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Record W2783141207

Eficacia y seguridad similares de liraglutida 3,0 mg en el control del peso en las distintas categorías basales del Sistema de Clasificación de la Obesidad Edmonton (EOSS): análisis a posteriori a las 56 semanas.

2018· article· es· W2783141207 on OpenAlexaboutno aff
Concepción Muñoz

Bibliographic record

VenueBMI-Journal · 2018
Typearticle
Languagees
FieldHealth Professions
TopicHealth and Lifestyle Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Los estudios SCALE Obesidad y Prediabetes y SCALE  Diabetes evaluaron la eficacia y la seguridad de liraglutida 3,0 mg, junto con dieta y ejercicio para el manejo del peso. La perdida de peso, los criterios de valoracion secundarios y la seguridad se evaluaron a posteriori en distintos subgrupos del Sistema de Clasificacion de la Obesidad Edmonton (EOSS). Para ello, se asigno una puntuacion EOSS a los pacientes aleatorizados para recibir liraglutida 3,0 mg o placebo. Mas pacientes con diabetes tipo 2 (DM2) presentaron una puntuacion EOSS basal de 2 o 3, lo que indica mayor riesgo. Las medias de edad, peso, IMC y presion sistolica aumentaron con la puntuacion basal. De forma consistente en las distintas categorias EOSS, con liraglutida 3,0 mg se observo una mayor perdida de peso y mejorias en HbA1c, presion sistolica, lipidos y funcion fisica en la semana 56 versus placebo .En general, los efectos del tratamiento fueron independientes de las puntuaciones EOSS basales. Los eventos adversos y los eventos adversos graves fueron similares en las distintas categorias EOSS, concluyendo, por todo ello, que los efectos de liraglutida 3,0 mg y el perfil de seguridad fueron por lo general consistentes en las distintas puntuaciones EOSS basales.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.398
Teacher spread0.381 · 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
Published2018
Admission routes1
Has abstractyes

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