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Record W2776409552 · doi:10.3389/fcvm.2017.00082

Echocardiographic Image Quality Deteriorates with Age in Children and Young Adults with Duchenne Muscular Dystrophy

2017· article· en· W2776409552 on OpenAlexafffund
Alyssa Power, Sabrina Poonja, Dal Disler, Kimberley Myers, David J. Patton, Jean K. Mah, Nowell M. Fine, Steven C. Greenway

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsLibin Cardiovascular Institute of AlbertaAlberta Children's HospitalUniversity of Calgary
FundersAlberta Children's Hospital Research InstituteHealth Research Board
KeywordsMedicineDuchenne muscular dystrophyCardiologyCardiomyopathyMagnetic resonance imagingRetrospective cohort studyInternal medicineRadiologyHeart failure

Abstract

fetched live from OpenAlex

Background: Advances in medical care for patients with Duchenne muscular dystrophy (DMD) have resulted in improved survival and an increased prevalence of cardiomyopathy. Serial echocardiographic surveillance is recommended to detect early cardiac dysfunction and initiate medical therapy. Clinical anecdote suggests that echocardiographic quality diminishes over time, impeding accurate assessment of left ventricular systolic function. Furthermore, evidence-based guidelines for the use of cardiac imaging in DMD, including cardiac magnetic resonance imaging, are limited. The objective of our single-centre, retrospective study was to quantify the deterioration in echocardiographic image quality with increasing patient age and identify an age at which cardiac magnetic resonance imaging should be considered. Methods: We retrospectively reviewed and graded the image quality of serial echocardiograms obtained in young patients with DMD. The quality of 16 left ventricular segments in two echocardiographic views was visually graded using a binary scoring system. An endocardial border delineation percentage score was calculated by dividing the number of segments with adequate endocardial delineation in each imaging window by the total number of segments present in that window and multiplying by 100. Linear regression analysis was performed to model the relationship between the endocardial border delineation percentage scores and patient age. Results: Fifty-five echocardiograms from 13 patients (mean age 11.6 years, range 3.6-19.9) were systematically reviewed. By 13 years of age, 50% of the echocardiograms were classified as suboptimal with ≥30% of segments inadequately visualized, and by 15 years of age 78% of studies were suboptimal. Linear regression analysis revealed a negative correlation between patient age and endocardial border delineation percentage score (r = -2.49, 95% confidence intervals -4.73, -0.25; p=0.032), with the score decreasing by 2.5% for each 1 year increase in age. Conclusions: Echocardiographic image quality declines with increasing age in DMD. Alternate imaging modalities may play a role in cases of poor echocardiographic image quality.

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)0.001
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 score0.021
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.216
Teacher spread0.212 · 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

Citations31
Published2017
Admission routes2
Has abstractyes

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