MétaCan
Menu
Back to cohort
Record W2007571836 · doi:10.1503/cjs.030612

The effect of bariatric surgery on gastroesophageal reflux disease

2014· review· en· W2007571836 on OpenAlexaffvenue
Mustafa El-Hadi, Daniel W. Birch, Richdeep S. Gill, Shahzeer Karmali

Bibliographic record

VenueCanadian Journal of Surgery · 2014
Typereview
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsGERDMedicineWeight lossRefluxDiseaseObesityIncidence (geometry)SurgerySleeve gastrectomyBody mass indexRoux-en-Y anastomosisObesity SurgeryGastric bypassGastroenterologyInternal medicineGeneral surgery

Abstract

fetched live from OpenAlex

Obesity is an epidemic that is known to play a role in the development of gastroesophageal reflux disease (GERD). Studies have shown that increasing body mass index plays a role in the incompetence of the gastroesophageal junction and that weight loss and lifestyle modifications reduce the symptoms of GERD. As a method of producing effective and sustainable weight loss, bariatric surgery plays a major role in the treatment of obesity. We reviewed the literature on the effects of different types of bariatric surgery on the symptomatic relief of GERD and its complications. Roux-en- Y gastric bypass was considered an effective method to alleviate symptoms of GERD, whereas laparoscopic sleeve gastrectomy appeared to increase the incidence of the disease. Adjustable gastric banding was seen to initially improve the symptoms of GERD; however, a subset of patients experienced a new onset of GERD symptoms during long-term follow-up. The literature suggests that different surgeries have different impacts on the symptomatology of GERD and that careful assessment may be needed before performing bariatric surgery in patients with GERD.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.295
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations121
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of SurgerySame topicBariatric Surgery and OutcomesFrench-language works237,207