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Record W4234482012 · doi:10.4244/eij20170912-01

Report of an ESC-EAPCI Task Force on the evaluation and use of bioresorbable scaffolds for percutaneous coronary intervention: executive summary

2018· review· en· W4234482012 on OpenAlexaff
Robert A. Byrne, Giulio Stefanini, Davide Capodanno, Yoshinobu Onuma, Andreas Baumbach, Javier Escaned, Michael Haude, Stefan James, Michael Joner, Peter Jüni, Adnan Kastrati, Semih Oktay, William Wijns, Patrick W. Serruys, Stephan Windecker

Bibliographic record

VenueEuroIntervention · 2018
Typereview
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicinePercutaneous coronary interventionTask forceRandomized controlled trialClinical trialMedical physicsPercutaneousClinical endpointClinical PracticePhysical therapySurgeryMyocardial infarctionCardiologyInternal medicine

Abstract

fetched live from OpenAlex

A previous Task Force of the European Society of Cardiology (ESC) and European Association of Percutaneous Cardiovascular Interventions (EAPCI) provided a report on recommendations for the non-clinical and clinical evaluation of coronary stents. Following dialogue with the European Commission, the Task Force was asked to prepare an additional report on the class of devices known as bioresorbable scaffolds (BRS). Five BRS have CE-mark approval for use in Europe. Only one device -the Absorb bioresorbable vascular scaffold- has published randomized clinical trial data and this data show inferior outcomes to conventional drug-eluting stents (DES) at 2-3 years. For this reason, at present BRS should not be preferred to conventional DES in clinical practice. The Task Force recommends that new BRS devices should undergo systematic non-clinical testing according to standardized criteria prior to evaluation in clinical studies. A clinical evaluation plan should include data from a medium sized, randomized trial against DES powered for a surrogate end point of clinical efficacy. Manufacturers of successful devices receive CE- mark approval for use and must have an approved plan for a large-scale randomized clinical trial with planned long-term follow-up.

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)0.014
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.005

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 head0.106
GPT teacher head0.387
Teacher spread0.281 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations44
Published2018
Admission routes1
Has abstractyes

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