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Record W1964781220 · doi:10.1503/cjs.001313

Endoscopic management of gastric band erosions: a 7-year series of 14 patients

2014· article· en· W1964781220 on OpenAlexvenueno aff
Ümit Doğan, Mustafa Akın, Serkan Yalakı, Atilla Akova, Cengiz Yılmaz

Bibliographic record

VenueCanadian Journal of Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdjustable gastric bandSurgeryEndoscopyComplicationGastric bandingLaparotomyGastric bypassWeight lossInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Intragastric band migration is an unusual but major complication of gastric banding. We review our experience with endoscopic removal of eroded gastric bands. METHODS: We retrospectively evaluated the cases of 110 morbidly obese patients who underwent adjustable gastric banding between 2005 and 2012 to identify those who experienced band erosion. To remove the migrated band, we used an endoscopic approach with a Gastric Band Cutter. RESULTS: Band or tube erosion occurred in 14 patients (12.7%). The median time interval from the initial gastric band placement to the diagnosis of band erosion was 32 (range 18-52) months. Upper abdominal pain, port site infection, loss of restriction and weight regain were the most common symptoms. We used the Gastric Band Cutter to remove the band endoscopically. It was able to cut the band successfully in all but 1 patient, in whom twisting of the cutting wire required conversion from endoscopy to laparotomy. In 2 patients, the band, after being cut, was locked in the gastric wall and required laparotomic removal. In 1 patient, we performed surgery for intragastric penetration of the connecting tube broken close to the band. CONCLUSION: The Gastric Band Cutter was successful in dividing the band in all but 1 patient, although we could not always complete the procedure endoscopically. Endoscopic removal seems to be effective and safe for band erosion.

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 score0.006
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.215
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 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

Citations19
Published2014
Admission routes1
Has abstractyes

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