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Record W4281750005 · doi:10.1097/pxr.0000000000000162

Does thermoplastics' thickness influence joint stabilization and movement coordination? An inferential study of wrist orthoses

2022· article· en· W4281750005 on OpenAlexaff
Pedro Henrique Tavares Queiroz de Almeida, Bruno Batista Santos, Lilian Dias Bernardo, Joy C. MacDermid

Bibliographic record

VenueProsthetics and Orthotics International · 2022
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Surgery and Rehabilitation
Canadian institutionsWestern University
Fundersnot available
KeywordsWristOrthoticsRange of motionPhysical medicine and rehabilitationKinematicsForearmBiomechanicsElbowFlexibility (engineering)Task (project management)MedicineAnkleUpper limbPhysical therapyOrthodonticsComputer scienceSurgeryMathematicsAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND: Given the existence of multiple low-temperature thermoplastics, clinicians fabricating can readily modify an orthoses' thickness, weight and flexibility, among other properties. However, there is limited evidence on the impact of such different materials on upper extremities' biomechanics. OBJECTIVE: Our study aimed to investigate differences in joint stabilization and movement coordination provided by upper extremity orthotics fabricated with low-temperature thermoplastics of different thicknesses. STUDY DESIGN: Inferential, cross-sectional study. METHOD: We conducted a kinematic analysis of a standardized task through a three-dimensional motion capture system. Ten participants (5 female) performed the same task under three circumstances: 1) wearing a volar wrist immobilization orthosis, made with a 3.2-mm thick low-temperature thermoplastic; 2) using the same orthotic fabricated with a 1.6-mm thick material; and (3) without orthoses. We divided the standardized task into five logical phases for data analysis, obtaining the active range of motion of the shoulder, elbow, forearm, and wrist joints as the primary outcome. Secondary outcomes included movement smoothness and coordination, measured by the number of motor units, time, and distance travelled by the upper extremity. RESULTS: Despite changes in thermoplastic thickness, both orthotics significantly restricted the wrist motion during task performance (F(2,16) = 14.32, P < .01, and η2p = 0.797), with no difference between the 2 devices and no significant changes to proximal joints' active range of motion. Although orthoses use increased the time required for task performance (F(2,16) = 23.05, P < .01, and η2p = 0.742), no significant differences in movement smoothness or coordination were noted. CONCLUSION: Our results indicate that wrist orthoses fabricated with a 1.6-mm thick low-temperature thermoplastic can provide joint stabilization similar to a device made from a 3.2-mm thickness material, suggesting thinner thermoplastics' efficacy to stabilize joints in the absence of contractures or preexisting chronic conditions.

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)0.011
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.273
Teacher spread0.260 · 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 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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