Beta-blockers in post-myocardial infarction with preserved ejection fraction: systematic review and meta-analysis

Abstract

Background: Myocardial infarction (MI) remains one of the main causes of mortality worldwide. Beta-blockers (BBs) are an essential component in the pharmacological treatment for MI. The long-term role of BB in patients with preserved left ventricular ejection fraction (LVEF) is not yet well established. Thus, we performed a systematic review and meta-analysis to synthesize the impact of long-term use of BB on reducing mortality in patients with preserved LVEF after MI.

Methods: This study adhered to the guidelines outlined by the Cochrane Collaboration and the PRISMA statement. The predefined research protocol was registered in PROSPERO under the ID CRD42024554630. A systematic search was conducted in Embase, the Cochrane Central Register of Controlled Trials, and PubMed for studies published in English up to September 1, 2024, using the succeeding medical subject terms: 'myocardial infarction', 'preserved ejection fraction', and 'beta-blockers'. Data were extracted for: (I) death from any cause; (II) death from cardiovascular causes; (III) MI; (IV) stroke; and (V) hospitalization for heart failure (HF). The risk of bias of each article was analyzed using the tool risk of bias in non-randomized studies of interventions (ROBINS-I) and risk-of-bias tool for randomized trials (RoB2). These outcomes were compared using pooled hazard ratios (HRs) to maintain the integrity of time-to-event data from individual studies.

Results: A total of 85,607 patients from 11 studies were included in this meta-analysis, of whom 65,790 (76.8%) were using BBs after MI with preserved ejection fraction. The use of BBs demonstrated a significant reduction in all-cause mortality in the global analysis of the included studies [HR =0.81; 95% confidence interval (CI): 0.67-0.98; P=0.03]. However, when performing sensitivity analyses to assess the impact of methodological biases and the robustness of the results, this reduction was no longer significant (HR =0.79; 95% CI: 0.62-1.02; P=0.07). Regarding reinfarction, there was no difference between BB users and non-users (HR =1.00; 95% CI: 0.92-1.09; P>0.99). Similarly, hospitalization for HF showed no significant variation between groups (HR =1.05; 95% CI: 0.89-1.24; P=0.55). Stroke incidence was also comparable between the groups, though with substantial heterogeneity (I²=60%). Heterogeneity was otherwise low for the outcomes of reinfarction, and hospitalization for HF (I²<25%). Subgroup analyses revealed no differences in outcomes when stratified by age, sex, hypertension, or diabetes.

Conclusions: Long-term BB use in patients with preserved LVEF after MI did not decrease all-cause mortality, cardiovascular mortality, or major adverse cardiac events (MACEs). There was also no identified reduction in hospitalizations for HF, MI, or stroke in the average follow-up of 3 years.

Keywords: Adrenergic beta-antagonists; mortality; myocardial infarction (MI); ventricular function.

Figure 1

PRISMA flowchart.

Figure 2

ROBINS-I of non-randomized studies included in meta-analysis. (A) Summary plot of ROBINS-I. (B) Summary plot of RoB2. RoB2, risk-of-bias tool for randomized trials; ROBINS-I, risk of bias in non-randomized studies of interventions.

Figure 3

ROBINS-I of non randomized studies included in meta-analysis. D1: risk of bias due to confounding; D2: risk of bias in classification of interventions; D3: risk of bias in selection of participants into the study (or into the analysis); D4: risk of bias due to deviations from intended interventions; D5: risk of bias due to missing data; D6: risk of bias arising from measurement of the outcome; D7: risk of bias in selection of the reported result. ROBINS-I, risk of bias in non-randomized studies of interventions.

Figure 4

The risk of bias analysis of the included randomized clinical trial was performed using the RoB2 tool. D1: bias arising from the randomization process; D2: bias due to deviations from intended intervention; D3: bias due to missing outcome data; D4: bias in measurement of the outcome; D5: bias in selection of the reported result. RoB2, risk-of-bias tool for randomized trials.

Figure 5

Forest plot of all-cause mortality. (A) Comparison of all-cause mortality in BB users vs. non-users across all studies. (B) Forest plot of all-cause mortality in BB users vs. non-users, filtered by studies employing PSM methodology to adjust for baseline confounders. (C) Sensitivity analysis excluding studies with a high risk of bias. The HRs with 95% CIs are shown for each study and the overall pooled analysis. Sensitivity analysis excludes studies with high risk of bias. A: risk of bias due to confounding; B: risk of bias arising from measurement of the exposure; C: risk of bias in selections of participants into the study (or into the analysis); D: risk of bias due to post-exposure interventions; E: risk of bias due to missing data; F: risk of bias arising from measure of the outcome; G: risk of bias in selection of the reported result. BB, beta-blocker; CI, confidence interval; HR, hazard ratio; PSM, propensity score matching; SE, standard error.

Figure 6

Forest plot of cardiac mortality. (A) Cardiac mortality in BB users vs. non-users. (B) Subgroup analysis by propensity score matching. (C) Sensitivity analysis with adjusted models. Sensitivity analysis excludes studies with high risk of bias. This figure highlights the heterogeneity (I² values) observed across the included studies. A: risk of bias due to confounding; B: risk of bias arising from measurement of the exposure; C: risk of bias in selections of participants into the study (or into the analysis); D: risk of bias due to post-exposure interventions; E: risk of bias due to missing data; F: risk of bias arising from measure of the outcome; G: risk of bias in selection of the reported result. BB, beta-blocker; CI, confidence interval; HR, hazard ratio; SE, standard error.

Figure 7

Forest plot of MACE. The pooled analysis of MACEs comparing BB users vs. non-users. The analysis includes HRs with 95% CIs for each study and the overall pooled result. The heterogeneity (I²) is indicated for all included studies. BB, beta-blocker; CI, confidence interval; HR, hazard ratio; MACE, major adverse cardiac event; SE, standard error.

Figure 8

Forest plot of reinfarction. (A) Comparison of reinfarction rates in BB users vs. non-users across included studies. (B) Subgroup analysis filtered by studies employing PSM. The figure highlights the effect estimates and heterogeneity between studies. BB, beta-blocker; CI, confidence interval; HR, hazard ratio; PSM, propensity score matching; SE, standard error.

Figure 9

Forest plot of hospitalization for HF. (A) Pooled analysis of hospitalization rates for HF in BB users vs. non-users. (B) Subgroup analysis restricted to studies with matched cohorts. The HRs and corresponding 95% CIs are displayed for each study and overall results. BB, beta-blocker; CI, confidence interval; HF, heart failure; HR, hazard ratio; PSM, propensity score matching; SE, standard error.

Figure 10

Forest plot of stroke incidence. The pooled analysis of stroke incidence in BB users vs. non-users. The analysis highlights significant heterogeneity and includes individual study estimates and the overall pooled effect. BB, beta-blocker; CI, confidence interval; HR, hazard ratio; PSM, propensity score matching; SE, standard error.