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Record W4390033568 · doi:10.3390/children11010008

Effectiveness of the Treatment of Physiotherapy in the Congenital Muscular Torticollis: A Systematic Review

2023· review· en· W4390033568 on OpenAlexaboutno aff
Manuel Rodríguez-Huguet, Daniel Rodríguez‐Almagro, Miguel Ángel Rosety, María Jesús Viñolo-Gil, Carmen Ayala-Martínez, Jorge Góngora-Rodríguez

Bibliographic record

VenueChildren · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsTorticollisPhysical therapyPhysical medicine and rehabilitationMedicineSurgery

Abstract

fetched live from OpenAlex

A single congenital muscular torticollis (CMT) is a postural musculoskeletal deformity and is characterized by the shortening or stiffness of the sternocleidomastoid muscle. The reported incidence of CMT ranges from 0.2% to 2%. The objective is to evaluate the effect of physical therapy programs on CMT. For the search, PubMed, Scopus, Web of Science, PEDro and Cochrane databases were used. Randomized controlled trials published between 2018 and 2023 have been included. This study follows the PRISMA 2020 statement and has been registered in the PROSPERO database. Finally, six studies were included. The cervical range of motion (ROM) in rotation was the most analyzed variable, followed by the ultrasound evaluation; one of the studies included the analysis of children's motor development with the Alberta scale. All research found benefits associated with soft tissue mobilization, passive stretching techniques and manual therapy of the cervical spine. In conclusion, it is possible to recommend manual therapy and passive stretching techniques for the treatment of CMT, with significant results on the cervical ROM.

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)0.003
metaresearch head score (Gemma)0.012
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.006
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.326
Teacher spread0.312 · 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".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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