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Record W4386949948 · doi:10.35366/112646

Impacto del bypass gástrico en Y de Roux como tratamiento de reflujo gastroesofágico en pacientes con obesidad en un centro de tercer nivel

2023· article· es· W4386949948 on OpenAlexaff
Miguel Ángel Medina Medrano, Salvador Medina González, Diana Gabriela Maldonado Pintado, María Angélica Maldonado Vázquez, Luis Antonio Romano Bautista, Diego Adrián Vences Anaya, Javier Alvarado Durán, Federico Armando Castillo González

Bibliographic record

VenueActa Médica Grupo Ángeles · 2023
Typearticle
Languagees
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsImpact
Fundersnot available
KeywordsMedicineHumanitiesRoux-en-Y anastomosisGastric bypassObesityInternal medicineWeight loss

Abstract

fetched live from OpenAlex

Introducción: la obesidad es el principal factor de riesgo modificable para el desarrollo de enfermedades crónicas, incluyendo reflujo gastroesofágico (RGE).México es el país con la prevalencia más alta de sobrepeso (43.9%) en Latinoamérica.El RGE afecta a un tercio de la población general y hasta 70% de los pacientes con obesidad.El bypass gástrico en Y de Roux (BGYR) ha demostrado ser altamente efectivo en pacientes con obesidad severa y RGE, con 97% de remisión de síntomas; este estudio busca demostrar el impacto que tiene el BGYR sobre el RGE, en pacientes con obesidad, que no responden a un tratamiento convencional.Material y métodos: estudio retrospectivo, observacional, analítico con base en expedientes clínicos de pacientes con obesidad y RGE sometidos a BGYR.Resultados: se estudiaron 84 pacientes con RGE y obesidad, con lo que se obtuvo una remisión clínica de hasta 89.7% (p < 0.001), una disminución del grado de esofagitis por hallazgo endoscópico (p < 0.001) y del reflujo a través del esofagograma (p < 0.039) posterior a un año del BGYR.Conclusión: el BGYR es una herramienta útil en el tratamiento de RGE en pacientes con obesidad refractarios a tratamiento convencional, con remisión clínica de sintomatología.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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.

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
Published2023
Admission routes1
Has abstractyes

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