MétaCan
Menu
Back to cohort
Record W1851267402 · doi:10.1186/1532-429x-15-s1-o72

Diffuse myocardial fibrosis in pediatric hypertrophic cardiomyopathy

2013· article· en· W1851267402 on OpenAlexaff
Tarique Hussain, A. Dragulescu, Lee Benson, Derek Wong, Mark K. Friedberg, Luc Mertens, Shi‐Joon Yoo, Lars Grosse‐Wortmann

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsChildren's Hospital of Eastern OntarioHospital for Sick Children
Fundersnot available
KeywordsMedicineAngiologyHypertrophic cardiomyopathyMyocardial fibrosisCardiologyFibrosisInternal medicineCardiomyopathyPathologyHeart failure

Abstract

fetched live from OpenAlex

Fibrosis is a common end-point in pathological processes. It is unclear, however, if diffuse fibrosis occurs early in the pathogenesis of hypertrophic cardiomyopathy (HCM). The purpose of this study was to evaluate the presence of diffuse myocardial fibrosis in children and adolescents with HCM using quantification of T1 changes late after gadolinium administration and to assess for associations between markers of fibrosis and standard clinical parameters of disease. Patients with confirmed HCM and healthy controls participated in this study. T1 measurements were made using standard multi-breath-hold spoiled gradient echo phase-sensitive inversion-recovery MRI. They were performed before and 15 minutes after 0.2 mmol/kg gadopentetate dimeglumine in a single mid-ventricular slice using increasing inversion times per breath-hold (150, 400, 800 and 3200 ms). For analysis, regions of interest were drawn in the septum, blood pool and left ventricular (LV) lateral wall, avoiding myocardium showing overt late enhancement (LGE). A curve-fitting technique was used to derive the T1 time constant (Figure 1 ). The tissue-blood partition coefficient (PCf) was calculated as a function of the ratio of T1 change of myocardium compared to blood [ 1 ]: higher PCf values indicate greater fibrosis. Clinical data included LV mass, ejection fraction, presence of LGE, symptoms, serum brain-natriuretic-peptide (BNP), mitral valve inflow velocities and presence of outflow tract obstruction at rest. A single mid-ventricular slice is imaged over multiple inversion times. A curve-fitting technique is used to create a T1 map of the myocardium. Individual regions of interest in the septum, blood pool and lateral wall are subsequently drawn and recorded. 12 controls (mean age 12.8yrs; 7 male) and 28 patients (mean age 12.8yrs; 21 male) participated. All patients had a clinical diagnosis of HCM. Among these, 20 children had HCM-specific mutations. Clinical parameters are given in table 1 . PCf for both septal (0.27±0.17 vs. 0.13±0.09 ml/g; p=0.03) and lateral walls (0.22±0.09 vs. 0.07±0.10; p<0.001) were increased in patients compared to controls. PCf did not correlate with age, either in patients or normal individuals. Eight patients had overt areas of LGE. These patients did not show increased coefficients compared to those without LGE (0.27±0.15 vs. 0.27±0.19 and 0.22±0.09 vs. 0.22±0.09; p=0.95 and 0.98 respectively). However, patients that were symptomatic (dyspnoea, arrhythmia or chest pain) had higher lateral wall coefficients than asymptomatic HCM patients (0.27±0.08 vs. 0.17±0.08; p=0.006). Similarly, patients with raised BNP (>100 pg/ml) had raised lateral wall coefficients (0.27±0.07 vs. 0.20±0.07; p=0.03). Other clinical parameters did not show any discrimination with respect to the lateral coefficient. Diffuse fibrosis, demonstrated by the partition coefficient technique, is demonstrable in children and adolescents with HCM. Markers of fibrosis show an association with symptoms and raised serum BNP. Further study of the prognostic implication of this technique is warranted.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.208
Teacher spread0.199 · 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
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

Citations7
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cardiovascular Magnetic ResonanceSame topicCardiomyopathy and Myosin StudiesFrench-language works237,207