Evidence map›Paper›PMID 33424942›Full record

ArticleJournal of geriatric cardiology : JGC2020

Effects of angiotensin-converting enzyme inhibitor and angiotensin II receptor blocker on one-year outcomes of patients with atrial fibrillation: insights from a multicenter registry study in China.

Si-Qi Lyu, Yan-Min Yang, Jun Zhu, Juan Wang, Shuang Wu, Jia-Meng Ren, Han Zhang, Xing-Hui Shao

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of geriatric cardiology : JGC, 2020. 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
0.4field-weighted citation impact, top 31% 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, 4 citations in OpenAlex.

  1. Pooled it
  2. Observational
  3. Review
  4. Review
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

8 authors at 1 institution in 1 country.

Si-Qi LyuEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yan-Min YangEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jun ZhuEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Juan WangEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Shuang WuEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jia-Meng RenEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Han ZhangEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xing-Hui ShaoEmergency and Critical Care Center, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the effect of angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB) therapy on the prognosis of patients with atrial fibrillation (AF).

methodsA total of 1, 991 AF patients from the AF registry were divided into two groups according to whether they were treated with ACEI/ARB at recruitment. Baseline characteristics were carefully collected and analyzed. Logistic regression was utilized to identify the predictors of ACEI/ARB therapy. The primary endpoint was all-cause mortality, while the secondary endpoints included cardiovascular mortality, stroke and major adverse events (MAEs) during the one-year follow-up period. Univariable and multivariable Cox regression were performed to identify the association between ACEI/ARB therapy and the one-year outcomes.

resultsIn total, 759 AF patients (38.1%) were treated with ACEI/ARB. Compared with AF patients without ACEI/ARB therapy, patients treated with ACEI/ARB tended to be older and had a higher rate of permanent AF, hypertension, diabetes mellitus, heart failure (HF), left ventricular ejection fraction (LVEF) < 40%, coronary artery disease (CAD), prior myocardial infarction (MI), left ventricular hypertrophy, tobacco use and concomitant medications (all

conclusionsIn patients with AF, ACEI/ARB was related to significantly reduced one-year all-cause mortality, cardiovascular mortality and MAEs despite the high burden of cardiovascular comorbidities.

Indexed as

Angiotensin-converting enzyme inhibitorAngiotensin II receptor blockerAtrial fibrillationMortality

Identifiers

PMID33424942
PMCPMC7762696
OpenAlexW3120444803

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.