Evidence map›Paper›PMID 39100705›Full record

ArticleJACC. Asia2024

Causal Association of Arterial Stiffness With the Risk of Chronic Kidney Disease.

Xue Tian, Shuohua Chen, Xue Xia, Qin Xu, Yijun Zhang, Xiaoli Zhang, Penglian Wang, Shouling Wu, Anxin Wang

Abstract read
In one paragraph

Article in JACC. Asia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Trial
  2. Article
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  5. 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

9 authors.

Xue TianDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Shuohua ChenDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
Xue XiaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Qin XuDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yijun ZhangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xiaoli ZhangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Penglian WangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Shouling WuDepartment of Cardiology, Kailuan Hospital, North China University of Science and Technology, Tangshan, China.
Anxin WangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Previous studies on the direction of the association between arterial stiffness (AS) and chronic kidney disease (CKD) were inconsistent, leaving a knowledge gap in understanding the temporal sequence of the association. Objectives: This study sought to assess the temporal and longitudinal relationship between AS and CKD. Methods: The temporal relationship between AS measured by brachial ankle pulse wave velocity and CKD measured by estimated glomerular filtration rate (eGFR) was analyzed among 7,753 participants with repeated examinations in the Kailuan study using cross-lagged panel analysis. The longitudinal associations of AS status and vascular aging (VA) phenotype with incident CKD were analyzed among 10,535 participants. Results: The adjusted cross-lagged path coefficient ( Conclusions: AS appeared to precede the decrease in eGFR. Additionally, increased AS and early VA were associated with an increased risk of incident CKD.

Indexed as

arterial stiffnesschronic kidney diseasecohort studycross-lagged panel analysisvascular aging

Identifiers

PMID39100705
PMCPMC11291385

What OpenQuestion holds

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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.