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Prognostic implications of coronary artery calcium in the absence of coronary artery luminal narrowing

2016· article· en· W2558541906 on OpenAlexaff
Iksung Cho, Bríain ó Hartaigh, Heidi Gransar, Valentina Valenti, Fay Y. Lin, Stephan Achenbach, Daniel S. Berman, Matthew J. Budoff, Tracy Q. Callister, Mouaz H. Al‐Mallah, Filippo Cademartiri, Kavitha M. Chinnaiyan, Benjamin J.W. Chow, Allison Dunning, Augustin DeLago, Todd C. Villines, Martin Hadamitzky, Jöerg Hausleiter, Jonathon Leipsic, Leslee J. Shaw, Philipp A. Kaufmann, Ricardo C. Cury, Gudrun Feuchtner, Yong‐Jin Kim, Erica Maffei, Gilbert Raff, Gianluca Pontone, Daniele Andreini, Hyuk‐Jae Chang, James K. Min

Bibliographic record

VenueAtherosclerosis · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of British ColumbiaUniversity of Ottawa
FundersNational Heart, Lung, and Blood InstituteKorea Evaluation Institute of Industrial TechnologyNational Institutes of HealthMinistry of Science, ICT and Future Planning
KeywordsMedicineCardiologyInternal medicineDyslipidemiaHazard ratioStenosisCoronary artery diseaseDiabetes mellitusArteryConfidence intervalCoronary artery calciumComputed tomographic angiographyDiseaseAngiography

Abstract

fetched live from OpenAlex

BACKGROUND AND AIMS: Coronary artery calcium (CAC) scoring is a predictor of future adverse clinical events, and a surrogate measure of overall coronary artery plaque burden. Coronary computed tomographic angiography (CCTA) is a contrast-enhanced method that allows for visualization of plaque as well as whether that plaque causes luminal narrowing. To date, the prognosis of individuals with CAC but without stenosis has not been reported. We explored the prevalence of CAC>0 and its prognostic utility for future mortality for patients without luminal narrowing by CCTA. METHODS: From 17 sites in 9 countries, we identified patients without known coronary artery disease, who underwent CAC scoring and CCTA, and were followed for >3 years. CCTA was graded for % stenosis according to a modified American Heart Association 16-segment model. We calculated hazard ratios (HR) with 95% confidence intervals (95% CI) for incident mortality and compared risk of death for patients as a function of presence or absence of CAC and presence or absence of luminal narrowing by CCTA. RESULTS: Among 6656 patients who underwent CCTA and CAC scoring, 399 patients (6.0%) had no coronary luminal narrowing but CAC>0. During a median follow-up of 5.1 years (IQR: 3.9-5.9 years), 456 deaths occurred. Compared to individuals without luminal narrowing or CAC, individuals without luminal narrowing but CAC>0 were older, more likely to be male and had higher rates of diabetes, hypertension, and dyslipidemia. Individuals without luminal narrowing but CAC experienced a 2-fold increased risk of mortality, with increasing risk of mortality with higher CAC score. Following adjustment, incident death persisted (HR, 1.8; 95% CI, 1.1-2.9, p = 0.02) among patients without luminal narrowing but with CAC>0 compared with patients whose CACS = 0. Individuals without luminal narrowing but CAC ≥100 had mortality risks similar to individuals with non-obstructive CAD (0 < stenosis<50%) by CCTA [HR 2.5 (95% CI 1.3-4.9) and 2.2 (95% CI 1.6-3.0), respectively]. CONCLUSIONS: Patients without luminal narrowing but with CAC experience greater risk of 5-year mortality. Patients with CAC score ≥100 and no coronary luminal narrowing experience death rates similar to those with non-obstructive CAD.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.281
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

Citations21
Published2016
Admission routes1
Has abstractyes

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