MétaCan
Menu
← Back to cohort

Abstract 19498: Abnormal Left ventricular Volumes Identified by Computed Tomography Improves Risk Stratification and Discrimination of Patients At Risk of Increased Mortality: Results from 3706 Patients in the Prospective Multicenter International CONFIRM Study

2012· article· en· W2237455208 on OpenAlexaff
Reza Arsanjani, Troy LaBounty, Victor Cheng, Fay Y. Lin, Mouaz H. Al‐Mallah, Matthew J. Budoff, Filippo Cademartiri, Tracy Q. Callister, Kavitha M. Chinnaiyan, Benjamin J.W. Chow, Augustin DeLago, Martin Hadamitzky, Jöerg Hausleiter, Philipp A. Kaufmann, Leslee J. Shaw, Todd C. Villines, James K. Min

Bibliographic record

VenueCirculation · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineRisk stratificationComputed tomographyProspective cohort studyMulticenter studyCardiologyInternal medicineRadiologyRandomized controlled trial

Abstract

fetched live from OpenAlex

Background: Prior studies have evaluated the prognostic value of abnormal left ventricular end-systolic (LVESV) and end-diastolic (LVEDV) volumes by cardiac CT angiography. These studies were limited to smaller studies and single centers. We evaluated whether left ventricular volumes improves risk stratification and discrimination for mortality prediction in a large prospective study. Methods: From 27125 subjects in the CONFIRM registry, we identified subjects without prior known coronary artery disease (CAD) who underwent CCTA with quantitative LVESV and LVEDV assessment. LVESV and LVEDV were categorized as normal (< 90ml and 90ml and > 200ml, respectively). CAD extent and severity was categorized as none (0%), non-obstructive ( 50%) 1-, 2- and 3-vessel disease. LVESV, LVEDV, and CAD were examined in relation to risk prediction and discrimination for future mortality employing Cox proportional hazards models and area under the receiver operating characteristics curve (AUC), respectively. Results: In a follow-up of 2.2+0.9 years, 3706 patients (59.1 + 12.6 years, 54.2% male) were studied with 207 (5.6%) with abnormal LVESV and 190 (5.1%) with abnormal LVEDV. Abnormal volumes were associated with male gender, hypertension, smoking and younger age (p<0.05 for all). In multivariable analyses, increased volumes was independently associated with mortality for abnormal LVESV (hazards ratio (HR) 6.56, 95% confidence interval (CI) 3.75-11.46, p<0.001) and abnormal LVEDV (HR 4.00, 95% confidence interval 1.98-8.08, p<0.001). Abnormal LVEDV (AUC 0.8178) and LVESV (0.8335) improved discrimination for identification of individuals at risk of death, when compared to CAD risk factors alone (0.7745) or CAD extent and severity and risk factors (0.7819) [p<0.001]. Conclusions: Incremental to clinical variables and CAD extent and severity, abnormal left ventricular volumes by CCTA offers improved risk prediction and discrimination for future mortality.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.254
Teacher spread0.244 · 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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCirculation→Same topicCardiac Imaging and Diagnostics→French-language works237,207→