Evidence map›Paper›PMID 39131881›Full record

ArticleKidney diseases (Basel, Switzerland)2024

Association of Estimated Glomerular Filtration Rate Trajectories with Atrial Fibrillation Risk in Populations with Normal or Mildly Impaired Renal Function.

Chi Wang, Qian Xin, Junjuan Li, Jianli Wang, Siyu Yao, Miao Wang, Maoxiang Zhao, Shuohua Chen, Shouling Wu, Hao Xue

Abstract read
In one paragraph

Article in Kidney diseases (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. 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

10 authors.

Chi WangDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
Qian XinDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
Junjuan LiDepartment of Nephrology, Kailuan General Hospital, Tangshan, China.
Jianli WangDepartment of Rehabilitation, Kailuan General Hospital, Tangshan, China.
Siyu YaoDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
Miao WangDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
Maoxiang ZhaoDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.
Shuohua ChenDepartment of Cardiology, Kailuan General Hospital, Tangshan, China.
Shouling WuDepartment of Cardiology, Kailuan General Hospital, Tangshan, China.
Hao XueDepartment of Cardiology, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The association between the longitudinal patterns of estimated glomerular filtration rate (eGFR) and risk of atrial fibrillation (AF) in populations with normal or mildly impaired renal function is not well characterized. We sought to explore the eGFR trajectories in populations with normal or mildly impaired renal function and their association with AF. Methods: This prospective cohort study included 62,407 participants who were free of AF, cardiovascular diseases, and moderate to severe renal insufficiency (eGFR <60 mL/min/1.73 m Results: According to survey results for the range and changing pattern of eGFR during 2006-2010, four trajectories were identified: high-stable (range, 107.47-110.25 mL/min/1.73 m Conclusion: The trajectories of eGFR were associated with subsequent AF risk in populations with normal or mildly impaired renal function.

Indexed as

Atrial fibrillationCohort studyEstimated glomerular filtration rateRisk predictionTrajectory

Identifiers

PMID39131881
PMCPMC11309754

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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.