MétaCan
Menu
Back to cohort
Record W2325301412 · doi:10.1186/1532-429x-18-s1-q21

Left atrial volume and function are predictive of cardiac death or appropriate device therapy in patients with non-ischemic dilated cardiomyopathy

2016· article· en· W2325301412 on OpenAlexaff
Punitha Arasaratnam, Archa Rajagopalan, Yoko Mikami, Khokan C. Sikdar, Naeem Merchant, Jacqueline McQuaker, Andrew G. Howarth, Bobby Heydari, James A. White, Carmen Lydell

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of CalgaryLibin Cardiovascular Institute of Alberta
Fundersnot available
KeywordsMedicineAngiologyCardiologyInternal medicineDilated cardiomyopathyCardiac function curveCardiomyopathyIschemic cardiomyopathyHeart failureEjection fraction

Abstract

fetched live from OpenAlex

Several small studies have suggested that left atrial end-diastolic volume (LAEDV) is associated with adverse outcomes in patients with non-ischemic dilated cardiomyopathy (NICM). However, left atrial function, assessed through either LA end-systolic volume (LAESV) or the LA ejection fraction (LAEF) may provide incremental predictive utility. We sought to evaluate the prognostic value of LA volume and LAEF by Cardiovascular Magnetic Resonance (CMR) in a cohort of patients with NICM. 117 patients (58% male) with NICM clinically referred for CMR were studied. Long axis cine images of the 2 and 4 chamber view were used to determine LAESV and LAEDV by a blinded reader using the area-length method. Values were indexed to body surface area using the Mostellar formula. Calculation of left ventricular (LV) volumes and EF were performed and the presence of any LV late gadolinium enhancement (LGE) was scored by an independent reader. All patients were followed for the composite outcome of cardiac death or appropriate implantable cardiac defibrillator (ICD) therapy. Cox proportional hazards models and Kaplan-Meier analysis were used to examine associations between LA measurements and the composite outcome. Mean age was 57.1 ± 14.0 years and mean LVEF 31.8 ± 12.1%. Over a median follow-up of 689 days, 19 patients developed the composite outcome. In univariable analysis, ICD implantation, presence of LGE, LVEF, LAEDV, LAESV and LAEF were significantly associated with the composite outcome. Following adjustment for ICD implantation, hazard ratios (HRs) for each of the LA measurements were; LAEDVi: 1.32 per 10 ml/m (95%CI 1.05-1.67, p = 0.02), LAESVi: 1.52 per 10 ml/m (95%CI 1.21-1.91, p < 0.01), and LAEF: 0.66 per 10% (95%CI 0.50-0.87, p < 0.01). These measures remained independently associated with the composite outcome following adjustment for ICD implantation and LVEF with HRs of 1.33 (p = 0.01), 1.51 (p < 0.01), and 0.66 (p < 0.01), respectively. A multivariable model that replaced LVEF with presence of LGE as an independent variable showed similar results with HRs of 1.30 (p = 0.04), 1.47 (p < 0.01), and 0.68 (p = 0.01), respectively. Kaplan-Meier analysis showed only LAEF to have significant predictive value for event free survival (p = 0.04). Both LA volume and LAEF are associated with the occurence of cardiac death or appropriate ICD therapy among patients with NICM. However, LAEF is superior for the discrimination of event free survival and may therefore be a preferred measure of risk in this population. Event free survival among NICM patients with LAEF above and below 40% .

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)0.004
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.198
Teacher spread0.191 · 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

Citations0
Published2016
Admission routes1
Has abstractno

Explore more

Same venueJournal of Cardiovascular Magnetic ResonanceSame topicCardiovascular Function and Risk FactorsFrench-language works237,207