patients and with no contraindications.15) Similarly, 2017 European Society of Cardiology (ESC) guideline for STEMI suggests that routine oral beta blocker treatment should be considered during and after hospitalization in all patients without contraindications (Class IIa, level of evidence C).16) 2011 AHA/American College of Cardiology Foundation (ACCF) Secondary prevention and risk reduction therapy for patients with coronary and other atherosclerotic vascular disease recommended beyond 3 years of beta blocker therapy in AMI patients with normal LV function.17) There is no randomized controlled trial to show the efficacy of beta blocker in PCI era. Evidence supporting routine beta blocker therapy following by AMI was lacking in reperfusion era. Beta-blockers did not reduce mortality at 1 year after AMI in patients with heart failure or ventricular dysfunction.5) However, only approximate half of enrolled patients underwent coronary intervention and prescription data was based on point at discharge. A recent meta-analysis which included studies since 2000 showed that beta blocker therapy was not associated to reduce mortality following AMI.18) Conversely, from a registry data, beta blocker at discharge significantly reduced all cause death at 1 year after STEMI in patients treated primary PCI.6) The results from previous studies are inconsistent. Our result of all comer nationwide KNHI database was in line with recommendations from current guidelines for beta blockers therapy in patients with AMI, even after PCI.
Effective duration of beta blocker therapy after AMI has been still unveiled. A single center retrospective study investigated the effect of beta blocker according to the durations of prescription on clinical outcome.19) Beta-blocker therapy after AMI had beneficial effect until 1 years with 29% of mortality reduction, but beta blocker prescription at 1 and 3 years after AMI could not reduce mortality. In addition, 5-year mortality was not significantly decreased in patients who were taking beta blockers at 1 year.20) Most studies had performed based on the information of medication at discharge or small sample size. A few studies tried to provide data of medication at some period point, but not of continued use of the beta blocker. In this study, it is meaningful to compare the patients who were consistently prescribed during follow-up period with patients who never prescribed beta blockers. In contemporary reperfusion era, early revascularization, antiplatelet therapy, ARB or ACE inhibitor, and lipid lowering therapy may likely attenuate the mortality benefit of beta blockers in post AMI. However, this nationwide cohort study showed that beta blocker therapy was associated with mortality reduction at least for 2 years in AMI patients treated with PCI.
A number of limitations must be acknowledged in this study. First of all, there was raised question about the accuracy of the AMI definition using the KCD-10 codes in KNIH claims database. AMI was validated in a previous study with the accuracy of 73%.21) However, we defined AMI as if patients underwent PCI with AMI diagnosis so that the accuracy of diagnosis might be much higher. Diagnosis of AMI was not differentiated into STEMI and non-STEMI due to intrinsic limitation of database. Also, death was defined as the situational status, including hospital death and out of hospital death based on the loss of KNIH qualification. There was a chance of not accurate diagnosis. Uncontrolled covariates may exist. Secondly, this study was not a result of a randomized controlled trial. Consequently, the risk factors not included in the parameters could potentially affect the result. For example, patients who did not receive beta blocker were sicker or at higher risk. Furthermore, we defined regular use as MPR ≥80% but true drug adherence would depend on each patient. There is a possibility to overestimate the effect of beta blocker. Third, we could not adjust several variables, such as LV ejection fraction and time point of primary PCI in patients with STEMI, due to the intrinsic limitation of database. Even though we tried to adjust LV systolic dysfunction using prescription of loop diuretics and spironolactone, the results could be affected by LV function. Despite these limitations, the strength of this study is a large population based all comer dataset to determine the role of beta blocker after PCI in patients with AMI.
In conclusion, use of beta blocker in patients with AMI after PCI was subsequently increased from 2005 to 2014 in Korea. Regular use of beta blocker for 2 years after PCI in AMI patients was associated with improved clinical outcomes compared to no use of beta blocker.

Notes

Funding: This study was supported by a grant from the Korean Society of Cardiology (201605-03) and Severance Hospital (4-2015-0700, 4-2018-0136). We thank you for J. Hwang, who is a professor of division of mathematics and big data science, Daegu University, Gyeongsan, Korea, to support statistical analysis.

Conflict of Interest: The authors have no financial conflicts of interest.

Author Contributions:

  • Conceptualization: Won H, Suh Y, Ko YG, Hong MK.

  • Data curation: Suh Y.

  • Formal analysis: Won H, Hong MK.

  • Funding acquisition: Won H, Hong MK.

  • Investigation: Won H, Suh Y, Kim GS, Hong MK.

  • Methodology: Won H, Suh Y, Kim GS, Ko YG, Hong MK.

  • Project administration: Won H, Hong MK.

  • Resources: Won H, Hong MK.

  • Software: Hong MK.

  • Supervision: Hong MK.

  • Validation: Won H, Suh Y.

  • Writing - original draft: Won H.

  • Writing - review & editing: Won H, Suh Y, Kim GS, Ko YG, Hong MK.

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SUPPLEMENTARY MATERIAL

Supplementary Table 1

Definition of variables (KCD codes)
kcj-50-499-s001.xls
TOOLS
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