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Abstract 14304: Assessing the Association of Adherence to Fractional Flow Reserve Treatment Thresholds and Outcomes of Patients With Coronary Artery Disease

2020· article· en· W3106213537 on OpenAlexaffabout
Maneesh Sud, Lu Han, Maria Koh, Peter C. Austin, Michael E. Farkouh, Hung Q. Ly, Mina Madan, Madhu K. Natarajan, Derek So, Harindra C. Wijeysundera, Dennis T. Ko

Bibliographic record

VenueCirculation · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsUniversity of OttawaUniversity of TorontoHamilton Health SciencesOttawa Heart InstituteMontreal Heart InstituteInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineFractional flow reserveConventional PCIPercutaneous coronary interventionMaceInternal medicineCardiologyMyocardial infarctionHazard ratioCoronary artery diseaseCohortRevascularizationAnginaConfidence interval

Abstract

fetched live from OpenAlex

Background: Although fractional flow reserve (FFR) thresholds have been established to guide the use of percutaneous coronary intervention (PCI) or medical therapy, little is known about the adherence to FFR thresholds for PCI in clinical practice and their association with clinical outcomes. Methods: Adults undergoing FFR assessment in a single vessel (excluding ST-segment elevation myocardial infarction [MI]) from April 1, 2013 to March 31, 2018 in Ontario, Canada were included. Patients were divided into two cohorts based on FFR ≤ 0.80 (ischemic) and > 0.80 (non-ischemic). Inverse probability of treatment weighting was used to balance confounders between patients treated with PCI vs. no PCI in each cohort. The primary outcome was major adverse cardiac events (MACE) defined by death, MI, unstable angina, or urgent revascularization. Results: We identified 9,106 patients who underwent single-vessel FFR measurement. Among the 2,693 patients with an ischemic FFR (mean age 65, 27.0% female), 75.3% of patients received PCI and 24.7% were treated only with medical therapy. Over a median follow-up of 2.6 years in the ischemic cohort, PCI was associated with a 20% lower rate of MACE compared to no PCI (24.0% vs. 31.6%; hazard ratio [HR]: 0.80, 95% CI: 0.66-0.96). However, among 6,413 patients with a non-ischemic FFR (mean age 66, 38.9% female), 12.6% received PCI and 87.4% were treated only with medical therapy. Over a median follow-up of 2.8 years in the non-ischemic cohort, PCI was associated with a 42% higher rate of MACE compared to no PCI (25.6% vs. 17.6%; HR: 1.42, 95% CI: 1.18-1.70). The increased rate of MACE was driven mainly by MI (HR 1.67, 95% CI: 1.20-2.31) but not death (HR 0.99, 95% CI: 0.72-1.35). Conclusions: In routine practice, we found 1 in 4 patients did not receive PCI for ischemic lesions while 1 in 8 received PCI for non-ischemic lesions. Performing PCI procedures according to recommended FFR cutoffs was associated with lower rates of clinical events.

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)0.008
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 score0.062
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.048
GPT teacher head0.335
Teacher spread0.287 · 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
Published2020
Admission routes2
Has abstractyes

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