Literature DB >> 32096355

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

Hoyoun Won1, Yongsung Suh2, Gwang Sil Kim3, Young Guk Ko4,5, Myeong Ki Hong4,6.   

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.
Copyright © 2020. The Korean Society of Cardiology.

Entities:  

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

Year:  2020        PMID: 32096355      PMCID: PMC7234850          DOI: 10.4070/kcj.2019.0231

Source DB:  PubMed          Journal:  Korean Circ J        ISSN: 1738-5520            Impact factor:   3.243


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

User typesOverall2005200620072008200920102011201220132014
User63,885 (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-user17,867 (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 patients81,7525,9707,5987,7627,6667,9988,0588,0058,7149,50310,478

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

User typesOverall2005200620072008200920102011201220132014
Regular user53,991 (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 user16,770 (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-user10,991 (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.

Values are presented as number of patients (%). AMI = acute myocardial infarction. 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

Baseline characteristicsRegular 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)----
Male41,426 (76.73)12,477 (74.40)8,243 (75.00)<0.0001<0.00010.2635<0.0001
Study enrollment<0.0001<0.0001<0.0001<0.0001
2005–200817,629 (32.65)6,229 (37.14)5,138 (46.75)
2009–201116,477 (30.52)4,945 (29.49)2,639 (24.01)
2012–201419,885 (36.83)5,596 (33.37)3,214 (29.24)
Underlying medical condition
Hypertension26,685 (49.42)7,944 (47.37)5,135 (46.72)<0.0001<0.00010.2885<0.0001
DM14,656 (27.15)4,708 (28.07)3,090 (28.11)0.01640.01850.94220.0377
Dyslipidemia14,653 (27.14)4,494 (26.8)3,094 (28.15)0.03920.38410.01340.0302
Previous stroke, all type3,968 (7.35)1,564 (9.33)1,024 (9.32)<0.0001<0.00010.9788<0.0001
Previous MI1,728 (3.20)705 (4.20)526 (4.79)<0.0001<0.00010.0213<0.0001
CHF2,340 (4.33)912 (5.44)563 (5.12)<0.0001<0.00010.25110.0003
History of malignancy1,363 (2.52)518 (3.09)317 (2.88)0.0002<0.00010.32890.0303
Charlson comorbidity score1 (0–2)1 (0–2)1 (0–2)<0.0001<0.00010.02650.0005
≤136,729 (68.03)11,030 (65.77)7,287 (66.30)
2–310,364 (19.20)3,245 (19.35)2,149 (19.55)
