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Record W4408391385 · doi:10.1016/j.cjcpc.2025.03.002

Diastolic Function and Left Atrial Mechanics in Children With Marfan and Loeys-Dietz Syndrome

2025· article· en· W4408391385 on OpenAlexaff
Nairy Khodabakhshian, Alison J Howell, Wei Hui, Luc Mertens, Vitor Guerra

Bibliographic record

VenueCJC Pediatric and Congenital Heart Disease · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMarfan syndromeDiastolic functionCardiologyInternal medicineMedicineDiastoleBlood pressure

Abstract

fetched live from OpenAlex

Background: Diastolic function in patients with pediatric Marfan syndrome (MFS) and Loeys-Dietz syndrome (LDS) remains underexplored. Conventional diastolic assessments in this population can be challenging, and speckle-tracking echocardiography (STE)-derived left atrial (LA) strain measurements offer a novel and sensitive approach. Methods: This retrospective, observational study included 37 patients with MFS, 37 patients with LDS, and 30 age-matched controls. Comprehensive echocardiographic evaluations were performed to assess diastolic function. STE-based LA strain measurements during the reservoir, conduit, and pump phases were obtained and analyzed. Results: = 0.004). LA pump strain remained similar between groups. In addition, conventional diastolic parameters differed significantly between MFS, LDS, and controls. Conclusions: Pediatric patients with MFS and LDS exhibit lower LA reservoir and conduit strains, along with differences in early diastolic parameters, while maintaining preserved LA pump function. These findings suggest subclinical changes in early diastolic function. STE-derived LA strain offers a sensitive, noninvasive method for detecting subtle functional impairments that may precede clinical dysfunction, underscoring its diagnostic potential for early monitoring and management of at-risk 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.016
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.233
Teacher spread0.229 · 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 teacher head, 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

Citations1
Published2025
Admission routes1
Has abstractyes

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