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Record W4384297431 · doi:10.1016/j.sleep.2023.07.011

Periodic leg movements during sleep and cognitive functioning in the older general population

2023· article· en· W4384297431 on OpenAlexaff
Nicola Andrea Marchi, Arton Peci, José Haba‐Rubio, Geoffroy Solelhac, Virginie Bayon, Mathieu Berger, Péter Vollenweider, Pedro Marques‐Vidal, Armin von Gunten, Marie‐Pierre F. Strippoli, Martin Preisig, Bogdan Draganski, Raphaël Heinzer

Bibliographic record

VenueSleep Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsCanadian Sleep & Circadian NetworkUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersChinese Society of Clinical OncologyUniversité de LausanneFondation LeenaardsGlaxoSmithKlineSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsCognitionPolysomnographyEffects of sleep deprivation on cognitive performanceDementiaCognitive skillAssociation (psychology)Cognitive declineMedicinePsychologyClinical psychologyPsychiatryInternal medicineDiseaseApnea

Abstract

fetched live from OpenAlex

OBJECTIVE: The current evidence of a relationship between periodic leg movements during sleep (PLMS) and cognitive functioning is limited and inconsistent. This cross-sectional study assessed associations between PLMS and cognitive functioning among community-dwelling older adults. METHODS: We included community-dwelling older adults who underwent a polysomnography and a cognitive assessment. The PLMS index (PLMI) and PLMS arousal index (PLMAI) were categorized into tertiles: PLMI <5/h (reference), 5-29.9/h, ≥30/h; and PLMAI <1/h (reference), 1-4.9/h, ≥5/h. The cognitive assessment consisted of ten scores covering the main cognitive domains: global cognition, processing speed, executive function, language, episodic verbal memory, and visuospatial function. Associations between PLMI, PLMAI, and cognitive scores were assessed using regression unadjusted and adjusted models. RESULTS: A total of 579 individuals without dementia were included (mean age: 71.5 ± 4.4 years; men 45.4%). The number of participants in the high-PLMI categories, 5-29.9/h and ≥30/h, was 185 (32.0%) and 171 (29.5%), respectively. Participants in the high-PLMI categories showed no significant difference compared to the reference group regarding their cognitive performance according to the unadjusted and adjusted models. Similarly, we found no association between PLMAI severity and cognitive functioning. CONCLUSIONS: This study shows no cross-sectional association between PLMS severity and cognitive functioning among community-dwelling older adults. However, given the paucity of data in this field, further studies are needed to clarify the relationship between PLMS and cognitive functioning.

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)0.001
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 score0.023
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.032
GPT teacher head0.333
Teacher spread0.301 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

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