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Biomechanical Outcomes Related with Gait in Children with Cerebral Palsy Using Ankle-Foot Orthotic - A Systematic Review

2019· review· en· W2939971755 on OpenAlexaff
Jessica Jorge Gordo, Paula Pascoal‐Faria, Artur Mateus, Pedro Morouço, Verónica Schiriati, Sandra Amado

Bibliographic record

VenueApplied Mechanics and Materials · 2019
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Victoria
FundersFundação para a Ciência e a TecnologiaPan African Materials InstituteAgência Nacional de Inovação
KeywordsGaitCadenceCerebral palsyPhysical medicine and rehabilitationAnkleGait analysisMedicinePhysical therapyOrthoticsPopulationFoot (prosody)Surgery

Abstract

fetched live from OpenAlex

Gait in children with cerebral palsy (CP) is often affected by motor impairments which limit the patient's ability to walk. To improve gait and reduce walking limitations, children with CP need to use ankle foot orthoses. An orthosis is an externally applied device that is designed and fitted to the body to achieve one or more of the following goals: a) Control biomechanical alignment. b) Correct or accommodate deformity, and 3) Protect and support an injury. This systematic review aims to describe research evidence supporting the use of ankle-foot orthoses to improve gait biomechanical outcomes among individuals with CP. Literature search was pursued from PubMed database. Studies were included if (1) they evaluated an outcome measure related with gait using ankle-foot orthotic (AFO) in children (2) considered children with a diagnosis of CP and have a (3) GMFCS classification of I, II or III. Papers were excluded if they evaluated (1) other population besides CP, (2) the use of orthoses other than AFOs and (3) gait analysis procedure was not presented. All the included studies have analyzed spatiotemporal parameters, the step length (m), stride length (m) and cadence (steps/minute) were the most frequently reported. Our findings showed that several studies have investigated the effects of AFOs, all of which have reported positive influences on at least one gait parameter, as well as positive changes in joint kinematics and kinetic in children with CP.

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)0.002
metaresearch head score (Gemma)0.013
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
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.006
Bibliometrics0.0080.008
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.288
Teacher spread0.258 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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