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131 Left ventricular indexed mass associated with ventricular arrhythmias in patients with hypertrophic cardiomyopathy – a tertiary centre mri registry

2017· article· en· W2737780335 on OpenAlexaff
Habib Khan, Konstantinos Somarakis, Andrew Thain, Ayman Al‐Atta, Thomas Mathew

Bibliographic record

VenueHeart · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineHypertrophic cardiomyopathyCardiologyInternal medicineVentricular tachycardiaIncidence (geometry)Holter monitorCardiomyopathySudden cardiac deathElectrocardiographyHeart failure

Abstract

fetched live from OpenAlex

Background Hypertrophic cardiomyopathy (HCM) is a common inherited cardiac condition. Multiple factors have been identified towards high risk of sudden cardiac death (SCD) as outlined in the ESC guidelines. LV wall thickness (LV wt ) is an identified risk. Left ventricular mass indexed to body surface area (LV IBSA ) increases with wall thickness and may predict risk not currently utilised in the risk score. Objectives 1. Compare differences in LV wt using transthoracic echocardiogram(TTE) and MRI and the effect on ESC risk score. 2. Observe for association of LV IBSA and incidence of non-sustained ventricular tachycardia(NSVT) either on 24 hour holter monitor or following ICD insertion. Methods We retrospectively reviewed patients between January 2010 to July 2015 who were confirmed to have HCM on MRI. ESC Risk was calculated using LV TTE and MRI LV wt . LV IBSA was calculated from MRI images and compared with incidence of VA on holter monitors. Patients who received ICD had follow up and VA incidence recorded. Results 103 patients with confirmed HCM were identified with median age of 60 (range 15–87). Non sustained VT (NSVT) was recorded in 20 (19.4%) patients while 16 patients had missing or no record of holter. Primary prevention ICDs (ICD 1* ) were inserted in 20 (19.4%) patients. MRI identified a higher absolute LV wt compared to TTE in 68.9% of patients. This lead to an increase in ESC risk score from low risk to high risk in 5% of the patients (ESC score>4). LV IBSA was higher in the patients with holter positive for VA (mean 109.7g/m 2 , 95% CI [92.8, 126.6] vs 89.8g/m 2 , 95% CI [83.2, 96.4], p=<0.05). Patients with ICD (n=20) were followed up for 52.6 months±5.8 months. One patient with ICD 1* had VA detected after 7 months of ICD insertion and treated successfully with 1 anti-tachycardia pacing algorithm. Conclusion The detection of HCM through use of MRI allows for earlier diagnosis of patients and provides for accurate and reproducible measurements of LV wt and LV IBSA x as opposed to TTE. In our retrospective study it is suggested that higher LV IBSA is related to increase incidence of VA. If LV IBSA derived from MRI were applied to ESC guidelines, this could result in more patients ICD 1* . We feel this should be explored with larger studies to see if LV IBSA is an independent risk factor for SCD.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.007
GPT teacher head0.214
Teacher spread0.206 · 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.

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
Published2017
Admission routes1
Has abstractyes

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