Evidence map›Paper›PMID 34811932›Full record

ArticleESC heart failure2022

Long-term impact of β-blocker in elderly patients without myocardial infarction after percutaneous coronary intervention.

Tatsuya Fukase, Tomotaka Dohi, Takuma Koike, Hidetoshi Yasuda, Mitsuhiro Takeuchi, Norihito Takahashi, Yuichi Chikata, Hirohisa Endo, Shinichiro Doi, Hiroki Nishiyama and 6 more

Open access · goldAbstract read
In one paragraph

Article in ESC heart failure, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 29% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 2 institutions in 1 country.

Tatsuya FukaseDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Tomotaka DohiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.ORCID 0000-0002-6646-468X
Takuma KoikeDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hidetoshi YasudaDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Mitsuhiro TakeuchiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Norihito TakahashiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Yuichi ChikataDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hirohisa EndoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Shinichiro DoiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hiroki NishiyamaDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Iwao OkaiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hiroshi IwataDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Shinya OkazakiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Katsumi MiyauchiDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Hiroyuki DaidaDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Tohru MinaminoDepartment of Cardiovascular Biology and Medicine, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
Juntendo University · JPJapan Agency for Medical Research and Development · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsLittle is known about the long-term outcomes of β-blockers use in patients with coronary artery disease (CAD) without myocardial infarction (MI) and reduced ejection fraction (rEF). However, more attention should be paid to the oral administration of β-blockers in elderly patients who are susceptible to heart failure (HF), sinus node dysfunction, or rate response insufficiency. We aimed to evaluate the long-term impact of β-blockers in elderly patients with CAD without MI or systolic HF who have undergone percutaneous coronary intervention. METHODS AND

resultsA total of 1018 consecutive elderly patients with CAD (mean age, 72 ± 7 years; 77% men) who underwent their first intervention between 2010 and 2018 were included in this study. According to the presence or absence of the use of β-blockers, 514 patients (50.5%) were allocated to the β-blocker group, and 504 (49.5%) to the non-β-blocker group. We evaluated the incidence of 4-point major adverse cardiovascular events (4P-MACE), including cardiovascular death, non-fatal MI, non-fatal stroke, admission for HF, target vessel revascularization (TVR), and all-cause death. We focused on the association between chronotropic incompetence of β-blockers and incidence of a new HF and analysed the results using an exercise electrocardiogram regularly performed in the outpatient department after percutaneous coronary intervention. During a median follow-up duration of 5.1 years, 83 patients (8.3%) developed 4P-MACE, including cardiovascular death in 17, non-fatal MI in 13, non-fatal stroke in 25, and admission for HF in 39 patients. Additionally, 124 patients (12.2%) had a TVR and 104 (10.2%) died of other causes. Kaplan-Meier analysis showed that the cumulative incidence rate of 4P-MACE in the β-blocker group was significantly higher than that in the non-β-blocker group (15.4% vs. 10.0%, log-rank test, P = 0.015). Above all, the cumulative incidence rate of admission for HF in the β-blocker group was significantly higher (8.8% vs. 3.2%, log-rank test, P < 0.001). The β-blocker group had significantly lower resting heart rate, stress heart rate, and stress-rest Δ heart rate on exercise electrocardiogram. Multivariate Cox hazard analysis revealed that EF, β-blocker use, stress-rest Δ heart rate, and CKD were strong independent predictors of admission for HF.

conclusionsLong-term β-blocker use was significantly associated with an increased risk of adverse cardiovascular events in elderly patients with CAD without MI or systolic HF. In particular, the chronotropic incompetence action of β-blockers could increase the risk of admission for HF in elderly patients with CAD without MI and systolic HF, and the present findings warrant further investigation.

Indexed as

Coronary Artery DiseaseHeart FailureMyocardial InfarctionPercutaneous Coronary InterventionAdrenergic beta-AntagonistsAgedFemaleHumansMaleAdrenergic beta-AntagonistsCoronary artery diseaseHeart failureLong termPercutaneous coronary interventionβ-Blockers

Identifiers

PMID34811932
PMCPMC8787957
OpenAlexW3215349947

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.