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Record W4415973766 · doi:10.1101/2025.11.04.25339540

Revisiting the concept of “phenotype” in pediatric hypertrophic cardiomyopathy using myocardial stiffness and strain variations assessed by ultrafast ultrasound imaging

2025· preprint· W4415973766 on OpenAlexafffund
Aimen Malik, Maëlys Venet, Seema Mital, Clément Papadacci, Mathieu Pernot, Mark K. Friedberg, Luc Mertens, Jérôme Baranger, Olivier Villemain

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Language
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsHospital for Sick Children
FundersHORIZON EUROPE Framework ProgrammeCanadian Institutes of Health ResearchHospital for Sick ChildrenEuropean Commission
KeywordsHypertrophic cardiomyopathyStrain (injury)DiastoleElastographyCardiomyopathyStiffnessPopulationGenotype

Abstract

fetched live from OpenAlex

ABSTRACT Background Pediatric hypertrophic cardiomyopathy (HCM) is associated with significant morbidity and mortality. While identified as a genetic disease mainly involving sarcomeric genes, the association between genotypical variation and phenotypic expression is not fully established. Developments in Ultrafast ultrasound imaging allows quantifying myocardial stiffness using shear waves elastography (SWE). When combined with strain measurements, myocardial work can be computed, offering new insights into phenotype myocardial properties. Methods An age-matched population of 20 Healthy volunteers (HVs, mean age=11.1 ± 4.5years), 20 HCM (genotype- and phenotype-positive, mean age=11.6 ± 5.3years) and 20 Genotype (genotype-positive, phenotype-negative, mean age=11.1 ± 4.8years) were included in the study. Each participant underwent conventional echocardiography and a full cardiac-cycle exploration of the basal anteroseptal segment consisting of: (1) myocardial stiffness by SWE, (2) segmental strain and thickness, which are used to compute one-beat work, the stress-strain loop area, contributive and dissipative work. Results Mean diastolic myocardial stiffness (DMS) and peak myocardial strain (PMS) distinguished the HCM group (DMS=23.7 ± 8.7kPa; PMS= −6.64 ± 5.9%) from HV group (DMS=7.2 ± 0.7kPa, p<0.01; PMS= −19.9 ±4.1%, p<0.01). No significant differences were observed in DMS and PMS between HVs and Genotype groups. One-beat work and stress-strain loop areas showed significant differences among all 3 groups (p<0.01) and could distinguish the Genotype group (one-beat work= 318.2 ± 100.2µJ/mm; stress-strain loop area=33.2 ± 10.6kPa.%) from HVs (one-beat work= 582.4 ± 137µJ/mm; stress-strain loop area= 66.8 ± 19.8 kPa.%), and the HCM group (one-beat work= 38.2 ± 107.1µJ/mm, stress-strain loop area=5.8 ± 6.5kPa.%), p<0.01. Conclusion Combining Ultrafast ultrasound with speckle-tracking echocardiography, we demonstrate that one-beat work and stress-strain relationship, obtained by combining myocardial stiffness, strain, and thickness have the potential to distinguish genotype-positive, phenotype-negative patients from healthy controls. Clinical outcome studies are needed to determine the prognostic value of these parameters in phenotype-positive HCM patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.273
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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