4–54,821 (8.93)1,640 (9.78)1,082 (9.84)
≥62,077 (3.85)855 (5.10)473 (4.30)
Type of stent<0.0001<0.0001<0.0001<0.0001
BMS2,262 (4.19)766 (4.57)592 (5.39)
1st generation DES14,902 (27.60)5,262 (31.38)4,044 (36.79)
2nd generation DES36,827 (68.21)10,742 (64.05)6,355 (57.82)
Number of stents0.02880.00470.19180.7611
14,4670 (82.74)13,922 (83.02)9,088 (82.69)
26,096 (11.29)1,770 (10.55)1,228 (11.17)
≥33,225 (5.97)1,078 (6.43)675 (6.14)
In-hospital medication
Dual antiplatelet agent48,896 (90.56)15,261 (91.00)10,044 (91.38)0.01250.08810.27290.0069
RAAS blocker43,658 (80.86)12,835 (76.54)7,149 (65.04)<0.0001<0.0001<0.0001<0.0001
Beta-blocker48,524 (89.87)12,850 (76.62)2,511 (22.85)<0.0001<0.0001<0.0001<0.0001
CCB2,021 (3.74)786 (4.69)630 (5.73)<0.0001<0.00010.0001<0.0001
Statin44,834 (83.04)1,692 (81.65)8,733 (79.46)<0.0001<0.0001<0.0001<0.0001
High intensity statin14,755 (27.33)4,125 (24.60)2,073 (18.86)<0.0001<0.0001<0.0001<0.0001
Thiazide1,510 (2.80)600 (3.58)402 (3.66)<0.0001<0.00010.7276<0.0001
Loop diuretics7,963 (14.75)3,010 (17.95)2,033 (18.50)<0.0001<0.00010.2466<0.0001
Spironolactone5,683 (10.53)2,085 (12.43)1,272 (11.57)<0.0001<0.00010.03160.0012
Vasodilators27,255 (50.48)8,619 (51.40)5,935 (54.00)<0.00010.0385<0.0001<0.0001
Vasopressor9,322 (17.27)3,129 (18.66)2,335 (21.24)<0.0001<0.0001<0.0001<0.0001
Followed medication
Dual antiplatelet agent31,584 (58.50)8,369 (49.90)6,745 (61.37)<0.0001<0.0001<0.0001<0.0001
Aspirin users15,556 (28.81)4,276 (25.50)2,693 (24.50)
Clopidogrel users6,363 (11.79)1,760 (10.49)1,008 (9.17)
No antiplatelet agents488 (0.90)2,365 (14.10)545 (4.96)
RAAS blocker39,369 (72.92)6,784 (40.45)6,089 (55.40)<0.0001<0.0001<0.0001<0.0001
CCB4,192 (7.76)967 (5.77)1,026 (9.33)<0.0001<0.0001<0.0001<0.0001
Statin46,501 (86.13)8,948 (53.36)7,991 (72.70)<0.0001<0.0001<0.0001<0.0001
High intensity statin11,962 (22.16)3,329 (19.85)1,541 (14.02)<0.0001<0.0001<0.0001<0.0001
Thiazide2,580 (4.78)498 (2.97)569 (5.18)<0.0001<0.0001<0.00010.0762
Loop diuretics5,535 (10.25)1,287 (7.67)1,195 (10.87)<0.0001<0.0001<0.00010.0515
Spironolactone3,014 (5.58)571 (3.40)612 (5.57)<0.0001<0.0001<0.00010.9528
Vasodilators18,320 (33.93)3,999 (23.85)4,088 (37.19)<0.0001<0.0001<0.0001<0.0001
Number of antihypertensives1.85±0.590.49±0.620.70±0.67<0.0001<0.0001<0.0001<0.0001
Number of antihypertensives2 (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.

