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Record W4417105805 · doi:10.1016/j.ahjo.2025.100694

Predictive value of abnormal coronary computed tomography angiography in patients with Normal single-photon emission computed tomography scan

2025· article· en· W4417105805 on OpenAlexaff
Rami M. Abazid, Monerah A. Almohideb, Osama Smettie, Naveed Asad, Yasmine Sallam, Mohamed Abdelrazek, Çiğdem Akincioğlu, James Warrington, Jonathan Romsa, William C. Vezina

Bibliographic record

VenueAmerican Heart Journal Plus Cardiology Research and Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt. Joseph’s Healthcare HamiltonWestern UniversityLondon Health Sciences CentreSault Area Hospital
Fundersnot available
KeywordsComputed tomographyCoronary artery diseaseMaceCoronary angiographyPredictive valueComputed tomography angiography

Abstract

fetched live from OpenAlex

Background: The aim of this study was to assess the prognostic value of abnormal coronary computed tomography angiography (CCTA) in patients with normal single-photon emission computed tomography (SPECT) study. Methods: We retrospectively enrolled patients with normal SPECT scans and abnormal CCTA studies, who were categorized according to CCTA findings into obstructive with ≥50 %, and non-obstructive CAD <50 % coronary artery stenosis. Major adverse cardiac events (MACE) was defined as cardiovascular death and non-fatal myocardial infarction. Results: < 0.001) are independent predictors of mortality. Conclusion: Obstructive CAD on CCTA is associated with significantly higher long-term risk of MACE in comparison to non-obstructive CAD in patients with normal SPECT.

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)0.005
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.019
GPT teacher head0.328
Teacher spread0.309 · 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
Published2025
Admission routes1
Has abstractyes

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