ArticleInsights into imaging2026
Enhancing risk prediction for sudden cardiac death: quantitative late gadolinium enhancement analysis in hypertrophic cardiomyopathy.
Article in Insights into imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
objectivesTo assess the prognostic value of multiple late gadolinium enhancement (LGE) quantification methods for sudden cardiac death (SCD) prediction in hypertrophic cardiomyopathy (HCM). MATERIALS AND
methodsIn this single-center retrospective study, 617 HCM patients who underwent cardiac magnetic resonance (CMR) examinations were consecutively enrolled. LGE was quantified using the n-standard deviation (SD) technique (with multiple thresholds) and the full width at half maximum method. "Gray zone" was defined as the myocardium with signal intensity between two predefined thresholds on LGE images. The primary outcome was SCD or aborted SCD.
resultsAmong 617 HCM patients, 424 (68.7%) were male, mean age was 49.1 ± 14.0 years, and LGE was identified in 438 (71.0%). During 67.9 ± 21.0 months of follow-up, 24 patients (3.9%) reached the primary endpoint. All dual-threshold gray zone measures and five single-threshold LGE quantifications (2-6 SDs) independently predicted SCD (HR range: 1.031-1.220, all adjusted p < 0.05). Gray zone (HR range: 1.091-1.220) showed stronger associations than single-threshold LGE measures (HR range: 1.031-1.046). Both approaches improved discrimination beyond the composite American Heart Association (AHA)/American College of Cardiology (ACC) model, with increased net reclassification improvement (0.321 and 0.397, respectively) and comparable C-statistics (0.794-0.871 vs 0.794-0.898, p = 0.155).
conclusionWhile conventional single-threshold LGE quantification predicts SCD in HCM, dual-threshold gray-zone analysis demonstrates stronger associations. Both approaches provide incremental prognostic value beyond the AHA/ACC guideline-based risk model. These findings underscore the importance of standardizing LGE quantification to improve SCD risk stratification in patients with HCM. KEY POINTS: Question: The optimal LGE quantification approach for SCD risk stratification in HCM remains uncertain.
findingsBoth single- and dual-threshold LGE quantification independently predict SCD in patients with HCM, while dual-threshold gray zone metrics demonstrate stronger prognostic associations. Critical Relevance: By systematically comparing multiple LGE quantification approaches, this study highlights the impact of methodological variability on SCD risk stratification in HCM, underscores the need for standardized LGE assessment, and informs clinical radiology practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.