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Record W74677082 · doi:10.1186/1532-429x-17-s1-q6

Global diastolic function in endurance athletes: three-dimensional volume tracking of the mitral annulus with cine-CMR

2015· article· en· W74677082 on OpenAlexaff
Vin‐Cent Wu, Sohae Chung, Myra Cocker, Jacqueline Flewitt, Yoko Mikami, James A. White, Matthias G. Friedrich, Leon Axel

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsUniversity of CalgaryMontreal Heart InstituteLibin Cardiovascular Institute of AlbertaUniversity of Ottawa
FundersNational Institutes of Health
KeywordsMedicineMitral annulusAngiologyCardiologyAthletesDiastolic functionInternal medicineDiastolePhysical therapyBlood pressure

Abstract

fetched live from OpenAlex

Background CMR can be used to assess the structure and function of athletes’ hearts. However, diastolic function is not routinely measured with CMR. Mitral annular (MA) motion, commonly assessed by tissue Doppler imaging, is an important element of diastole that may help to distinguish physiological remodeling from pathological processes of the heart. CMR has been shown to play a useful role in evaluating MA motion. This study aims to characterize the global left ventricular diastolic function in endurance athletes by 3D volume tracking of the MA, using conventional cine-CMR images. Methods CMR studies of 24 high-level endurance athletes (age 22 ± 3) were retrospectively selected from a database. Routine CMR studies from 39 patients with normal hearts (age 42 ± 16) and 29 hypertrophic cardiomyopathy (HCM) patients (age 52 ± 17) with normal ejection fractions were included for comparison. Using normalized cross-correlation, feature-tracking of the atrioventricular junctions was performed over the cardiac cycle, in routine long-axis 2-, 3-, and 4-chamber cine-CMR views. This resulted in 6 spatial MA points per cardiac phase, which were interpolated with a spline for 3D MA reconstruction. The 3D volume swept out by the MA was then calculated; the net sweep volume at a given cardiac phase was derived from the sum of the incremental volumes starting from end-diastole.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.001
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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations2
Published2015
Admission routes1
Has abstractyes

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