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P6646Real life EP lab without fluoroscopy

2018· article· en· W2903929433 on OpenAlexaff
L Ayala Valani, E Al Baridi, Sofía Rivera, C Brambilla, Y Brahim, Andrea Klein, P Coluccini, P Compagno, Raúl Pérez Etchepare, Mohamed I Badra, Charles Dussault, Jean-François Roux, F. Ayala‐Paredes

Bibliographic record

VenueEuropean Heart Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging and Pathology Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineFluoroscopyMedical physicsNuclear medicineRadiology

Abstract

fetched live from OpenAlex

Background: Arrhythmias' invasive treatment requires X-rays to introduce and guide catheters to target ablation foci. X-rays have no therapeutic role in patients (pts) and there is no clear safe exposure dose either for pts or for EP physicians. Purpose: Single center experience with a daily life fluoroscopy free EP lab to guide introduction, navigation, mapping and ablation catheters in the four chambers of the heart. Methods: A near zero EP program was started in 2009, using 3-D mapping technology,beginning with flutter ablations FLU, AVNRT, AVRT, and finally complex AT and VT ablations; fluoroscopy elimination was achieved early in the experience, even pregnant patients were safely offered EP procedures when needed. Duration was measured since pts arrival to departure from EP lab. Acute success needed arrhythmia or substrate elimination with no complication. EPS were pts with palpitations in whom no arrhythmia was found. Follow up was completed in 81% of this cohort (1–61 months).

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.447
Threshold uncertainty score0.789

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.4470.167

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 head0.076
GPT teacher head0.370
Teacher spread0.294 · 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.

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

Citations1
Published2018
Admission routes1
Has abstractyes

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