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Nonculprit Lesion Plaque Morphology in Patients With ST-Segment–Elevation Myocardial Infarction

2020· article· en· W3041007085 on OpenAlexafffund
Natalia Pinilla‐Echeverri, Shamir R. Mehta, Wang Jia, Shahar Lavi, Érick Schampaert, Warren J. Cantor, Kevin R. Bainey, Robert C. Welsh, S.A. Kassam, Roxana Mehran, Robert F. Storey, Helen Nguyen, Brandi Meeks, David Wood, John A. Cairns, Tej Sheth

Bibliographic record

VenueCirculation Cardiovascular Interventions · 2020
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsVancouver General HospitalThe Scarborough HospitalHôpital du Sacré-Cœur de MontréalWestern UniversitySouthlake Regional Health CenterSt. Paul's HospitalLondon Health Sciences CentreUniversity of AlbertaPopulation Health Research Institute
FundersCanadian Institutes of Health Research
KeywordsMedicinePercutaneous coronary interventionCardiologyMyocardial infarctionInternal medicineLesionCulpritConventional PCITarget lesionStenosisRevascularizationAcute coronary syndromeRadiologySurgery

Abstract

fetched live from OpenAlex

Background: Complete revascularization with routine percutaneous coronary intervention of nonculprit lesions after primary percutaneous coronary intervention improves outcomes in ST-segment–elevation myocardial infarction. Whether this benefit is associated with nonculprit lesion vulnerability is unknown. Methods: In a prospective substudy of the COMPLETEs trial (Complete vs Culprit-Only Revascularization to Treat Multi-Vessel Disease After Early PCI for STEMI), we performed optical coherence tomography of at least 2 coronary arteries before nonculprit lesion percutaneous coronary intervention in 93 patients with ST-segment–elevation myocardial infarction and multivessel disease; and the ST-segment–elevation myocardial infarction culprit vessel if there was unstented segment amenable to imaging. Nonculprit lesions were categorized as obstructive (≥70% stenosis by visual angiographic assessment) or nonobstructive, and as thin-cap fibroatheroma (TCFA) or non-TCFA by optical coherence tomography criteria. TCFA was defined as a lesion with mean fibrous cap thickness <65 μm overlying a lipid arc >90°. Results: On a patient level, at least one obstructive TCFA was observed in 44/93 (47%) of patients. On a lesion level, there were 58 TCFAs among 150 obstructive nonculprit lesions compared with 74 TCFAs among 275 nonculprit lesions (adjusted TCFA prevalence: 35.4% versus 23.2%, P =0.022). Compared with obstructive non-TCFAs, obstructive TCFAs had similar lesion length (23.1 versus 20.8 mm, P =0.16) but higher lipid quadrants (55.2 versus 19.2, P <0.001), greater mean lipid arc (203.8° versus 84.5°, P <0.001), and more macrophages (97.1% versus 54.4%, P <0.001) and cholesterol crystals (85.8% versus 44.3%, P <0.001). For nonobstructive lesions, TCFA lesions had similar lesion length (16.7 versus 14.6 mm, P =0.11), but more lipid quadrants (36.4 versus 13.5, P <0.001), and greater mean lipid arc (191.8° versus 84.2°, P <0.001) compared with non-TCFA. Conclusions: Among patients who underwent optical coherence tomography imaging in the COMPLETE trial, nearly 50% had at least one obstructive nonculprit lesion containing complex vulnerable plaque. Obstructive lesions more commonly harbored vulnerable plaque morphology than nonobstructive lesions. This may help explain the benefit of routine percutaneous coronary intervention of obstructive nonculprit lesions in patients with ST-segment–elevation myocardial infarction and multivessel disease. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT01740479s.

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)0.002
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.038
GPT teacher head0.269
Teacher spread0.231 · 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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Citations133
Published2020
Admission routes2
Has abstractyes

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