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Record W2509926797 · doi:10.1002/bem.22001

Analgesic effect of repetitive transcranial magnetic stimulation (rTMS) in patients with chronic low back pain

2016· article· en· W2509926797 on OpenAlexaboutno aff
Mónica Ambriz‐Tututi, Beatriz Alvarado‐Reynoso, René Drucker-Colı́n

Bibliographic record

VenueBioelectromagnetics · 2016
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTranscranial magnetic stimulationAnalgesicMedicineStimulationPhysical medicine and rehabilitationDeep transcranial magnetic stimulationAnesthesiaPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

The objective of the present study was to assess the benefits of 1-week repetitive transcranial magnetic stimulation (rTMS) in patients with chronic low back pain (LBP). The visual analogue scale (VAS), Short Form McGill pain questionnaire (SF-MPQ), and Short Form 36 Health Survey were used to evaluate the effect of this treatment. Eighty-two patients diagnosed with LBP were divided randomly into three groups: rTMS-treated group, sham group, and physical therapy-treated group. We observed a significant reduction in VAS and SF-MPQ scores in the rTMS-treated group, but not in the sham group. Moreover, patients who received rTMS had a lower mean pain score than patients treated with physical therapy. Our study suggests that rTMS produces safe, significant, and long-term relief in patients with LBP without evident side effects. This study shows for the first time that long-term repeated sessions of rTMS decrease pain perception of LBP. Bioelectromagnetics. 37:527-535, 2016. © 2016 Wiley Periodicals, Inc.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.208
Teacher spread0.203 · 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 designNon-randomized trial
Domainnot available
GenreEmpirical

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

Citations52
Published2016
Admission routes1
Has abstractyes

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