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Record W4387914087 · doi:10.2196/50677

The Effects of Reinforcement Techniques in Sleeve Gastrectomy and Roux-en-Y Gastric Bypass: Protocol for a Web-Based Survey, Systematic Review, and Meta-Analysis

2023· article· en· W4387914087 on OpenAlexvenueno aff
Yunhui Xie, Jun Wen, Hongmei Zhu, Yanjun Liu

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldMedicine
TopicBariatric Surgery and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisRandomized controlled trialProtocol (science)CINAHLSleeve gastrectomySubgroup analysisSurgeryAnastomosisGastric bypassWeight lossInternal medicinePsychological interventionAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The effects of reinforcement are still controversial in bariatric surgery, and variations may exist in using this technique. OBJECTIVE: This protocol describes a study that aims to survey the views of bariatric surgeons on reinforcement techniques and evaluate the effects of applying reinforcement techniques in sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). METHODS: This study is composed of 2 parts. Part 1 will investigate the differences of using reinforcement techniques among surgeons worldwide who perform SG or RYGB through a survey. The survey will be conducted by email and social media. Part 2 will evaluate the safety and effectiveness of using omentopexy or staple line reinforcement in SG and RYGB by systematic review and meta-analysis. In this part, literature searches will be performed in English databases, including CENTRAL, EMBASE CINAHL, Web of Science, and PubMed, and Chinese databases, including Wanfang, China National Knowledge Infrastructure, Database of Chinese Technical Periodicals, and Chinese Biological Medicine, from their establishment to November 2023. Randomized controlled trials and case-control studies will be included. The primary outcomes are rates of postoperative bleeding and gastric leakage. The secondary outcomes include anastomotic stenosis, surgical site infection, reoperation, estimated intraoperative blood loss, operative time (minutes), length of hospital stay (days), overall complications, and 30-day mortality. The meta-analysis will be conducted using RevMan 5.4 under the random-effects model, as well as through extensive subgroup and sensitivity analyses. P values <0.05 will be considered statistically significant. This study was registered with PROSPERO (Prospective Register of Systematic Reviews) in accordance with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols). RESULTS: The results of this study will be published in a peer-reviewed journal. The web-based survey and initial title or abstract review of papers identified by the search strategy will be completed in November 2023. The second round of title or abstract review and downloading of the papers for full-text inclusion will be completed in January 2024. We aim to complete data extraction and meta-analysis by February 2024 and expect to publish the findings by the end of March 2024. CONCLUSIONS: This study aims to investigate the impact of reinforcement techniques on reducing the incidence of postoperative complications in SG and RYGB procedures and provide assistance for standardizing the procedures of SG and RYGB operations for bariatric surgeons. TRIAL REGISTRATION: PROSPERO CRD42022376438; https://tinyurl.com/2d53uf8n. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50677.

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)0.055
metaresearch head score (Gemma)0.066
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.055
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0550.066
Meta-epidemiology (narrow)0.0050.004
Meta-epidemiology (broad)0.0160.023
Bibliometrics0.0100.010
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0030.004
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0420.005

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 head0.184
GPT teacher head0.522
Teacher spread0.338 · 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
GenreProtocol

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

Citations1
Published2023
Admission routes1
Has abstractyes

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