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[PP.18.06] AORTIC STIFFNESS IMPROVES THE PREDICTION OF BOTH DIAGNOSIS AND SEVERITY OF CORONARY ARTERY DISEASE

2016· article· en· W2483338914 on OpenAlexaff
Alexandra Yannoutsos, M. Ahouah, C. Dreyfuss Tubiana, Jirar Topouchian, M Safar, Jacques Blacher

Bibliographic record

VenueJournal of Hypertension · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineCardiologyCoronary artery diseaseInternal medicinePulse wave velocityArterial stiffnessCohortBlood pressure

Abstract

fetched live from OpenAlex

Objective: Myocardial ischemia represents a crucial target of coronary artery disease (CAD) screening. Nevertheless, elective coronography presents a low diagnostic yield for obstructive CAD. The purpose of this study was to determine whether non invasive aortic stiffness assessment improves diagnostic accuracy of obstructive CAD screening.Design and method: A cross-sectional study was conducted from January 2013 to September 2014 in our medical center. Electrocardiogram (ECG) stress test coupled with nuclear imaging was performed in 367 consecutive patients routinely followed-up, for myocardial ischemia screening. Aortic pulse wave velocity (PWV) was assessed by applanation tonometry in overall population. Forty-two patients underwent elective coronography because of ischemia. Theoretical PWV was calculated according to age, blood pressure and gender. Results were expressed as an index [(measured PWV – theoretical PWV) / theoretical PWV] for each patient. Results: Ten patients presented with obstructive CAD, 16 patients had non-obstructive CAD and 16 patients had normal coronary angiography. PWV index and severity of CAD were positively correlated (p = 0.001). Glomerular filtration rate (GFR) was negatively associated with severity of CAD (p = 0.014). However, aortic PWV index and severity of CAD remained significantly correlated even after adjusting for GFR (p = 0.006). Diagnostic accuracy of stress test coupled with nuclear imaging was improved when using PWV index in case of discordant clinical/nuclear results (performance index without versus with PWV index: 0.41 versus 0.69). Twenty-two procedures may have been avoided in the present study cohort (Table 1). Conclusions: Aortic PWV index should be considered as clinically useful to rule out the presence of obstructive CAD and to reduce the rate of unnecessary angiographies. Furthermore, aortic PWV index was strongly correlated with the severity of CAD, according to the degree of stenosis. Thus, aortic stiffness may also be considered as a marker of the presence of non obstructive atherosclerotic coronary lesions which represent a potential target for pharmaceutical interventions to prevent acute coronary syndrome. Prospective studies, taking into account renal function, shall have the potential to further evaluate PWV index as a marker of 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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.344
Threshold uncertainty score0.936

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.3440.193

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 head0.024
GPT teacher head0.245
Teacher spread0.221 · 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.

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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