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Record W4416827897 · doi:10.1111/obr.70044

Transforming Treatment: The Impact of Bariatric Surgery on Oral Drug Absorption

2025· article· en· W4416827897 on OpenAlexaff
David R. Wigg, Andrea N. Edginton, Matthew Jones, Nikoletta Fotaki

Bibliographic record

VenueObesity Reviews · 2025
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsUniversity of Waterloo
FundersPharmacy Research UK
KeywordsDrugBioavailabilitySleeve gastrectomyPharmacokineticsObesityWeight lossBody mass indexLaparoscopy

Abstract

fetched live from OpenAlex

Obesity represents a significant threat to global public health, with an estimated 16% of adults worldwide (2022) being classified as people with obesity, with a body mass index of 30 or more. Bariatric surgery is regarded as the most effective treatment option for people with obesity, with the three main types of bariatric surgery being gastric bypass or Roux-en-Y gastric bypass, laparoscopic gastric band, and laparoscopic sleeve gastrectomy. Drug bioavailability after oral administration is affected by several factors including properties of the drug itself, formulation properties, and anatomical and physiological factors. Procedures such as gastric bypass and laparoscopic sleeve gastrectomy result in significant anatomical and physiological alterations thought to profoundly influence oral drug bioavailability postoperatively. Consequently, following bariatric surgery, there is a risk of subtherapeutic drug levels leading to treatment failure, or the risk of potential toxicity if levels are elevated. In this review, previously unexamined aspects such as the impact of the "very low-calorie diet" (VLCD) initiated prior to surgery on anatomical parameters and subsequent pharmacokinetic changes, are explored. This review also highlights alterations in hepatic and renal volume that are expected to have a significant impact on renal and hepatic clearance. A clearer understanding of the effect of physiological alterations and weight loss on drug performance after surgery would support more evidence-based medicines optimization in this frequently complex patient group.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.041
GPT teacher head0.327
Teacher spread0.286 · 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.

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
Published2025
Admission routes1
Has abstractyes

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