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FFR-Negative Nonculprit High-Risk Plaques and Clinical Outcomes in High-Risk Populations: An Individual Patient-Data Pooled Analysis From COMBINE (OCT-FFR) and PECTUS-obs

2025· article· en· W4406706936 on OpenAlexaff
Rick Volleberg, Andi Rroku, Jan‐Quinten Mol, Renicus S. Hermanides, Maarten A.H. van Leeuwen, Balázs Berta, Martijn Meuwissen, Fernándo Alfonso, Wojciech Wojakowski, Anouar Belkacemi, Tomasz Roleder, Elvin Kedhi, Niels van Royen, Enrico Fabris, Alexander Ijsselmuiden, Floris Kauer, Clemens von Birgelen, Javier Escaned, Cyril Camaro, Mark Kennedy, Bruno Pereira, Michael Magro, Holger Nef, Sebastian Reith, Arif Al Nooryani, Fernando Rivero, Krzysztof Piotr Malinowski, Giuseppe De Luca, Héctor García García, Juan F. Granada, А. В. Протопопов, Peep Laanmets, Oleg Krestyaninov, Robert Dennert, Rohit M. Oemrawsingh, Jan‐Peter van Kuijk, Karin Arkenbout, Dirk J. van der Heijden, Saman Rasoul, Erik Lipšic, Laura Rodwell, Peter Damman, Robert‐Jan van Geuns

Bibliographic record

VenueCirculation Cardiovascular Interventions · 2025
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsRoyal Victoria Hospital
Fundersnot available
KeywordsMedicineFractional flow reserveCardiologyMyocardial infarctionInternal medicineRevascularizationPercutaneous coronary intervention

Abstract

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BACKGROUND: Despite fractional flow reserve (FFR)–guided deferral of revascularization, recurrent events in patients with diabetes or after myocardial infarction remain common. This study aimed to assess the association between FFR-negative but high-risk nonculprit lesions and clinical outcomes. METHODS: This is a patient-level pooled analysis of the prospective natural-history COMBINE (OCT-FFR) study (Optical Coherence Tomography Morphologic and Fractional Flow Reserve Assessment in Diabetes Mellitus Patients) and PECTUS-obs study (Identification of Risk Factors for Acute Coronary Events by OCT After STEMI and NSTEMI Patients With Residual Non- Flow Limiting Lesions). Optical coherence tomography was performed on all FFR-negative (FFR >0.80) native nonculprit lesions. Patients or lesions with a high-risk plaque were compared with those without a high-risk plaque. A high-risk plaque was defined in the presence of at least 2 prespecified criteria: (1) lipid arc ≥90 o , (2) minimum fibrous cap thickness <65 µm, and (3) presence of either plaque rupture or thrombus. The primary end points were native major adverse cardiovascular events (composite of all-cause mortality, nonfatal myocardial infarction, or unplanned revascularization excluding stent-failure–related events and nonattributable events) and target lesion failure (composite of cardiac death, target vessel myocardial infarction, or target lesion revascularization). RESULTS: Among 810 patients, 450 (55.6%) had a history of diabetes and 482 (59.5%) presented with myocardial infarction. At least 1 high-risk plaque was identified in 271 (33.5%) patients and 287 (30.6%) lesions. Over a median follow-up of 761 (interquartile range, 731–1175) days, the presence of a high-risk plaque was associated with patient-level native major adverse cardiovascular events (hazard ratio, 2.127 [95% CI, 1.451–3.120]; P <0.001) and lesion-level target lesion failure (hazard ratio, 2.623 [95% CI, 1.559–4.414]; P <0.001). The risk of adverse outcomes increased with the copresence of multiple high-risk features. CONCLUSIONS: FFR-negative but high-risk nonculprit lesions are associated with adverse patient- and lesion-level clinical outcomes. These findings emphasize the additional value of intracoronary imaging in patients with FFR-negative nonculprit lesions. REGISTRATION: URL: https://clinicaltrials.gov ; Unique identifier: NCT02989740; Unique identifier: NCT03857971.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.358
Teacher spread0.298 · 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 teacher head, 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".

Quick stats

Citations18
Published2025
Admission routes1
Has abstractyes

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