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Record W4306254481 · doi:10.1093/eurheartj/ehac544.201

Completeness of revascularization by FFRCT and prognosis in stable chest pain

2022· article· en· W4306254481 on OpenAlexaff
Kristian Tækker Madsen, B L Noergaard, K A Oevrehus, Erik Thorlund Parner, Jesper Møller Jensen, Erik Lerkevang Grove, Timothy Fairbairn, Koen Nieman, Michele L Patel, Campbell Rogers, Hans Mickley, A Rohold, Hans Erik Boetker, Jonathon Leipsic, N P R Sand

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineRevascularizationInternal medicineMyocardial infarctionCardiologyClinical endpointCoronary artery diseaseChest painStenosisRandomized controlled trial

Abstract

fetched live from OpenAlex

Abstract Introduction Major randomized trials of patients with stable chest pain (CP) demonstrated no prognostic benefits of coronary revascularization over optimal medical treatment (OMT). However, in a recent large-scale study, completeness of revascularization was associated with a reduced risk of all-cause death and non-fatal myocardial infarction (MI). Purpose To evaluate the association between completeness of revascularization relative to the result of coronary CT angiography (CTA) derived fractional flow reserve (FFRCT) and 3-year prognosis in patients with new onset stable CP and coronary stenosis. Methods Multicenter cohort 3-year follow-up sub-study of 900 patients from the Assessing Diagnostic Value of Non-invasive FFRCT in Coronary Care (ADVANCE) registry at three Danish sites, the “ADVANCE-DK Registry”. All patients had at least one ≥30% coronary stenosis by CTA and underwent subsequent core laboratory FFRCT analysis by HeartFlow. The FFRCT result was abnormal when ≤0.80 (2 cm distal to stenosis). Patients were classified according to completeness of revascularization by FFRCT: 1) completely revascularized (CR-FFRCT), all coronary arteries with an abnormal FFRCT test result revascularized; 2) incompletely revascularized (IR-FFRCT), ≥1 coronary artery with an abnormal FFRCT test result not revascularized. The primary endpoint (PE) was a composite of all-cause death and spontaneous MI. The secondary endpoint (SE) was a composite of cardiovascular (CV) death and spontaneous MI. Results Patient characteristics are given in Table 1. In total 36 (4.0%) patients suffered a PE (all-cause death, n=24; MI, n=12) and 22 (2.4%) an SE (CV death, n=10; MI, n=12). Overall, an abnormal vs a normal FFRCT test result was associated with an increased risk of both the PE, 6.6% vs 2.1%, relative risk (RR): 3.1; 95% CI: 1.6–6.3, p<0.001 and of the SE, 5.0% vs 0.6%, RR: 8.7; 95% CI: non assessable, p<0.001. In patients with abnormal FFRCT, revascularization vs no revascularization did not reduce the risk of the PE or the SE (data not shown). Patients with IR-FFRCT vs CR-FFRCT had a numerical, but not statistical significantly, increased risk of the PE, 8.6% vs 4.2%, RR: 2.14; 95% CI: 0.87–5.26, p=0.10), and an increased risk of the SE, 7.1% vs 2.4%, RR: 3.13; 95% CI: 1.02–9.63, p=0.04, Figure 1. In CR-FFRCT versus normal FFRCT no difference in the risk of the PE or the SE was observed, Figure 1. Univariate sensitivity analyses performed in the IR-FFRCT group did not reveal any differences in the risk of the PE or the SE after adjustment for neither statin therapy at follow-up (−/+), baseline risk variables (< / ≥3), amount of CAC (< / ≥400), degree of stenosis by CTA (< / ≥50%) nor referral to ICA (−/+). Conclusion In symptomatic patients with coronary stenosis by CTA, incomplete revascularization determined by FFRCT is associated with an increased risk of adverse cardiovascular outcomes compared to complete revascularization. Funding Acknowledgement Type of funding sources: None.

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)0.005
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.027
GPT teacher head0.264
Teacher spread0.237 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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