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Record W2626262863

Ablación o drogas en la fibrilación auricular paroxística

2016· article· es· W2626262863 on OpenAlexaff
Aldo Carrizo, J. Gabriel Acosta, Carlos A. Morillo

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2016
Typearticle
Languagees
FieldMedicine
TopicCardiac Arrhythmias and Treatments
Canadian institutionsPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsMedicine
DOInot available

Abstract

fetched live from OpenAlex

"Resumen Durante años las drogas antiarrítmicas (DAA) han constituido el tratamiento fundacional para los pacientes con fibrilación auricular paroxística (FAP) en los cuales se desea mantener el ritmo sinusal. Debido a las limitaciones en su eficacia, principalmente a largo plazo, sumado a la gran proporción de pacientes que discontinúan la terapia por efectos adversos, nuevas terapias no farmacológicas han sido desarrolladas con el fin de lograr un adecuado control del ritmo. En la última década la ablación por catéter se ha mostrado como la terapia más efectiva y posiblemente la más segura en aquellos pacientes con falla del tratamiento antiarrítmico. Estudios randomizados y metaanálisis recientemente publicados indican que la ablación podría ser considerada como primera línea de terapia en pacientes seleccionados con FAP en quienes se busca controlar el ritmo. Por lo tanto, en este artículo revisaremos la evidencia actual que avala el uso de DAA o ablación en la FAP."

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.009
GPT teacher head0.243
Teacher spread0.234 · 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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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