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Record W7052481128

Sleep Disturbances and Associated Factors in Drug-Naïve Patients with Parkinson’s Disease

2021· other· en· W7052481128 on OpenAlexaboutno aff

Bibliographic record

VenueDove Medical Press (Taylor and Francis Group) · 2021
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSleep disorderSleep (system call)Pittsburgh Sleep Quality IndexDepression (economics)AnxietyDiseaseQuality of life (healthcare)Cognition
DOInot available

Abstract

fetched live from OpenAlex

Min Zhong,1 Xu Jiang,1 Sha Zhu,1 Ruxin Gu,1 Yu Bai,2 Hong He,3 Yang Pan,1 Pingyi Xu,4 Jun Yan,1 Li Zhang1 1Department of Geriatric Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, People’s Republic of China; 2Department of Biological Sciences, University of Toronto Scarborough, Toronto, ON, Canada; 3School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, People’s Republic of China; 4Department of Neurology, First Affiliated Hospital of Guangzhou Medical University, Guangzhou, People’s Republic of ChinaCorrespondence: Li Zhang; Jun YanDepartment of Geriatric Neurology, Affiliated Brain Hospital of Nanjing Medical University, No. 264 Guangzhou Road, Nanjing, Jiangsu Province, 210029, People’s Republic of ChinaEmail neuro_zhangli@163.com; 815473709@qq.comPurpose: Sleep disturbance is one of the common symptoms in Parkinson’s disease (PD). The study of sleep disturbance used to concentrate on treated PD. This study aimed to investigate the factors that are associated with the sleep quality of drug-naïve patients with PD.Patients and Methods: All participants were interviewed using a standard questionnaire to collect basic information. PD severity, depression symptoms, anxiety symptoms, sleep quality, cognitive status, life quality, and the presence of rapid eye movement (REM) sleep behavior disorder (RBD) and minor hallucination were assessed using corresponding rating scales. The patients with a Pittsburgh Sleep Quality Index score ≤ 6 fell into the poor sleep group, and those with REM Sleep Behavior Disorder Screening Questionnaire score ≥ 5 were considered to have probable RBD.Results: Seventy drug-naive patients with PD and 30 healthy controls matched for age, sex, and education were recruited. Up to 41.4% of the patients suffered from sleep disturbance, and 24.3% of the patients had RBD. Poor sleepers were more likely to have left-side predominant motor symptoms. Compared with good sleepers, poor sleepers, particularly female patients, had more burden in the aspect of anxiety and depression. RBD was associated with more nonmotor symptoms, poor sleep quality, bad performance in cognition orientation domain, anxiety, depression, presence of minor hallucination, and poor life quality.Conclusion: Sleep disturbances are common in drug-naïve PD and require wide attention. Motor symptom laterality and gender difference in mood are associated with sleep quality. Depression, anxiety, and RBD are highly related to sleep disturbance. RBD has many comorbidities, which can influence the cognitive function and life quality of the patients.Keywords: Parkinson’s disease, drug naïve, sleep disturbance, REM sleep behavior disorder, depression, anxiety

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 score0.003
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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