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Record W4403588913 · doi:10.2196/55870

Efficacy of Electroacupuncture in the Treatment of Mild to Moderate Female Stress Urinary Incontinence: Protocol for a Systematic Review and Network Meta-Analysis

2024· article· en· W4403588913 on OpenAlexvenueno aff
JiaNi Shi, Peiqi Li, Yuchen Zhang, Bin Xiao

Bibliographic record

VenueJMIR Research Protocols · 2024
Typearticle
Languageen
FieldMedicine
TopicPelvic floor disorders treatments
Canadian institutionsnot available
Fundersnot available
KeywordsUrinary incontinencePreprintElectroacupunctureMedicineProtocol (science)Meta-analysisBathingAcupuncturePhysical therapyPsychologyAlternative medicineUrologyComputer scienceWorld Wide WebInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Stress urinary incontinence (SUI), the most common form of urinary incontinence, is a condition that affects many women. It is characterized by involuntary urine leakage during activities that increase abdominal pressure, such as sneezing, coughing, or physical exertion, according to the International Continence Society. SUI affects patients' quality of life and causes depression and emotional disorders, which negatively influences physical and mental health. The participants in the studies in this review comprised women with mild to moderate SUI, because there are more female patients than male patients, and most patients with severe SUI are treated surgically. Moreover, after retrieval, there were no systematic reviews or network meta-analyses (NMAs) of conservative treatments, such as electroacupuncture (EA), in women with mild to moderate SUI. OBJECTIVE: This study aims to investigate the efficacy of electroacupuncture among women with mild to moderate SUI using an NMA. METHODS: Randomized clinical trials related to conservative treatments for SUI will be searched in 5 English and 3 Chinese literature databases: EMBASE, PubMed, Cochrane, Web of Science, ClinicalTrials.gov, Chinese National Knowledge Infrastructure (CNKI), WanFang, and the Chinese BioMedical Literature Database. The search period for these 8 electronic databases will be from 2002 to 2022. The PROSPERO database and the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) database will also be searched. Two reviewers will independently complete the research selection. After screening the studies, 2 other researchers will extract the data, and the quality of the included studies will be evaluated according to the quality standards specified in the Cochrane Collaboration Tool (version 2). The primary outcomes will be the change in urine leakage determined by a 1-hour pad test and International Consultation on Incontinence Questionnaire Short Form (ICIQ-SF) scores at baseline and at the conclusion of the follow-up. The secondary outcomes will be 72-hour incontinence episodes, residual bladder volume, effective rate, urodynamic indexes, and other reported measurements. Stata (version 14.0; StataCorp) and Review Manager (RevMan version 5.3; Cochrane) will be implemented for data synthesis and meta-analysis. RESULTS: The results are not yet accessible because this is a protocol for a systematic review and meta-analysis. The protocol was registered on INPLASY on February 22, 2023. By April 6, 2023, we had completed the literature search of the 8 databases and completed the selection and data extraction of the articles. CONCLUSIONS: The results of this systematic review will demonstrate the efficacy of EA among women with mild to moderate SUI. The results will provide evidence for clinicians and guideline makers to choose suitable treatments for SUI. TRIAL REGISTRATION: International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) 202320098; https://inplasy.com/inplasy-2023-2-0098/. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55870.

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)0.046
metaresearch head score (Gemma)0.065
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.046
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.065
Meta-epidemiology (narrow)0.0060.004
Meta-epidemiology (broad)0.0220.032
Bibliometrics0.0080.008
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0040.004
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0460.003

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 head0.261
GPT teacher head0.550
Teacher spread0.289 · 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
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

Citations3
Published2024
Admission routes1
Has abstractyes

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