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Record W2952986024 · doi:10.1016/j.hrcr.2019.06.002

Bipolar ablation with half normal saline for deep intramural outflow tract premature ventricular contraction

2019· article· en· W2952986024 on OpenAlexaff
Andrés Enríquez, Víctor Neira, David Bakker, Jason Baley, Gianluigi Bisleri, Adrián Baranchuk, Damian Redfearn

Bibliographic record

VenueHeartRhythm Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsAbbott (Canada)Queen's University
Fundersnot available
KeywordsMedicineAblationIntracardiac injectionCardiologyInternal medicineSalineVentricular outflow tract

Abstract

fetched live from OpenAlex

Key Teaching Points•In ventricular arrhythmias, an intramural septal origin should be suspected in case of poor precocity or pace map in either side of the septum, far-field local electrograms, and/or diffuse areas of earlier activation recorded on the mapped surfaces.•Bipolar ablation using half normal saline as irrigant can be effectively and safely performed to treat intramural septal ventricular arrhythmias when conventional ablation has failed.•Gradual titration of power, real-time monitoring with intracardiac echocardiography, and close attention to impedance and temperature are recommended to minimize complications. •In ventricular arrhythmias, an intramural septal origin should be suspected in case of poor precocity or pace map in either side of the septum, far-field local electrograms, and/or diffuse areas of earlier activation recorded on the mapped surfaces.•Bipolar ablation using half normal saline as irrigant can be effectively and safely performed to treat intramural septal ventricular arrhythmias when conventional ablation has failed.•Gradual titration of power, real-time monitoring with intracardiac echocardiography, and close attention to impedance and temperature are recommended to minimize complications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.055
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.251
Teacher spread0.244 · 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.

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

Citations6
Published2019
Admission routes1
Has abstractyes

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