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Record W4391364801 · doi:10.1016/j.jcct.2024.01.009

Identifying left ventricular dysfunction using prospective electrocardiogram-triggered coronary computed tomography angiography

2024· article· en· W4391364801 on OpenAlexaff
Ashwin Sharma, Fernanda Erthal, Daniel Juneau, Atif Alzahrani, Ali Alenazy, Samia Massalha, Yeung Yam, Bilaal Kabir, Gary R. Small, Benjamin J.W. Chow

Bibliographic record

VenueJournal of cardiovascular computed tomography · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsOttawa HospitalCentre Hospitalier de l’Université de MontréalMontreal Heart InstituteUniversity of Ottawa
Fundersnot available
KeywordsMedicineEjection fractionCardiologyCoronary artery diseaseInternal medicineProspective cohort studyCohortStroke volumeHeart failure

Abstract

fetched live from OpenAlex

PurposeCoronary computed tomography angiography (CCTA) is an important non-invasive tool for the assessment of coronary artery disease and the delivery of information incremental to coronary anatomy. CCTA measured left ventricular (LV) mid-diastolic volume (LVMDV) and LV mass (LVMass) have important prognostic information but the utility of prospectively ECG-triggered CCTA to predict reduced left ventricular ejection fraction (LVEF) is unknown. The objective of this study was to determine if indexed LVMDV (LVMDVi) and the LVMDV:LVMass ratio on CCTA can identify patients with reduced LVEF.Materials/methods8179 patients with prospectively ECG-triggered CCTA between November 2014 and December 2019 were reviewed. A subset derivation cohort of 4352 healthy patients was used to define normal LVMDVi and LVMDV:LVMass. Sex-specific thresholds were tested in a validation cohort of 1783 patients, excluded from the derivation cohort, with cardiac disease and known LVEF. The operating characteristics for 1 SD above the mean were tested for the identification of abnormal LVEF, LVEF≤35 ​% and ≤30 ​%.ResultsThe derivation cohort had a mean LVMDVi of 61.0 ​± ​13.7 ​mL/m2 and LVMDV:LVMass of 1.11 ​± ​0.24 ​mL/g. LVMDVi and LVMDV:LVMass were both higher in patients with reduced LVEF than those with normal LVEF (98.8 ​± ​40.8 ​mL/m2 vs. 63.3 ​± ​19.7 ​mL/m2, p ​< ​0.001, and 1.32 ​± ​0.44 ​mL/g vs. 1.05 ​± ​0.28 ​mL/g, p ​< ​0.001). Both mean LVMDVi and LVMDV:LVMass increased with the severity of LVEF reduction. Sex-specific LVMDVi thresholds were 79 ​% and 80 ​% specific for identifying abnormal LVEF in females (LVMDVi ​≥ ​69.9 ​mL/m2) and males (LVMDVi ​≥ ​78.8 ​mL/m2), respectively. LVMDV:LVMass thresholds had high specificity (87 ​%) in both females (LVMDVi:LVMass ​≥ ​1.39 ​mL/g) and males (LVMDVi:LVMass ​≥ ​1.30 ​mL/g).ConclusionOur study provides reference thresholds for LVMDVi and LVMDV:LVMass on prospectively ECG-triggered CCTA, which may identify patients who require further LV function assessment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.783
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.017
Bibliometrics0.0050.006
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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