Evidence map›Paper›PMID 39364064›Full record

ArticleFrontiers in cardiovascular medicine2024

Influencing factors and predictive model for left atrial appendage emptying velocity in nonvalvular AF patients.

Weibin He, Lei Yin, Qian Liu, Yan Zhang, Yanlei Zhao, Lianxia Wang, Ling You

Abstract read
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 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

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Additional Stroke Risk Factors Beyond the CHAJournal of clinical medicine · 2026
    Article
4 · The record

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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

7 authors.

Weibin HeDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Lei YinDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Qian LiuDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yan ZhangDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yanlei ZhaoDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Lianxia WangDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Ling YouDepartment of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia, significantly increasing the risk of death and stroke. The left atrial appendage (LAA) plays a crucial role in the development of AF. Reduced left atrial appendage emptying velocity (LAAEV) is an important indicator of nonvalvular AF, associated with thrombosis and recurrence after catheter ablation. This study aims to identify factors influencing LAAEV and construct a predictive model for LAAEV in nonvalvular AF patients. Methods: This retrospective cohort study included 1,048 nonvalvular AF patients hospitalized at the Second Hospital of Hebei Medical University from January 1, 2015, to December 31, 2021. Patients underwent transthoracic and transesophageal echocardiography and had complete laboratory data. Statistical analyses included binary logistic regression and multiple linear regression to identify independent predictors of reduced LAAEV and construct a predictive model. Results: Patients were divided into two groups: reduced LAAEV (<40 cm/s) and normal LAAEV (≥40 cm/s). The reduced LAAEV group included 457 patients (43.61%), with significant differences in age, gender, alcohol consumption, heart failure (HF), ischemic stroke, AF type, resting heart rate, CHA2DS2-VASc score, serum creatinine (SCR), serum uric acid (SUA), estimated glomerular filtration rate (eGFR), glycated hemoglobin (HbA1C), β2 macroglobulin (B2M), left atrial diameter (LAD), and left ventricular ejection fraction (LVEF) compared to the normal LAAEV group. Logistic regression analysis identified age (OR 0.974, 95% CI 0.951-0.997, Conclusion: Age, HF, type of AF, LAD, and LVEF are independent predictors of reduced LAAEV. The predictive model (LAAEV = 96.567-15.940 × AFtype-1.309 × LAD-0.18 × Age + 37.069 × LVEF) demonstrates good predictive value, aiding in the initial assessment and management of nonvalvular AF patients.

Indexed as

atrial fibrillationechocardiographyleft atrial appendage emptying velocitypredictive modelretrospective study

Identifiers

PMID39364064
PMCPMC11446783

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