Evidence map›Paper›PMID 39421160›Full record

ArticleFrontiers in cardiovascular medicine2024

Association between myocardial layer-specific strain and high 10-year risk of atherosclerotic cardiovascular disease in hypertension-findings from the China-PAR project study.

Jianxiong Chen, Xiaohuan Yang, Xinyi Li, Lin Jin, Lingheng Wu, Mengjiao Zhang, Lianfang Du, Xianghong Luo, Zhaojun Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

9 authors.

Jianxiong Chen *Department of Ultrasound, Mindong Hospital Affiliated to Fujian Medical University, Ningde, Fujian, China.
Xiaohuan Yang *Department of Ultrasound, Shanghai Fourth People's Hospital Affiliated to Tongji University, Shanghai, China.
Xinyi Li *Business School, Hubei University, Wuhan, China.
Lin JinDepartment of Ultrasound, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Lingheng WuDepartment of Ultrasound, Mindong Hospital Affiliated to Fujian Medical University, Ningde, Fujian, China.
Mengjiao ZhangDepartment of Medical Imaging, Weifang Medical University, Weifang, China.
Lianfang DuDepartment of Ultrasound, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Xianghong LuoDepartment of Echocardiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Zhaojun LiDepartment of Ultrasound, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Myocardial layer-specific strain is a sensitive tool for detecting myocardial dysfunction. The objective of this study was to assess changes in the left ventricle (LV) function using myocardial layer-specific strain and its association with 10-year atherosclerotic cardiovascular disease risk (10Y-ASCVDR) in individuals with hypertension (HP). Methods: The parameters of LV structure, including layer-specific global longitudinal strain (GLS Results: The values of GLS Conclusions: In hypertensive patients, myocardial layer-specific strain, especially GLS, sensitively detected LV dysfunction and showed a significant J-shaped relationship with 10Y-ASCVDR. GCS

Indexed as

echocardiographyhypertensionlayer-specific circumferential strainlayer-specific longitudinal straintwo-dimensional speckle-tracking imaging

Identifiers

PMID39421160
PMCPMC11484262

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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.