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Record W4410055091 · doi:10.1007/s10620-025-09074-z

Endoscopic Submucosal Dissection with Rubber Bands and Clips Compared to Conventional Endoscopic Submucosal Dissection: A Systematic Review and Meta-Analysis

2025· review· en· W4410055091 on OpenAlexaboutno aff
Abdelaziz A. Awad, Hazem Abosheaishaa, Malak A. Hassan, Mohamed Mahmoud Marey, Ahmed Bahnasy, Rashad G. Mohamed, M. Keshk, Yousef Radwan Alnomani, Manar A. Balouz, Fatma Saffeyeldin Mohamed, Mohammed A. Alaeb, Mohamed S. Sharaf, Omar T. Ahmed, Nigar Neknam, Sherif Andrawes

Bibliographic record

VenueDigestive Diseases and Sciences · 2025
Typereview
Languageen
FieldMedicine
TopicGastric Cancer Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsEndoscopic submucosal dissectionCLIPSTransplant surgeryMedicineHepatologyMeta-analysisDissection (medical)SurgeryRadiologyInternal medicine

Abstract

fetched live from OpenAlex

The rising number of gastrointestinal (GI) tumors, including esophageal, gastric, and colorectal tumors, makes it essential to develop more effective treatment methods. Endoscopic submucosal dissection (ESD) has become a popular intervention due to its ability to resect the tumor completely and prevent local recurrence. This study evaluates the safety and efficacy of ESD with rubber bands and clips (ESD-RBC) in the treatment of various GI tumors. We systematically searched Embase, Scopus, Web of Science, Medline/PubMed, and Cochrane databases until April 20, 2024. Eligible studies included clinical trials and observational studies focusing on ESD-RBC alone or compared to conventional ESD (C-ESD) in patients with gastrointestinal tumors. The risk of bias was assessed using the Newcastle–Ottawa Scale (NOS) tool. Statistical analyses were performed using RevMan and R software. ESD-RBC was superior to C-ESD in achieving R0 resection and en bloc resection (OR: 1.99 with 95% CI [1.17 to 3.36], P = 0.01, I 2 = 0%) and (OR: 5.98 with 95% CI [2.30 to 15.55]; P = 0.0002, I 2 = 0%), respectively. ESD-RBC enhanced the resection speed compared to C-ESD (MD: 8.48 mm 2 /min with 95% CI [3.12 to 13.83]; P < 0.00001, I 2 = 89%) and shortened the procedure duration (MD: − 11.94 min with 95% CI [− 21.98 to − 1.91]; P < 0.00001, I 2 = 7%). There was no statistically significant difference between both groups in terms of bleeding and delayed bleeding (OR: 1.08 with 95% CI [0.37 to 3.14]; P = 0.89, I 2 = 0%) and (OR: 0.69 with 95% CI [0.20 to 2.33]; P = 0.55, I 2 = 0%), respectively. The proportion of R0 resection using ESD-RBC was 90%, with 95% CI [65% to 98%] and I 2 = 78%. The en bloc resection rate was 96%, with 95% CI [95% to 97%], and I 2 = 0%. In addition, the raw mean (MRAW) of resection speed was 24.25 mm2/min, with 95% CI [13.48 to 35.02], and I 2 = 99.4%. ESD-RBC was superior to C-ESD in achieving en bloc resection and R0 resection with a comparable risk of bleeding and delayed bleeding. In addition, ESD-RBC enhanced the resection speed and shortened the procedure duration.

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)0.009
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.020
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0180.028
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.363
Teacher spread0.305 · 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 designMeta-analysis
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

Citations2
Published2025
Admission routes1
Has abstractyes

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