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Periodic limb movements among persons with epilepsy: A retrospective polysomnographic study

2025· article· en· W4414095788 on OpenAlexaff
Laurel Charlesworth, Helen S. Driver, Gavin P. Winston, Lysa Boissé Lomax, Garima Shukla

Bibliographic record

VenueEpilepsy Research · 2025
Typearticle
Languageen
FieldMedicine
TopicRestless Legs Syndrome Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsObstructive sleep apneaEpilepsyPolysomnographyCohortRetrospective cohort studySleep apneaSleep (system call)Lower limb

Abstract

fetched live from OpenAlex

INTRODUCTION: Persons with epilepsy (PWE) frequently contend with disrupted sleep related to multiple seizure related as well as other factors like medications and comorbidities. Such disturbances often lead to fragmented sleep, which can adversely affect quality of life and compromise seizure management. Previous Although previous research has addressed conditions like sleep apnea and insomnia among PWE, less attention has been paid to periodic limb movements (PLMs), a requirement for diagnosis of the periodic limb movement disorder and also commonly observed in restless legs syndrome (RLS) as well as other conditions. This study aims to determine the prevalence and specific features of PLMs in PWE and to explore how these movements correlate with objective sleep measurements. METHODS: This investigation employed a retrospective chart review of consecutive adult patients diagnosed with epilepsy who underwent polysomnography at a tertiary-care sleep laboratory over a ten-year span. The control group consisted of individuals evaluated for possible obstructive sleep apnea, who were matched to cases based on age, sex, and the severity of sleep apnea. Patient records were initially identified using keywords related to "epilepsy" or "seizures." Epilepsy diagnosis was confirmed through detailed chart review, which also yielded clinical details likety duration of epilepsy, seizure classification, and antiseizure medication usage. Sleep parameters such as sleep efficiency, spontaneous arousal index, periodic limb movement index, periodic limb movement with arousal index, and apnea-hypopnea index were extracted from archived polysomnography reports. The subsequent analysis was carried out using descriptive statistical methods using RStudio version 4.4.1. RESULTS: A total of 152 relevant patient records were found in the database. Of these, 61 patients with epilepsy (mean age 41.4 ± 17.2 years, including 31 females) met the inclusion criteria and were matched with 61 patients suspected for OSA. Within the epilepsy cohort, 43 patients experienced focal-onset epilepsy while 16 had generalized epilepsy. 25 patients were prescribed two or more antiseizure medications, and 12 were categorized as medically refractory. PLMs were detected in 23 % of patients with epilepsy compared to 26 % in the control group, with mean PLMI values of 6.1 ± 16.8 and 8.8 ± 20.7, respectively. The PLMAI was also similar between the two groups (0.5 ± 1.0 vs. 1.1 ± 2.4). Other sleep parameters, including the mean AHI (16.0 ± 20.0 in the epilepsy group vs. 19.7 ± 19.4 in the control group), did not exhibit significant differences between groups. Within the epilepsy cohort, the only factor linked to the presence of periodic limb movements was older age, with no observed association with seizure type, number of antiseizure medications, or seizure control. CONCLUSIONS: PLMs are a frequently observed phenomenon in polysomnographic studies of PWE and are predominantly related to advancing age. Given the comparable indices of periodic limb movements in both the epilepsy group and an age- and sex-matched cohort with obstructive sleep apnea, the findings suggest that obstructive sleep apnea might be a major contributor to the periodic limb movements seen among PWE.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.047
GPT teacher head0.389
Teacher spread0.343 · 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.

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
Published2025
Admission routes1
Has abstractyes

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