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

Risk factorsBefore matching (n=64,982)After matching (n=21,248)
Regular user (n=53,991)Non-user (n=10,991)SDpRegular user (n=10,624)Non-user (n=10,624)SDp
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-
Male41,426 (76.73)8,243 (75.00)0.03<0.00017,988 (75.19)7,991 (75.22)0.00<0.0001
Study enrollment<0.00010.8109
2005–200817,629 (32.65)5,138 (46.75)−0.244,886 (45.99)4,930 (46.40)−0.01
2009–201116,477 (30.52)2,639 (24.01)0.122,589 (24.37)2,557 (24.07)0.01
2012–201419,885 (36.83)3,214 (29.24)0.133,149 (29.64)3,137 (29.53)0.00
Underlying medical condition
Hypertension26,685 (49.42)5,135 (46.72)0.04<0.00015,058 (47.61)4,989 (46.96)0.01<0.0001
DM14,656 (27.15)3,090 (28.11)−0.020.03772,993 (28.17)2,975 (28.00)0.00<0.0001
Dyslipidemia14,653 (27.14)3,094 (28.15)−0.020.03023,041 (28.62)3,006 (28.29)0.01<0.0001
Previous stroke, all type3,968 (7.35)1,024 (9.32)−0.06<0.0001993 (9.35)969 (9.12)0.02<0.0001
CHF1,728 (3.20)526 (4.79)−0.07<0.0001505 (4.75)493 (4.64)0.02<0.0001
ESRD2,340 (4.33)563 (5.12)−0.030.0003532 (5.01)538 (5.06)−0.01<0.0001
History of malignancy1,363 (2.52)317 (2.88)−0.020.0303312 (2.94)304 (2.86)0.02<0.0001
Charlson comorbidity score1 (0–2)1 (0–2)−0.04-1 (0–2)1 (0–2)0.01-
≤136,729 (68.03)7,287 (66.3)0.030.00057,006 (65.95)7,054 (66.40)−0.010.8917
2–310,364 (19.20)2,149 (19.55)−0.012,091 (19.68)2,078 (19.56)0.00
4–54,821 (8.93)1,082 (9.84)−0.031,068 (10.05)1,041 (9.80)0.01
≥62,077 (3.85)473 (4.30)−0.02459 (4.32)451 (4.25)0.00
Type of stent<0.00010.1590
BMS2,262 (4.19)592 (5.39)−0.05514 (4.84)573 (5.39)−0.02
1st generation DES14,902 (27.60)4,044 (36.79)−0.163,948 (37.16)3,887 (36.59)0.01
2nd generation DES36,827 (68.21)6,355 (57.82)0.186,162 (58.00)6,164 (58.02)0.00
Number of stents0.76110.4762
144,670 (82.74)9,088 (82.69)0.008,736 (82.23)8,786 (82.70)−0.01
26,096 (11.29)1,228 (11.17)0.001,196 (11.26)1,188 (11.18)0.00
≥33,225 (5.97)675 (6.14)−0.01692 (6.51)650 (6.12)0.01
Followed medication
Dual antiplatelet agent31,584 (58.50)6,745 (61.37)−0.05<0.00016,686 (62.93)6,725 (63.30)−0.010.0001
Aspirin users15,556 (28.81)2,693 (24.50)0.082,653 (24.97)2,690 (25.32)−0.01
Clopidogrel users6,363 (11.79)1,008 (9.17)0.07983 (9.25)1,007 (9.48)−0.01
No antiplatelet agents488 (0.90)545 (4.96)−0.23302 (2.84)202 (1.90)0.05
RAAS blocker39,369 (72.92)6,089 (55.40)0.31<0.00016,163 (58.01)6,082 (57.25)0.01<0.0001
CCB4,192 (7.76)1,026 (9.33)−0.05<0.00011,024 (9.64)1,015 (9.55)0.01<0.0001
Statin46,501 (86.13)7,991 (72.70)0.29<0.00018,061 (75.88)7,979 (75.10)0.01<0.0001
High intensity statin11,962 (22.16)1,541 (14.02)0.17<0.00011,505 (14.17)1,521 (14.32)−0.01<0.0001
Thiazide2,580 (4.78)569 (5.18)−0.020.0762598 (5.63)561 (5.28)0.05<0.0001
Loop diuretics5,535 (10.25)1,195 (10.87)−0.020.05151,232 (11.60)1,184 (11.14)0.03<0.0001
Spironolactone3,014 (5.58)612 (5.57)0.000.9528609 (5.73)604 (5.69)0.01<0.0001
Vasodilators18,320 (33.93)4,088 (37.19)−0.06<0.00014,069 (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

