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Record W4406852084 · doi:10.1142/s1013702525710015

Ataxia telangiectasia in a Bahraini child treated with intensive physiotherapy: A case report

2025· article· en· W4406852084 on OpenAlexaff
Fatima Razzaqi, Aysha Albastaki, Israa Sinan

Bibliographic record

VenueHong Kong Physiotherapy Journal · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsCanadore College
Fundersnot available
KeywordsMedicineAtaxiaAtaxic GaitBalance (ability)Ataxia-telangiectasiaPhysical therapyAtrophyPediatricsTelangiectasiaPhysical medicine and rehabilitationGaitSurgeryInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Ataxia telangiectasia (AT) is a rare neurodegenerative condition with a prevalence of 1 in 40,000 to 1 in 300,000 worldwide. It involves a genetic mutation of chromosome 11q.26. The condition is inherited in an autosomal recessive manner causing atrophy of the cerebellum due to loss of Purkinje fibres. AT presents early in childhood and the clinical features depend on the type of mutation. The study is a case report of a rare genetic disorder of a 9-year-old female who came to the physiotherapy clinic with a diagnosis of AT. The patient was presented with progressively worsening gait problems with frequent falls, with complete dependence on assistance and impaired balance and coordination. The treatment program was 12 months divided into an intense physiotherapy program for two months followed by 10 months of two times per week of physiotherapy sessions. The program was divided into four elements which are: (1) Lifestyle changes, (2) Strengthening exercises, (3) Coordination exercises, and (4) Balance training exercises. The result showed a positive outcome in increasing the patient's independence, increased muscle strength, reduced ataxia symptoms intensity, and the patient can carry out complex activities with the help of accessory orthosis devices.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

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 head0.005
GPT teacher head0.276
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 teacher head, not a consensus.

Study designBench or experimental
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

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