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Record W4414461866 · doi:10.4103/jpbs.jpbs_1054_25

Efficacy of Remote Electrical Neuromodulation (REN) on Migraine-Induced Neuronal Activity: A Systematic Review

2025· review· en· W4414461866 on OpenAlexaboutno aff
Prabu Nagarathinam Poosai, Sumit Sharma, Gunjan Singh Aswal, P. Sai Archana

Bibliographic record

VenueJournal of Pharmacy And Bioallied Sciences · 2025
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyNeuromodulationRandomized controlled trialMigraineSystematic reviewPlaceboData extractionMEDLINE

Abstract

fetched live from OpenAlex

This systematic review evaluated the efficacy of Remote Electrical str Neuromodulation (REN) in migraine-induced neuronal activity. A PubMed and Google Scholar search identified studies published between 2007 and 2025. Inclusion criteria focused on randomized controlled trials, open-label studies, and real-world observational studies that evaluated REN for migraine treatment. Duplicate reports and studies with insufficient information were excluded. Data extraction and quality assessment followed preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and the Newcastle-Ottawa Scale. The results showed that 10 peer-reviewed studies were included (4 Randomized Controlled Trials [RCTs], 4 open-label studies, and 2 real-world observational studies). REN demonstrated significant improvements in pain freedom and pain relief at 2 hours compared to placebo (pain freedom: 41-46% vs. 20-25%, pain relief: 59-67% vs. 35-42%). Patients treated with REN also showed significant reductions in migraine attacks and improved daily functioning. REN was well-tolerated, with minimal side effects, primarily mild local paresthesia or skin sensitivity. The majority of RCTs had low risk of bias, though observational studies exhibited a higher risk. It was concluded that REN may serve as a valuable nonpharmacologic option for migraine management.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.426
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.157
GPT teacher head0.422
Teacher spread0.266 · 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 teacher head, 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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