Risk factorsUnivariateMultivariate
HR95% CIpHR95% CIp
Age1.0571.055–1.059<0.00011.0451.042–1.047<0.0001
Male0.5800.549–0.612<0.00011.1681.099–1.241<0.0001
Study enrollment
2005–20081--1--
2009–20110.8450.794–0.901<0.00011.1551.063–1.2540.0006
2012–20140.7460.700–0.794<0.00011.0500.955–1.1530.3122
Underlying medical condition
Hypertension1.9871.881–2.099<0.00011.1671.095–1.245<0.0001
DM1.8671.770–1.969<0.00011.2151.131–1.304<0.0001
Dyslipidemia1.2391.171–1.311<0.00010.8950.840–0.9520.0005
Previous stroke, all type2.9562.767–3.158<0.00011.4981.388–1.616<0.0001
Previous MI2.2392.027–2.473<0.00011.2461.124–1.380<0.0001
CHF2.7612.542–2.999<0.00011.3271.212–1.453<0.0001
History of malignancy2.1901.952–2.457<0.00011.2931.133–1.4760.0001
Charlson comorbidity score1.2141.202–1.227<0.00011.0380.994–1.0830.0905
≤11--1--
2–31.6631.557–1.776<0.00011.0650.957–1.1850.2465
4–52.4352.259–2.625<0.00011.1150.935–1.3300.2252
≥63.5653.260–3.899<0.00011.1910.894–1.5890.2327
Type of stent
BMS1--1--
1st generation DES0.8530.760–0.9560.00630.8240.731–0.9280.0014
2nd generation DES0.6240.558–0.697<0.00010.6340.563–0.715<0.0001
Number of stents
11--1--
21.0470.964–1.1380.27310.9130.840–0.9920.0323
≥31.1871.072–1.3140.00100.9250.828–1.0340.1698
Followed medication
Dual antiplatelet agent3.9493.622–4.306<0.00013.6573.352–3.99<0.0001
Aspirin users1--1--
Clopidogrel users1.2841.118–1.4740.00041.1551.005–1.3270.0418
No antiplatelet agents6.4305.715–7.233<0.00012.8472.513–3.224<0.0001
RAAS blocker0.5610.532–0.591<0.00010.7330.692–0.777<0.0001
CCB0.7890.708–0.879<0.00010.6930.621–0.774<0.0001
Statin0.3600.341–0.379<0.00010.5020.473–0.534<0.0001
High intensity statin0.7990.745–0.857<0.00011.1871.102–1.278<0.0001
Thiazide0.9070.795–1.0350.14580.8260.722–0.9440.0051
Loop diuretics2.2942.146–2.452<0.00011.3491.250–1.457<0.0001
Spironolactone1.9481.778–2.135<0.00011.2781.154–1.416<0.0001
Vasodilators1.0761.018–1.1380.00961.0090.953–1.0690.7480
Regular user1--1--
Irregular user1.9831.867–2.105<0.00011.3161.230–1.407<0.0001
No user1.8531.726–1.990<0.00011.3801.282–1.485<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

Patterns of beta blockingRegular userNon-userHR of regular user95% CIp
Patients-yearNumber of events2-year predicted event ratePatients-yearNumber of events2-year predicted event rate
All death1,873.323453.702,952.405255.530.8250.720–0.9460.0060
Followed MI1,151.142122.221,608.352863.020.9000.836–0.9690.0052
Followed stroke955.671761.88894.151591.720.9030.839–0.9720.0068
Composite of MI or stroke2,095.953864.042,496.884444.670.8970.833–0.9660.0038
Composite of all death, MI or stroke3,871.537137.415,269.339379.620.9650.926–1.0060.0938
Revascularization7,422.701,36713.368,261.091,46914.610.9600.921–1.0000.0508
All re-hospitalization24,733.274,55546.9125,396.244,51646.690.9510.913–0.9910.0173

CI = confidence interval; HR = hazard ratio; MI = myocardial infarction.

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. 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. 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.
  21 in total

1.  Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.

Authors:  Hude Quan; Bing Li; Chantal M Couris; Kiyohide Fushimi; Patrick Graham; Phil Hider; Jean-Marie Januel; Vijaya Sundararajan
Journal:  Am J Epidemiol       Date:  2011-02-17       Impact factor: 4.897

2.  2013 ACCF/AHA guideline for the management of ST-elevation myocardial infarction: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines.

Authors:  Patrick T O'Gara; Frederick G Kushner; Deborah D Ascheim; Donald E Casey; Mina K Chung; James A de Lemos; Steven M Ettinger; James C Fang; Francis M Fesmire; Barry A Franklin; Christopher B Granger; Harlan M Krumholz; Jane A Linderbaum; David A Morrow; L Kristin Newby; Joseph P Ornato; Narith Ou; Martha J Radford; Jacqueline E Tamis-Holland; Carl L Tommaso; Cynthia M Tracy; Y Joseph Woo; David X Zhao
Journal:  J Am Coll Cardiol       Date:  2012-12-17       Impact factor: 24.094

3.  Long-term recording of cardiac arrhythmias with an implantable cardiac monitor in patients with reduced ejection fraction after acute myocardial infarction: the Cardiac Arrhythmias and Risk Stratification After Acute Myocardial Infarction (CARISMA) study.

