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Record W2398040722

The Effect of Intramuscular Electrical Stimulation in Myofascial Pain Syndrome

2002· article· en· W2398040722 on OpenAlexaboutno aff
Myoung-Hwan Ko, Hwan-Taek Byeon, Jeong‐Hwan Seo, Yunhee Kim

Bibliographic record

VenueAnnals of Rehabilitation Medicine · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsIMesDry needlingMedicineVisual analogue scaleMyofascial painMyofascial pain syndromeAnesthesiaDorsumStimulationPhysical therapyInternal medicineAcupuncture
DOInot available

Abstract

fetched live from OpenAlex

Objective: This study was conducted to assess the effect of intramuscular electrical stimulation (IMES) and compared it with that of transcutaneous electrical nerve stimulation (TENS) and dry needling in the patients with myofascial pain syndrome (MPS). Method: Forty five patients with MPS was assigned randomly to TENS group (n=15), dry needling group (n=15) and IMES group (n=15). In TENS group, TENS was applied to the trigger point. In dry needling group, dry needling was applied to the trigger point. In IMES group, IMES was applied to the trigger point. Duration of treatment was 2 weeks. Effects were assessed before treatment, 1 day, 3 days, 7 days and 14 days after treatment by visual analogue scale (VAS) and McGill pain questionnaire (MPQ). Thermography was performed before treatment, 7 days and 14 days after treatment. Results: Significant change of VAS improvement ratio was noticed in IMES group from the 1 day after treatment compared with other groups. Significant change of MPQ improvement ratio was noticed in IMES group from the 3 days after treatment compared with other groups. The skin temperature difference was significantly improved in IMES group at 14 days after treatment. Conclusion: These results showed that IMES is effective treatment method for pain control in patients with MPS.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.306
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.293
Teacher spread0.281 · 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 designObservational
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

Citations1
Published2002
Admission routes1
Has abstractyes

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