Evidence map›Paper›PMID 39466555›Full record

Trial reportJournal of general internal medicine2025

Efficacy of the ABC Pathway for Integrated Care Across Phenotypes of Patients with Atrial Fibrillation: A Latent-Class Analysis Report from the mAFA-II Clinical Trial.

Bernadette Corica, Giulio Francesco Romiti, Davide Antonio Mei, Marco Proietti, Hui Zhang, Yutao Guo, Gregory Y H Lip, mAF-App II trial investigators

Abstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

8 citing papers in PubMed.

  1. Trial
  2. Association between comorbidity burden and outcomes of catheter ablation vs. medical therapy for atrial fibrillation: insights from the CABANA trial.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025
    Trial
  3. Observational
  4. Article
  5. Review
  6. Observational
  7. Article
  8. Observational
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.

Bernadette CoricaLiverpool Centre for Cardiovascular Sciences at University of Liverpool, Liverpool John Moores University of Liverpool Heart & Chest Hospital, Liverpool, UK.ORCID 0000-0001-9460-4435
Giulio Francesco RomitiLiverpool Centre for Cardiovascular Sciences at University of Liverpool, Liverpool John Moores University of Liverpool Heart & Chest Hospital, Liverpool, UK.
Davide Antonio MeiLiverpool Centre for Cardiovascular Sciences at University of Liverpool, Liverpool John Moores University of Liverpool Heart & Chest Hospital, Liverpool, UK.
Marco ProiettiDepartment of Clinical Sciences and Community Health, University of Milan, Milan, Italy.
Hui ZhangDepartment of Pulmonary Vessel and Thrombotic Disease, Medical School of Chinese PLA, Chinese PLA General Hospital, Beijing, China.
Yutao GuoLiverpool Centre for Cardiovascular Sciences at University of Liverpool, Liverpool John Moores University of Liverpool Heart & Chest Hospital, Liverpool, UK.
Gregory Y H LipLiverpool Centre for Cardiovascular Sciences at University of Liverpool, Liverpool John Moores University of Liverpool Heart & Chest Hospital, Liverpool, UK. gregory.lip@liverpool.ac.uk.
mAF-App II trial investigators

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 82170309
6 · The paper itself

Abstract

backgroundThe mAFA-II cluster randomised trial demonstrated the efficacy of a mobile health-technology implemented 'Atrial fibrillation Better Care' (ABC) pathway (mAFA intervention) for integrated care management of patients with AF.

objectiveTo evaluate the effect of mAFA intervention across phenotypes of patients with AF.

designWe conducted a latent-class analysis (LCA) according to eight variables, including age and comorbidities.

participantsThe mAFA-II trial enrolled AF patients between June 2018 and August 2019 across 40 centres in China. MAIN MEASURES: We evaluated the interaction between the groups identified through LCA, and the effect of mAFA intervention on the risk of the primary composite outcome of all-cause death, stroke/thromboembolism, and rehospitalisations. Results were expressed as adjusted hazard ratio (aHR) and 95% confidence intervals (95% CI). KEY

resultsAcross the 3324 patients included in the trial (mean age 68.5 ± 13.9 years, 38.0% females), we identified three phenotypes: (i) low morbidity phenotype (n = 1234, 37.1%), (ii) hypertensive/coronary artery disease (CAD) phenotype (n = 1534, 46.2%), and (iii) mixed morbidity phenotype (n = 556, 16.7%). The effect of mAFA intervention on the primary outcome appeared greater in the low morbidity phenotype (aHR, 0.08; 95% CI 0.02-0.33) compared to the hypertensive/CAD (aHR, 0.30; 95% CI 0.16-0.58) and the mixed morbidity phenotype (aHR, 0.68; 95% CI 0.37-1.24), with a statistically significant interaction (p

conclusionsIn patients with AF, the ABC pathway improved prognosis across different comorbidity phenotypes, although with some differences in the magnitude of risk reduction. Patients with more complex phenotypes require further efforts to improve their outcomes, considering their high baseline risk of adverse events.

trial registrationWHO International Clinical Trials Registry Platform (ICTRP) Registration number: ChiCTR-OOC-17014138.

Indexed as

Atrial FibrillationDelivery of Health Care, IntegratedAgedChinaFemaleHumansLatent Class AnalysisMaleMiddle AgedPhenotypeTelemedicineatrial fibrillationintegrated carelatent class analysisprognosis

Identifiers

PMID39466555
PMCPMC12045915

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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.