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Record W2888147975 · doi:10.1093/eurheartj/ehy530

Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve: lessons from the ADVANCE Registry

2018· article· en· W2888147975 on OpenAlexaff
Timothy Fairbairn, Koen Nieman, Takashi Akasaka, Bjarne Linde Nørgaard, Daniel S. Berman, Gilbert Raff, Lynne M. Hurwitz-Koweek, Gianluca Pontone, Tomohiro Kawasaki, Niels Peter Rønnow Sand, Jesper Møller Jensen, Tetsuya Amano, Michael Poon, Kristian Altern Øvrehus, Jeroen Sonck, Mark Rabbat, Sarah Mullen, Bernard De Bruyne, Campbell Rogers, Hitoshi Matsuo, Jeroen J. Bax, Jonathon Leipsic, Manesh R. Patel

Bibliographic record

VenueEuropean Heart Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of British Columbia
FundersHeartFlowDuke Clinical Research Institute
KeywordsMedicineFractional flow reserveComputed tomographyRadiologyAngiographyCoronary angiographyClinical decision makingComputed tomography angiographyAppropriate Use CriteriaCardiologyMedical physicsIntensive care medicineInternal medicineMyocardial infarction

Abstract

fetched live from OpenAlex

Aims: Non-invasive assessment of stable chest pain patients is a critical determinant of resource utilization and clinical outcomes. Increasingly coronary computed tomography angiography (CCTA) with selective CCTA-derived fractional flow reserve (FFRCT) is being used. The ADVANCE Registry, is a large prospective examination of using a CCTA and FFRCT diagnostic pathway in real-world settings, with the aim of determining the impact of this pathway on decision-making, downstream invasive coronary angiography (ICA), revascularization, and major adverse cardiovascular events (MACE). Methods and results: A total of 5083 patients with symptoms concerning for coronary artery disease (CAD) and atherosclerosis on CCTA were enrolled at 38 international sites from 15 July 2015 to 20 October 2017. Demographics, symptom status, CCTA and FFRCT findings, treatment plans, and 90 days outcomes were recorded. The primary endpoint of reclassification between core lab CCTA alone and CCTA plus FFRCT-based management plans occurred in 66.9% [confidence interval (CI): 64.8-67.6] of patients. Non-obstructive coronary disease was significantly lower in ICA patients with FFRCT ≤0.80 (14.4%) compared to patients with FFRCT >0.80 (43.8%, odds ratio 0.19, CI: 0.15-0.25, P < 0.001). In total, 72.3% of subjects undergoing ICA with FFRCT ≤0.80 were revascularized. No death/myocardial infarction (MI) occurred within 90 days in patients with FFRCT >0.80 (n = 1529), whereas 19 (0.6%) MACE [hazard ratio (HR) 19.75, CI: 1.19-326, P = 0.0008] and 14 (0.3%) death/MI (HR 14.68, CI 0.88-246, P = 0.039) occurred in subjects with an FFRCT ≤0.80. Conclusions: In a large international multicentre population, FFRCT modified treatment recommendation in two-thirds of subjects as compared to CCTA alone, was associated with less negative ICA, predicted revascularization, and identified subjects at low risk of adverse events through 90 days.

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)0.055
metaresearch head score (Gemma)0.163
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 score0.055
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.163
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0010.002
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 head0.082
GPT teacher head0.445
Teacher spread0.363 · 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

Citations306
Published2018
Admission routes1
Has abstractyes

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