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Record W2510421155 · doi:10.21037/cdt.2016.08.01

Alcohol septal ablation for hypertrophic obstructive cardiomyopathy in a patient with a chronic total occlusion of the right coronary artery: “beware of collateral damage”

2017· article· en· W2510421155 on OpenAlexaff
Quentin de Hemptinne, Fabien Picard, Philippe L. L’Allier

Bibliographic record

VenueCardiovascular Diagnosis and Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersAbbott VascularFédération Française de Cardiologie
KeywordsMedicineAlcohol septal ablationContraindicationCardiologyInternal medicinePercutaneousRevascularizationArteryObstructive cardiomyopathySurgeryHypertrophic cardiomyopathyMyocardial infarctionPathology

Abstract

fetched live from OpenAlex

Alcohol septal ablation (ASA) is an effective semi-invasive alternative to surgical myectomy in selected patients for the management of severely symptomatic and drug-refractory hypertrophic obstructive cardiomyopathy (HOCM). One contraindication of this procedure is the presence of collateral flow originating from the target septal perforator to a remote myocardial territory. In such circumstances, ethanol injection could cause remote non-target myocardial necrosis in the collateralized territory. Percutaneous revascularization of the collateralized vessel prior to ASA might cope with this contraindication by restoring normal antegrade flow in the occluded artery. We report a case that illustrates the feasibility and efficacy of such strategy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.014
GPT teacher head0.238
Teacher spread0.224 · 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 designCase report
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

Citations1
Published2017
Admission routes1
Has abstractyes

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