Authors:  Poul Erik Bloch Thomsen; Christian Jons; M J Pekka Raatikainen; Rikke Moerch Joergensen; Juha Hartikainen; Vesa Virtanen; J Boland; Olli Anttonen; Uffe Jakob Gang; Nis Hoest; Lucas V A Boersma; Eivin S Platou; Daniel Becker; Marc D Messier; Heikki V Huikuri
Journal:  Circulation       Date:  2010-09-13       Impact factor: 29.690

4.  Effect of propranolol on myocardial-infarct size in a randomized blinded multicenter trial.

Authors:  R Roberts; C Croft; H K Gold; T D Hartwell; A S Jaffe; J E Muller; S M Mullin; C Parker; E R Passamani; W K Poole
Journal:  N Engl J Med       Date:  1984-07-26       Impact factor: 91.245

5.  Protection by beta-blocking agents against free radical-mediated sarcolemmal lipid peroxidation.

Authors:  I T Mak; W B Weglicki
Journal:  Circ Res       Date:  1988-07       Impact factor: 17.367

6.  Association of beta-blocker therapy at discharge with clinical outcomes in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention.

Authors:  Jeong Hoon Yang; Joo-Yong Hahn; Young Bin Song; Seung-Hyuk Choi; Jin-Ho Choi; Sang Hoon Lee; Joo Han Kim; Young-Keun Ahn; Myung-Ho Jeong; Dong-Joo Choi; Jong Seon Park; Young Jo Kim; Hun Sik Park; Kyoo-Rok Han; Seung Woon Rha; Hyeon-Cheol Gwon
Journal:  JACC Cardiovasc Interv       Date:  2014-06       Impact factor: 11.195

7.  Medication possession ratio: implications of using fixed and variable observation periods in assessing adherence with disease-modifying drugs in patients with multiple sclerosis.

Authors:  Chris M Kozma; Michael Dickson; Amy L Phillips; Dennis M Meletiche
Journal:  Patient Prefer Adherence       Date:  2013-06-12       Impact factor: 2.711

8.  Validity of the diagnosis of acute myocardial infarction in korean national medical health insurance claims data: the korean heart study (1).

Authors:  Heejin Kimm; Ji Eun Yun; Sang-Hak Lee; Yangsoo Jang; Sun Ha Jee
Journal:  Korean Circ J       Date:  2012-01-31       Impact factor: 3.243

9.  Effect of β-Blockers Beyond 3 Years After Acute Myocardial Infarction.

Authors:  Jin Joo Park; Sun-Hwa Kim; Si-Hyuck Kang; Chang-Hwan Yoon; Young-Seok Cho; Tae-Jin Youn; In-Ho Chae; Dong-Ju Choi
Journal:  J Am Heart Assoc       Date:  2018-03-03       Impact factor: 5.501

10.  β-Blockers and Mortality After Acute Myocardial Infarction in Patients Without Heart Failure or Ventricular Dysfunction.

Authors:  Tatendashe B Dondo; Marlous Hall; Robert M West; Tomas Jernberg; Bertil Lindahl; Hector Bueno; Nicolas Danchin; John E Deanfield; Harry Hemingway; Keith A A Fox; Adam D Timmis; Chris P Gale
Journal:  J Am Coll Cardiol       Date:  2017-06-06       Impact factor: 27.203

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Authors:  Ji Woong Roh; Yongcheol Kim
Journal:  Korean Circ J       Date:  2022-05-16       Impact factor: 3.101

Review 2.  Beta-Blocker Use after Discharge in Patients with Acute Myocardial Infarction in the Contemporary Reperfusion Era.

Authors:  Mengjin Hu; Song Hu; Xiaojin Gao; Yuejin Yang
Journal:  Medicina (Kaunas)       Date:  2022-08-30       Impact factor: 2.948

3.  Clinical Impact of Beta-blockers in the Revascularization Era.

Authors:  Soo Jin Kang
Journal:  Korean Circ J       Date:  2020-06       Impact factor: 3.243

4.  Beta blockers versus calcium channel blockers for provocation of vasospastic angina after drug-eluting stent implantation: a multicentre prospective randomised trial.

Authors:  Mitsuaki Sawano; Toshiomi Katsuki; Shun Kohsaka; Takeshi Kitai; Koichi Tamita; Kotaro Obunai; Yukinori Ikegami; Takafumi Yamane; Ikuko Ueda; Ayaka Endo; Yuichiro Maekawa; Akio Kawamura; Keiichi Fukuda
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