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Record W4300955091

Effects of Physiotherapy and Occupational Therapy in A Case with Winchester Syndrome

2013· article· en· W4300955091 on OpenAlexaboutno aff
Songül ATASAVUN UYSAL, İ. Alemdaroğlu, Öznur Yılmaz, Hülya Kayıhan, Aynur Ayşe Karaduman

Bibliographic record

VenueDergiPark (Istanbul University) · 2013
Typearticle
Languageen
FieldMedicine
TopicTumors and Oncological Cases
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyPhysical therapyMedicinePhysical medicine and rehabilitation
DOInot available

Abstract

fetched live from OpenAlex

Purpose: The aim of this study was to investigate the effects of physiotherapy and occupational therapy in a case with Winchester syndrome. Material and methods: In this report, 13 years old boy with Winchester Syndrome and physical and occupational therapy approaches were presented. Kamakura’s Hand Grips Evaluation Method, Canadian Occupational Performance Measure were used to assess hand ability and performance in daily living activities. Duration of writing sentences and hand functions were assessed by Jebsen Taylor Hand Function Test. Fine motor skills were assessed by using the fine motor skills’ subtests of Bruininks- Oseretsky Motor Proficiency Test, activities of daily living by Functional Independence Measurement for children (Wee-FIM), and quality of life by Child Assessment of Health Questionnaire (CHAQ). The range of motions and posture analysis of the subject were also examined. Exercise and activity trainings that included physiotherapy and occupational therapy approaches were planned to increase physical functions and ability in motor skills and performed 3 days in a week during six months regularly. Results: The range of motions of joints, independency level in daily living activities and quality of life of the subject were improved obviously after trainings. conclusion: It is concluded that physiotherapy and occupational therapy approaches may be one of the important supportive therapeutic options for the cases with Winchester Syndrome

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)0.000
metaresearch head score (Gemma)0.000
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 score0.171
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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