MétaCan
Menu
Back to cohort
Record W4412410620 · doi:10.7759/cureus.87863

Early-Life Trauma as a Trigger for Developmental Myofascial Dysfunction: A Case Report

2025· article· en· W4412410620 on OpenAlexaff
Gillian Lauder, Jessica Y. Luo, Judith Nassaazi

Bibliographic record

VenueCureus · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMyofascial pain diagnosis and treatment
Canadian institutionsBC Children's HospitalCanadian Association of Nurses in OncologyUniversity of British Columbia
Fundersnot available
KeywordsMedicineMyofascial painPhysical medicine and rehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

Skeletal asymmetry is a major, unrecognized contributor to myofascial dysfunction and chronic pain in children and adolescents. myoActivation® is a novel medical intervention for the assessment of skeletal asymmetries and treatment of myofascial chronic pain. The therapeutic component of myoActivation involves a needling technique to release myofascial trigger points and scars. myoActivation restores normal mechanics, reduces pain, and improves balance. We report the case of an 18-month-old boy with a history of an asymmetrical gait and a diagnosis of mild developmental dysplasia of the hip, identified following a minor injury. He received trigger point injections to the muscles around his pelvis using myoActivation principles. An immediate improvement in symmetry was observed, resulting in improved gait, without a limp, and was also associated with a change in his hip X-rays. Based on these observations, myoActivation may be an effective assessment and therapeutic tool for other children with developmental myofascial dysfunction.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.002
Science and technology studies0.0040.002
Scholarly communication0.0030.002
Open science0.0020.003
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.286
Teacher spread0.271 · 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 designCase report
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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCureusSame topicMyofascial pain diagnosis and treatmentFrench-language works237,207