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Record W3080149795 · doi:10.1097/rti.0000000000000556

Clinical Significance of Papillary Muscles on Left Ventricular Mass Quantification Using Cardiac Magnetic Resonance Imaging

2020· article· en· W3080149795 on OpenAlex
A. Al-Arnawoot, Ciara O’Brien, Gauri Rani Karur, Elsie T. Nguyen, Syed Wasim, Robert M. Iwanochko, Chantal F. Morel, Kate Hanneman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Thoracic Imaging · 2020
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsUniversity of TorontoUniversity Health NetworkMount Sinai HospitalToronto General Hospital
Fundersnot available
KeywordsMedicineIntraclass correlationCardiologyEjection fractionMagnetic resonance imagingAkaike information criterionInternal medicineCardiac magnetic resonance imagingHeart failureNuclear medicineRadiology

Abstract

fetched live from OpenAlex

PURPOSE: Accurate and reproducible assessment of left ventricular mass (LVM) is important in Fabry disease. However, it is unclear whether papillary muscles should be included in LVM assessed by cardiac magnetic resonance imaging (MRI). The purpose of this study was to evaluate the reproducibility and predictive value of LVM in patients with Fabry disease using different analysis approaches. MATERIALS AND METHODS: A total of 92 patients (44±15 y, 61 women) with confirmed Fabry disease who had undergone cardiac MRI at a single tertiary referral hospital were included in this retrospective study. LVM was assessed at end-diastole using 2 analysis approaches, including and excluding papillary muscles. Adverse cardiac events were assessed as a composite end point, defined as ventricular tachycardia, bradycardia requiring device implantation, severe heart failure, and cardiac death. Statistical analysis included Cox proportional hazard models, Akaike information criterion, intraclass correlation coefficients, and Bland-Altman analysis. RESULTS: Left ventricular end-diastolic volume, end-systolic volume, ejection fraction, and LVM all differed significantly between analysis approaches. LVM was significantly higher when papillary muscles were included versus excluded (157±71 vs. 141±62 g, P<0.001). Mean papillary mass was 16±11 g, accounting for 10%±3% of total LVM. LVM with pap illary muscles excluded had slightly better predictive value for the composite end point compared with LVM with papillary muscles included based on the model goodness-of-fit (Akaike information criterion 140 vs. 142). Interobserver agreement was slightly better for LVM with papillary muscles excluded compared with included (intraclass correlation coefficient 0.993 [95% confidence interval: 0.985, 0.996] vs. 0.989 [95% confidence interval: 0.975, 0.995]) with less bias and narrower limits of agreement. CONCLUSIONS: Inclusion or exclusion of papillary muscles has a significant effect on LVM quantified by cardiac MRI, and therefore, a standardized analysis approach should be used for follow-up. Exclusion of papillary muscles from LVM is a reasonable approach in patients with Fabry disease given slightly better predictive value and reproducibility.

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.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.386
Teacher spread0.331 · 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