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Record W4309861879 · doi:10.2196/29713

Matched Endoscopic Sleeve Gastroplasty and Laparoscopic Sleeve Gastrectomy Cases: Formative Cohort Study

2022· article· en· W4309861879 on OpenAlexvenueno aff
Skye Marshall, Graeme Rich, Felicity Cohen, Asha Soni, Elisabeth Isenring

Bibliographic record

VenueJMIR Formative Research · 2022
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
FundersBond University
KeywordsMedicineSleeve gastrectomyCohortBody mass indexSurgeryAnxietyHospital Anxiety and Depression ScaleProspective cohort studyQuality of life (healthcare)Internal medicinePhysical therapyWeight lossObesityGastric bypass

Abstract

fetched live from OpenAlex

Background Bariatric weight-loss surgery rates are increasing internationally. Endoscopic sleeve gastroplasty (ESG) is a novel, minimally invasive endoscopic procedure thought to mimic some of the effects of a more common surgery, laparoscopic sleeve gastrectomy (LSG). Patient factors affecting procedural choice are unexplored. Objective This formative study aimed to determine the preoperative and early postoperative characteristics of adults matched for age, sex, and BMI who chose ESG versus LSG. Methods This prospective cohort study recruited ESG and matched LSG adults in Australia. Preoperative outcomes were medical history, glycemic biomarkers, blood lipids, liver function enzymes, albumin, blood pressure, hepatic steatosis index, the Gastrointestinal Symptom Rating Scale, the Impact of Weight on Quality of Life–Lite questionnaire, and body composition via dual-energy x-ray absorptiometry. Adverse events were recorded preoperatively and up to 2 weeks postoperatively. SPSS was used to test if there were differences between cohorts by comparing means or mean ranks, and binary regression was used to understand how characteristics might predict procedure choice. Results A total of 50 (including 25 ESG and 25 LSG) patients were recruited, who were primarily White (45/50, 90%) and female (41/50, 82%) with a mean age of 41.7 (SD 9.4) years. Participants had a mean of 4.0 (SD 2.2) active comorbid conditions, with the most common being nonalcoholic fatty liver disease (38/50, 76%), back pain (32/50, 64%), anxiety or depression (24/50, 48%), and joint pain (23/50, 46%). The LSG cohort had higher hemoglobin A1c (5.3%, SD 0.2%) than the ESG cohort (5%, SD 0.2%; P=.008). There was a 2.4 kg/m2 difference in median BMI (P=.03) between the groups, but fat and fat-free mass had no meaningful differences. Comparing the LSG and ESG groups showed that the LSG group had lower total quality of life (49.5%, SD 10.6% vs 56.6%, SD 12.7%; P=.045), lower weight-related self-esteem (10.7%, IQR 3.6%-25% vs 25%, IQR 17.9%-39.3%; P=.02), and worse abdominal pain (38.9%, IQR 33.3%-50% vs 53.9%, SD 14.2%, P=.01). For every percent improvement in weight-related self-esteem, the odds for selecting ESG increased by 4.4% (95% CI 1.004-1.085; P=.03). For every percent worsening in hunger pain, the odds for selecting ESG decreased by 3.3% (95% CI 0.944-0.990; P=.004). Conclusions There was very little evidence that Australian adults who chose an endoscopic versus surgical sleeve had different rates of comorbidities, body fat percentage, or weight-related quality of life. There was evidence against the test hypothesis, that is, there was evidence suggesting that lower self-esteem predicted choosing a more invasive sleeve (ie, LSG rather than ESG) Trial Registration Australia New Zealand Clinical Trials Registry ACTRN12618000337279; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374595

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.042
GPT teacher head0.376
Teacher spread0.334 · 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 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".

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Citations4
Published2022
Admission routes1
Has abstractyes

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