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Record W4306320297 · doi:10.1093/eurheartj/ehac544.200

FFRCT and recurrent symptoms in patients with stable chest pain

2022· article· en· W4306320297 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, K K Thomsen, Hans Erik Boetker, Jonathon Leipsic, N. PR Sand

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineChest painFractional flow reserveCoronary artery diseaseRevascularizationStenosisInternal medicineAnginaCohortCardiologyCoronary angiographyMyocardial infarction

Abstract

fetched live from OpenAlex

Abstract Introduction The major benefit of coronary revascularization when compared with optimal medical treatment (OMT) in patients with stable chest pain (CP) relates to improvement of symptoms and reduction of reinterventions. Non-invasive methods are warranted to discriminate between patients at low and high risk of recurrent CP for subsequent guidance of antianginal treatment (invasive or OMT). Purpose To evaluate the association between coronary CT angiography (CTA) derived fractional flow reserve (FFRCT), recurrent CP and quality of life (QOL) in patients with new onset stable CP and stenosis by CTA. Methods Multicenter cohort 3-year follow-up sub-study of 769 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. An abnormal FFRCT was defined as the lowest in vessel FFRCT value ≤0.80. 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. All patients completed the Seattle Angina Questionnaire (SAQ-7), the EuroQol questionnaire (EQ-5D-5L) and graded (0–100) overall health using the EQ VAS scale at 3-year follow-up. Recurrent CP was defined as CP within the last 4 weeks prior to this follow-up. Results Patient characteristics are given in Table 1. At follow-up 23% patients reported recurrent CP. An abnormal vs a normal FFRCT increased the risk of recurrent CP, 27% vs 15%, RR: 1.82; 95% CI: 1.31–2.52, p<0.001. Amongst patients with abnormal FFRCT, revascularization (+/−) was associated to a numerical, but not statistical significantly, reduced risk of recurrent CP, 23% vs 30%, RR: 0.76; 95% CI: 0.56–1.03, p=0.07. IR-FFRCT vs CR-FFRCT had a higher risk for recurrent CP, 31% vs 13%, RR: 2.34; 95% CI: 1.48–3.68, p<0.001, whilst no difference was observed for CR-FFRCT vs normal FFRCT, 13% vs 15%, RR: 0.92; 95% CI: 0.54–1.54, p=0.74. IR-FFRCT vs CR-FFRCT or normal FFRCT, had lower SAQ-7, EQ-5D-5L and EQ-VAS scores, Table 1, all p<0.005. Scores for three selected SAQ-7 domains are shown in Figure 1. Use of antianginal medicine was higher in IR-FFRCT compared to CR-FFRCT and normal FFRCT, mean ± SD: 1.2±0.05 vs 1.0±0.04, p=0.02. Conclusion An abnormal FFRCT identifies patients with an increased risk of recurrent CP up to 3 years after index testing. Completeness of revascularization by FFRCT reclassifies patients with abnormal FFRCT into groups with low and high risk for recurrent CP and impaired QOL. 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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.243
Teacher spread0.230 · 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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