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Prognostic Significance of Cardiac Magnetic Resonance Imaging Late Gadolinium Enhancement in Fabry Disease

2018· letter· en· W2902420007 on OpenAlexaff
Kate Hanneman, Gauri Rani Karur, Syed Wasim, Chantal F. Morel, Robert M. Iwanochko

Bibliographic record

VenueCirculation · 2018
Typeletter
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineMagnetic resonance imagingGadoliniumFabry diseaseCardiac magnetic resonanceDiseaseRadiologyCardiac magnetic resonance imagingCardiologyInternal medicine

Abstract

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Cardiac involvement is the leading cause of mortality in Fabry disease (FD).Late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging predicts adverse cardiac events in other cardiomyopathies.However, it is unclear whether LGE is a significant predictor of adverse cardiac events in FD.The purpose of this study was to evaluate the prognostic significance of the presence and extent of LGE in FD.This retrospective cohort study was approved by the institutional research ethics board.The requirement for written informed consent was waived.All patients with gene-positive FD who had undergone cardiac magnetic resonance imaging with LGE between March 2008 and March 2018 and had clinical follow-up at our institution were included.Magnetic resonance imaging studies were performed with 1.5-or 3-T scanners (MAGNETOM Avanto or Skyra; Siemens Healthcare, Erlangen, Germany).Multiplane LGE images were acquired 12 to 15 minutes after intravenous contrast administration and were visually evaluated for the presence of LGE.Left ventricular endocardial and epicardial borders were contoured on short-axis LGE images to assess the extent of LGE using a signal intensity threshold of 4 SDs, expressed as a percentage of myocardial mass (Circle cmr42; Circle Cardiovascular Imaging, Calgary, Canada).The primary end point was defined as the composite of ventricular tachycardia (VT), bradycardia, heart failure, and cardiac death.Nonsustained VT and sustained VT were defined as ≥3 consecutive beats arising below the atrioventricular node with an inter-beat (RR) interval of >100 bpm lasting <30 and ≥30 seconds, respectively.Bradycardia was defined as a heart rate <60 bpm requiring device implantation for pacing.Heart failure was defined as the development of New York Heart Association functional class III/IV symptoms.Cardiac death was classified as sudden or heart failure-related death.Individual adverse cardiac events were evaluated as secondary end points.Patients without events were censored at the time of their last clinical follow-up.Statistical analysis was performed with STATA version 14.1 (StataCorp, College Station, TX).A 2-tailed value of P<0.05 was considered statistically significant.Time-to-event survival analysis using univariable Cox proportional hazard models were used to estimate the hazard ratio (HR) for the presence and extent of LGE.Eighty-two patients were included in the study with 3.8±2.8years of followup (mean age, 44.7±14.8years; 32.9% male).LGE was present in 34 patients (41.5%) with a mean LGE extent of 4.4±7.8%.Overall, 16 patients (19.5%) reached the primary end point with an incidence rate of 6.1%/y: 13 of 34 patients (38.2%) with LGE compared with 3 of 48 patients (6.3%) without LGE (HR, 7.35; 95% CI, 2.09-25.89;P=0.002; Table).The risk of the primary end point increased with the extent of LGE (HR, 1.26/5% increase in LGE; 95% CI, 1.06-1.50;P=0.008).

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)0.001
metaresearch head score (Gemma)0.005
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: Commentary · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.284
Teacher spread0.263 · 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
GenreCommentary

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".

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Citations25
Published2018
Admission routes1
Has abstractno

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