Evidence map›Paper›PMID 40893503›Full record

ArticleQuantitative imaging in medicine and surgery2025

Evaluation of myocardial structure and function in hypertrophic obstructive cardiomyopathy via cardiovascular magnetic resonance: regional distribution and sex differences.

Yuwei Bao, Peijun Zhao, Lu Huang, Lingping Ran, Dazhong Tang, Xianghu Yan, Liming Xia

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yuwei BaoDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID https://orcid.org/0000-0002-6322-3661
Peijun ZhaoDepartment of Radiology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Lu HuangDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lingping RanDepartment 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.
Xianghu YanDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID https://orcid.org/0000-0002-8670-3537
Liming XiaDepartment of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.ORCID https://orcid.org/0000-0001-8481-3380

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although hypertrophy and fibrosis have been identified as contributors to mechanical dysfunction in patients with hypertrophic cardiomyopathy (HCM), their regional distribution and sex differences remain inadequately characterized in those with hypertrophic obstructive cardiomyopathy (HOCM). This study aimed to evaluate the determinants of myocardial strain deterioration across different regions and sexes of patients with HOCM through use of cardiovascular magnetic resonance feature tracking (CMR-FT) techniques. Methods: This retrospective study included 102 patients with HOCM who underwent 3.0-T CMR. Global (G) and reginal left ventricular (LV) myocardial peak-strain parameters, including global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS), were derived via CMR-FT. Structural metrics including LV wall thickness (WT), hypertrophic distribution, late gadolinium enhancement percentage (LGE%), and extracellular volume fraction (ECV%) were comprehensively assessed. Bivariate correlation and multivariate linear regression analyses were performed to evaluate the independent associations and interaction effects of hypertrophic regions and sex on strain indices. Results: Strain indices exhibited stronger correlations with hypertrophy as compared to fibrosis markers, with correlation coefficients of GLS, GCS, and GRS of -0.72, -0.58, and 0.55, respectively, while mean WT had stronger correlations than did LGE%, at -0.56, -0.55, and 0.51, respectively. Mean WT demonstrated the strongest correlation with GLS, outperforming max WT, hypertrophic segment count, and WT variation. Mean WT emerged as the strongest independent predictor of global strain (GLS: B=0.79; GCS: B=0.54; GRS: B=-1.38; all P values <0.001). ECV% was also independently associated with GLS (B=0.25) and GCS (B=0.16), while WT variation was associated with GCS (B=5.49) (all P values <0.05). Interaction analyses revealed significantly greater strain impairment in female patients and apical regions as WT increased (all P values <0.001). Conclusions: Mean WT emerged as the most robust structural determinant of myocardial strain impairment in patients with HOCM, surpassing other hypertrophic characteristics and fibrosis surrogates. Notably, functional deterioration was most prominent in the apical regions and among female patients. These findings highlight the importance of incorporating sex-specific and region-specific hypertrophic patterns into individualized diagnostic and therapeutic strategies to improve clinical outcomes.

Indexed as

hypertrophic distributionHypertrophic obstructive cardiomyopathy (HOCM)myocardial strainsex differenceswall thickness (WT)

Identifiers

PMID40893503
PMCPMC12397711

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.