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Record W4399983588 · doi:10.3389/fnagi.2024.1399285

Correlation between motor function and health-related quality of life in early to mid-stage patients with Parkinson disease: a cross-sectional observational study

2024· article· en· W4399983588 on OpenAlexaboutno aff
Ying Ge, Wowa Zhao, Lu Zhang, Xiaoyi Zhao, Xuan Shu, Jiawei Li, Ying Liu

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2024
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBerg Balance ScaleQuality of life (healthcare)Balance (ability)Rating scalePhysical therapyParkinson's diseaseCross-sectional studyGaitTimed Up and Go testMetabolic equivalentSpearman's rank correlation coefficientPhysical medicine and rehabilitationStage (stratigraphy)Montreal Cognitive AssessmentDiseaseInternal medicinePsychologyPhysical activityCognitive impairment

Abstract

fetched live from OpenAlex

Aim To investigate the correlation between motor function and health-related quality of life (HrQOL) in early to mid-stage patients with Parkinson disease (PwP). Methods This cross-sectional study recruited PwP from April 2020 to December 2023 at the outpatient clinic of Peking Union Medical College Hospital in Beijing, China. The motor symptoms were assessed using Movement Disorder Society–sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) part 3. Balance function was evaluated using the Berg Balance Scale (BBS), and the risk of fall using Timed Up-and-Go test (TUG), and Five Times Sit-to-Stand test (FTSST). Freezing of gait questionnaire (FOGQ) was used to evaluate the severity of gait. The Intelligent Device for Energy Expenditure and Physical Activity (IDEEA) recorded gait cycle parameters, and the isokinetic dynamometer measured muscle strength. The Parkinson’s Disease Questionnaire-39 (PDQ-39) was used to measure HrQOL. All assessments were tested during the on state. Spearman correlation was conducted to evaluate the correlation between motor function and HrQOL. Results 243 patients with mean age of 69.33 years were enrolled. The PDQ-39 score was strongly correlated with FOG in H&Y stage III (r = 0.653, p < 0.001) and moderately correlated in H&Y stage I (r = 0.471, p < 0.001) and H&Y stage II (r = 0.386, p < 0.001). Furthermore, the FOG was strongly correlated with mobility domain at H&Y stage III (r = 0.694, p < 0.001) and moderately correlated at H&Y stage I (r = 0.431, p < 0.001) and H&Y stage II (r = 0.434, p < 0.001). All motor function scores were correlated with PDQ-39 scores at H&Y stage III (p < 0.05). Conclusion Motor function correlated with HrQOL in early to mid-stage PwP, and FOG was the main factor, especially affecting mobility, activities of daily life and communication. HrQOL in patients at different disease stages were variously affected by motor function, and HrQOL and multiple dimensions was significantly associated with motor function in patients at H&Y stage III.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.098
GPT teacher head0.388
Teacher spread0.290 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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