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Estudo comparativo entre as técnicas de nissen e Boix-Ochoa em ratos

2007· article· pt· W2026676679 on OpenAlexaff
Karla F. Pinto, Saulo Marcos Rebello Ferrante, Ivonete Siviero, Ivens Baker Méio, Marcos Antônio Turcatel, Danielle Nunes Forny

Bibliographic record

VenueRevista do Colégio Brasileiro de Cirurgiões · 2007
Typearticle
Languagept
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsPhysicsMolecular biologyBiology

Abstract

fetched live from OpenAlex

OBJETIVO: Comparar, em ratos, a eficiência das técnicas de Nissen e Boix-Ochoa no tratamento do refluxo gastroesofagiano (RGE) induzido pela operação de Heller. MÉTODO: Foram usados 30 ratos Wistar, com idades entre 40 e 60 dias de vida e peso corporal entre 210 g e 342 g. Os animais foram distribuídos em três Grupos (A, B, C) de 10 ratos. Em todos os animais realizou-se a operação de Heller. No Grupo B ela foi seguida de uma operação de Nissen e, no Grupo C, de uma operação de Boix-Ochoa. A pressão intra-gástrica necessária para produzir RGE foi medida em todos os animais: antes de qualquer procedimento; imediatamente após as operações de Heller, Nissen e Boix-Ochoa; e seis semanas depois, quando os animais foram mortos. RESULTADOS: Verificou-se que tanto a recuperação da perda de peso, que caracteriza o quadro de RGE, como a reconstituição mais fisiológica dos gradientes pressóricos gastroesofagianos são obtidos de forma mais eficiente pela técnica de Boix- Ochoa. CONCLUSÃO: As operações de Nissen e Boix- Ochoa são eficientes no tratamento do RGE induzido pela técnica de Heller, em ratos. A segunda, no entanto, restaurou, de forma mais adequada, os valores fisiológicos dos parâmetros estudados neste trabalho: o peso corporal e os gradientes pressóricos gastroesofagianos.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.019
GPT teacher head0.330
Teacher spread0.310 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2007
Admission routes1
Has abstractyes

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