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Record W2330711757 · doi:10.4172/2155-6156.1000353

Modelling the Absorption of Metformin with Patients Post Gastric Bypass Surgery

2014· article· en· W2330711757 on OpenAlexaff
Raimar Löbenberg

Bibliographic record

VenueJournal of Diabetes & Metabolism · 2014
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of Alberta
FundersPrincess Nourah Bint Abdulrahman University
KeywordsMedicineMetforminDiabetes mellitusGastric bypassGastric bypass surgeryInternal medicineGastroenterologyPharmacologyEndocrinologyObesityWeight loss

Abstract

fetched live from OpenAlex

Purpose: Gastric bypass surgery in obesity shortens the length of the small intestine, which can have a significant impact on drug absorption.Literature reports that the observed drug absorption patterns after gastric bypass surgery are sometimes unexpected.One report states that the absorption of Metformin was higher after gastric bypass surgery.The purpose of this study was to investigate the mechanistic background of the reported data using Advanced Compartmental Absorption and Transit (ACAT™) model and apply it to patient data with post gastric bypass surgery.Methods: GastroPlus™ 8 (Simulations Plus, Inc.) was used to develop a model that describes the observed absorption of an immediate release (IR) metformin tablet in healthy subjects.The data was taken from a published article that compared the absorption of metformin between a control group and post gastric bypass surgery patients.The model was fitted against the data for the control group and then used to predict the drug absorption in post gastric bypass surgery patients by changing the related GI parameters.All assumptions to explain the observed data, suggested in the literature, were tested by changing the appropriate parameters in the software.Results: As theoretically expected, GastroPlus™ underestimated the absorption of metformin in patients with post gastric bypass surgery due to the lesser absorption area.The increase in the pore size and porosity of the last part of the small intestine successfully predict the observed PK parameters.Changing other speculated parameters failed to predict the observed absorption pattern. Conclusion:The simulation of the observed absorption of metformin in post gastric bypass surgery patient was found where there was a change in the metformin gut paracellular permeability.This indicates that the gut must have undergone an adoption process to compensate for the loss of parts of the small intestine.The insights gained by this study can be used to predict the absorption of other drugs that have similar physiochemical properties like metformin.Computer simulations can be used to simulate the impact and mechanistic background of disease or other physiological changes like surgery on drug absorption.Stomach Stomach Pouch Duodenum Jejunum Staples Esophagus Roux-En-Y Figure 1: Roux-en-Y gastric bypass (RYGB).

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.203
Teacher spread0.194 · 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 designSimulation or modeling
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

Citations19
Published2014
Admission routes1
Has abstractyes

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