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Record W4309654449 · doi:10.17116/jnevro202212211230

Swimming disorders in Parkinson’s disease

2022· article· en· W4309654449 on OpenAlexaboutno aff
A.V. Kuzmina, И. Г. Смоленцева, О С Левин

Bibliographic record

VenueS S Korsakov Journal of Neurology and Psychiatry · 2022
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMovement disordersAnxietyDepression (economics)Parkinson's diseaseRating scaleEysenck Personality QuestionnaireDiseasePersonality disordersPhysical therapyHospital Anxiety and Depression ScaleMontreal Cognitive AssessmentPsychiatryCognitive impairmentInternal medicinePersonalityPsychologyBig Five personality traits

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate swimming disorders in patients with Parkinson's disease (PD). MATERIAL AND METHODS: During the pilot study, we examined 40 patients with PD, who were divided into two groups depending on the presence or absence of swimming disorders. The assessment on the Hoehn-Yahr scale in both groups ranged from 1 to 3. The severity of PD was assessed according to the unified Parkinson's disease scale of the International Society of Movement Disorders (MDS-UPDRS). The Montreal Cognitive Assessment Scale, the Hospital Scale of Anxiety and Depression, a new questionnaire of freezing when walking, a 6-minute walk test, the Eysenck Personality Questionnaire were administered. RESULTS: Of 40 patients with PD, 60% reported swimming disorders. No association was found between swimming disorders and the severity of motor symptoms of PD. At the same time, an increased level of anxiety was noted in the group of patients with swimming disorders. CONCLUSION: Further research is needed to study the mechanisms of the development of swimming disorders in PD.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.246
Teacher spread0.239 · 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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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Same venueS S Korsakov Journal of Neurology and PsychiatrySame topicParkinson's Disease Mechanisms and TreatmentsFrench-language works237,207