Evidence map›Paper›PMID 33058365›Full record

ArticleJournal of cellular and molecular medicine2020

Shifts in gut microbiome and metabolome are associated with risk of recurrent atrial fibrillation.

Jing Li, Kun Zuo, Jing Zhang, Chaowei Hu, Pan Wang, Jie Jiao, Zheng Liu, Xiandong Yin, Xiaoqing Liu, Kuibao Li and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
4.2field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.

  1. Pooled it
  2. Association of gut microbiome dysbiosis with the progression of atrial fibrillation: A systematic review.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2023
    Pooled it
  3. Correlation Between Dysbiosis and Atrial Fibrillation: What's New?International journal of molecular sciences · 2025
    Review
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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

11 authors at 1 institution in 1 country.

Jing LiHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Kun ZuoHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jing ZhangHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Chaowei HuKey Laboratory of Upper Airway Dysfunction-related Cardiovascular Diseases, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Pan WangHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Jie JiaoHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Zheng LiuHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Xiandong YinHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Xiaoqing LiuHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.
Kuibao Li
Xinchun YangHeart Center & Beijing Key Laboratory of Hypertension, Beijing Chaoyang Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-9813-8347
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alternations of gut microbiota (GM) in atrial fibrillation (AF) with elevated diversity, perturbed composition and function have been described previously. The current work aimed to assess the association of GM composition with AF recurrence (RAF) after ablation based on metagenomic sequencing and metabolomic analyses and to construct a GM-based predictive model for RAF. Compared with non-AF controls (50 individuals), GM composition and metabolomic profile were significantly altered between patients with recurrent AF (17 individuals) and non-RAF group (23 individuals). Notably, discriminative taxa between the non-RAF and RAF groups, including the families Nitrosomonadaceae and Lentisphaeraceae, the genera Marinitoga and Rufibacter and the species Faecalibacterium spCAG:82, Bacillus gobiensis and Desulfobacterales bacterium PC51MH44, were selected to construct a taxonomic scoring system based on LASSO analysis. After incorporating the clinical factors of RAF, taxonomic score retained a significant association with RAF incidence (HR = 2.647, P = .041). An elevated AUC (0.954) and positive NRI (1.5601) for predicting RAF compared with traditional clinical scoring (AUC = 0.6918) were obtained. The GM-based taxonomic scoring system theoretically improves the model performance, and the nomogram and decision curve analysis validated the clinical value of the predicting model. These data provide novel possibility that incorporating the GM factor into future recurrent risk stratification.

Indexed as

Gastrointestinal MicrobiomeGene Expression ProfilingMetabolomeAgedArea Under CurveAtrial FibrillationBacillusFaecalibacteriumFemaleHumansIncidenceKaplan-Meier EstimateMaleMetabolomicsMiddle AgedNitrosomonadaceaeatrial fibrillationgut microbiotametabolismpredictive modelrecurrence

Identifiers

PMID33058365
PMCPMC7701499
OpenAlexW3092678606

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.