Evidence map›Paper›PMID 39905775›Full record

ArticleESC heart failure2025

Cardiac magnetic resonance left atrioventricular coupling index as a prognostic tool in hypertrophic cardiomyopathy.

Jinyang Wen, Junhao Tu, Xinwei Tao, Yuanyuan Tang, Zhaoxia Yang, Ziyi Pan, Yi Luo, Chunlin Xiang, Dazhong Tang, Lu Huang and 1 more

Abstract read
In one paragraph

Article in ESC heart failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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.

Jinyang WenDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Junhao TuDepartment of Otorhinolaryngology, Head and Neck Surgery, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Xinwei TaoBayer Healthcare, Shanghai, China.
Yuanyuan TangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhaoxia YangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ziyi PanDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yi LuoDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Chunlin XiangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Dazhong TangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lu HuangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Liming XiaDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Funding

National Natural Science Foundation of China 82272109
6 · The paper itself

Abstract

aimsA novel marker left atrioventricular coupling index (LACI) has been proved to be associated with cardiovascular events in patients without history of cardiovascular disease. However, the studies on cardiac magnetic resonance-derived LACI in hypertrophic cardiomyopathy (HCM) patients are limited, and the prognostic value of LACI has still not been studied thoroughly, so we aimed to explore the association between LACI and adverse clinical outcomes in HCM patients.

methodsA total of 206 HCM patients underwent cardiac magnetic resonance examination were retrospectively enrolled. LACI is defined by the ratio between the left atrial (LA) volume and the left ventricular (LV) volume in LV end-diastolic phase. The composite endpoint was categorized into death-related, heart failure-related, and arrhythmia-related events, reflecting mortality risk, heart failure progression, and arrhythmia burden, respectively. Receiver operating characteristics curve analysis was used to determine the optimal cut-off value for LACI to distinguish HCM patients at high risk of adverse clinical outcome. Multivariable Cox regression models were built including significant clinical variables, LA ejection fraction (LAEF), LA volume index (LAVI), late gadolinium enhancement (LGE) extent and LACI. The improvement of discrimination by adding LACI to a clinical model was assessed using C-statistic, net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

resultsThirty-four HCM patients reached the endpoint during a median follow-up time of 60 [interquartile range (50-68)] months. In the multivariate Cox regression analysis, LACI [hazard ratio 1.054, 95% confidence interval (CI): 1.037, 1.071; P < 0.001] was an independent predictor of the composite events after adjustment for age and atrial fibrillation. Then 40.09% was identified as an optimal cut-off for LACI in the risk stratification. Integrating LACI to the clinical model yielded higher C-statistic 0.892 with 95% CI (0.861, 0.922) compared with LA diameter, LAEF, LAVI and LGE extent, providing an improvement in prediction of high-risk patients (NRI = 0.627, 95% CI: 0.112-0.934; IDI = 0.295, 95% CI: 0.016-0.709).

conclusionsLACI is an independent risk factor for clinical adverse outcome and is superior to conventional LA parameters and LGE extent for the identification of high-risk HCM patients.

Indexed as

Cardiomyopathy, HypertrophicHeart AtriaHeart VentriclesMagnetic Resonance Imaging, CineStroke VolumeVentricular Function, LeftAdultAgedFemaleFollow-Up StudiesHumansMaleMiddle AgedPrognosisRetrospective StudiesROC Curvecardiac magnetic resonancehypertrophic cardiomyopathyleft atrioventricular coupling indexprognosis

Identifiers

PMID39905775
PMCPMC12055398

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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.