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Record W3208867123 · doi:10.1093/pch/pxab061.089

109 Effectiveness of Neuromuscular Electrical Stimulation for Children with Dysphagia: A Systematic Review

2021· review· en· W3208867123 on OpenAlexaffabout
Roni Propp, Peter J. Gill, Sherna Marcus, Lily Ren, Eyal Cohen, Jeremy Friedman, Sanjay Mahant

Bibliographic record

VenuePaediatrics & Child Health · 2021
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsDysphagiaMedicineSwallowingCINAHLMEDLINEPhysical therapyOropharyngeal dysphagiaRandomized controlled trialPsycINFOCochrane LibraryObservational studyPediatricsPhysical medicine and rehabilitationSurgeryPsychological interventionInternal medicine

Abstract

fetched live from OpenAlex

Abstract Primary Subject area Complex Care Background Dysphagia is common in children with medical complexity and can result in undernutrition, respiratory complications and negatively impact child and caregiver quality of life; however, evidence on the effectiveness of treatments for dysphagia in children is limited. Neuromuscular electrical stimulation (NMES) is a novel proposed treatment for dysphagia where electrical current is applied to neck muscles using cutaneous electrodes during swallowing therapy. It is hypothesized that NMES improves dysphagia by strengthening swallowing muscles and/or enhancing sensory signals of the swallowing response. Objectives To systematically review the evidence on the effectiveness of NMES for treatment of oropharyngeal dysphagia in children. Design/Methods MEDLINE, EMBASE, PsycINFO, CINAHL, CENTRAL and Scopus databases were searched from inception to November 2020. Studies of children (18 years and younger) diagnosed with oropharyngeal dysphagia using NMES in the throat/neck region were included. Screening, data extraction, and risk of bias assessment followed PRISMA guidelines. Risk of bias was assessed using the Cochrane Collaboration’s tool for RCTs and the Newcastle-Ottawa tool for observational studies. [Registration: PROSPERO CRD42019147353] Results Of the 844 records screened, 26 were identified for full text review, and 8 studies were included (4 RCTs and 4 cohort studies). These studies represented 338 children, with a mean (or median) age below 7 years, including children with and without neurological impairments. In all studies, swallowing function as measured by imaging studies improved after NMES treatment; in the trials, the standardized mean difference ranged from 0.32 (95% CI -0.56, 1.20) to 1.18 (95% CI 0.40, 1.97) compared to control groups who received usual care without NMES. Seven of eight studies reported on the child’s feeding ability, and, with one exception, there was improvement in feeding ability (Figure 1). Few studies reported on health status (N=1), child’s quality of life (N=1), and adverse events and harms (N=1). No studies reported on the social impact on the child, impact on the caregiver, and the caregiver’s quality of life. In most studies, outcome follow-up was limited to less than 6 months. Overall, the studies demonstrated moderate to high risk of bias. A pooled intervention effect and meta-analysis was not conducted due to clinical heterogeneity. Conclusion NMES treatment may be beneficial in improving swallowing function for children with dysphagia, however, given the quality of the studies, inadequate outcome reporting, and short follow-up duration, additional well-designed RCTs are needed to establish its effectiveness.

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)0.006
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.008
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.034
GPT teacher head0.410
Teacher spread0.376 · 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 designSystematic review
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".

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Citations0
Published2021
Admission routes2
Has abstractyes

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