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Record W4392473940 · doi:10.1080/02703181.2024.2324334

The Effectiveness of Intensive Interdisciplinary Rehabilitation in a Patient with Multiple System Atrophy – Parkinsonian Subtype: A Case Report

2024· article· en· W4392473940 on OpenAlexaffabout
Alexander Gasser, McKyla McIntyre

Bibliographic record

VenuePhysical & Occupational Therapy In Geriatrics · 2024
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsRehabilitationAtrophyPhysical medicine and rehabilitationMedicinePhysical therapyPsychologyPathology

Abstract

fetched live from OpenAlex

Aims Multiple system atrophy (MSA) is a progressive neurodegenerative disorder with poor prognosis. This case report presents the first interdisciplinary rehabilitation program for a patient with the Parkinsonian subtype of MSA (MSA-P).Methods A 68-year-old male who was diagnosed with clinically probable MSA-P was transferred to a Canadian-based rehabilitation center. He participated in an intensive interdisciplinary program over 36 days, with goal-directed rehabilitation from a physiotherapist, occupational therapist, and speech language pathologist, including remediation, compensation and education.Results From admission to discharge, he made substantial improvements in Berg Balance Scale (BBS) score (14/56 to 30/56), Functional Independence Measure (FIM) score (61 to 75), dominant hand dexterity, communication, and development of safe swallowing strategies.Conclusion This case supports a short-term, intensive-based interdisciplinary approach for the MSA-P population to provide educational value to patients and their caregivers, to develop compensation strategies, and to achieve functional improvement which translates to community living.

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 score0.350
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.310
Teacher spread0.297 · 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
Published2024
Admission routes2
Has abstractyes

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