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Enregistrement W4407115963 · doi:10.1093/sleep/zsaf028

Strengthening the link between periodic leg movements during sleep and cerebral small vessel disease

2025· letter· en· W4407115963 sur OpenAlexaff
Raffaele Ferri, Giuseppe Lanza, Maria P. Mogavero

Notice bibliographique

RevueSLEEP · 2025
Typeletter
Langueen
DomaineMedicine
ThématiqueRestless Legs Syndrome Research
Établissements canadiensSurgical Specialties (Canada)
Organismes subventionnairesnon disponible
Mots-clésSleep (system call)Physical medicine and rehabilitationMedicineLink (geometry)DiseasePsychologyInternal medicineComputer science

Résumé

récupéré en direct d'OpenAlex

Sleep disruptions, especially periodic leg movements during sleep (PLMS), have long been implicated in cardiovascular and cerebrovascular conditions, albeit with mixed evidence. The recent study by Veitch et al. [1] presents a compelling exploration of the association between PLMS and cerebral small vessel disease (CSVD), focusing on patients with first-ever stroke or transient ischemic attack (TIA). By leveraging a larger cohort and refining methodologies, the study not only reinforces the link between PLMS and markers of CSVD but also opens new avenues for clinical and research discourse. The study stands out by addressing key limitations in prior research, including small sample sizes and inadequate control for confounding variables. With 86 participants, this research is the largest of its kind to investigate PLMS in the context of CSVD. The authors used validated imaging markers, including Fazekas and age-related white matter changes scale (ARWMC) scores, to measure white matter hyperintensities (WMHs) and other CSVD indicators. Importantly, the incorporation of age- and sex-specific PLMS index cutoffs represents a methodological innovation that ensures more precise classification of abnormal PLM activity. Unlike earlier studies, the authors adjusted for a broad spectrum of vascular risk factors, such as hypertension, diabetes, and obstructive sleep apnea (OSA), enhancing the robustness of their findings. This rigorous approach allowed them to isolate the impact of PLMS on WMHs, distinguishing it from confounding influences like OSA. Their findings—PLMS independently predicted higher WMH burden—add a crucial piece to the puzzle of how nocturnal physiological disruptions contribute to cerebrovascular pathology. The relationship between PLMS and CSVD has been a topic of ongoing debate. Previous studies [2, 3] suggested an association between elevated PLMS and CSVD markers, including WMHs, lacunar infarcts, and enlarged perivascular spaces (PVSs). However, these studies often lacked statistical adjustments for comorbidities, limiting the generalizability of their conclusions. Conversely, studies like those by Manconi et al. [4] and Del Brutto et al. [5] reported no significant association, underscoring the need for larger, well-controlled analyses. Veitch et al.’s study [1] bridges this gap by demonstrating consistent associations between PLMS and WMHs, even after controlling for potential confounders. This consistency aligns with the hypothesis that PLMS, through mechanisms such as nighttime sympathetic overactivity and systemic inflammation, may exacerbate endothelial damage and cerebrovascular dysregulation. One of the study’s strengths lies in its discussion of potential mechanisms linking PLMS and CSVD. The authors highlight that PLMS may disrupt sleep architecture, particularly slow-wave sleep, which is critical for neurovascular health. By impairing glymphatic clearance and exacerbating oxidative stress, PLMS could contribute to WMH development. Alternatively, the reverse causality hypothesis—wherein existing CSVD disrupts neural circuits governing motor activity—cannot be excluded. PLMS have been linked to significant autonomic fluctuations during sleep, including transient increases in heart rate [6, 7] and blood pressure (BP) [8, 9], contributing to nighttime sympathetic overactivity. For instance, reported elevated plasma nitric oxide levels in patients with PLMS suggest endothelial dysfunction mediated by recurrent cardiovascular stress [10]. Similarly, higher nocturnal BP has been reported in individuals with frequent PLMS [11], underscoring their potential role in promoting vascular strain and exacerbating cerebrovascular disease. These repeated hemodynamic changes may lead to long-term consequences, such as impaired vascular compliance and small vessel damage [12], highlighting the need for further investigation into their role in CSVD progression. Cerebral hemodynamic changes associated with PLMS have also been studied using advanced imaging techniques such as near-infrared spectroscopy (NIRS). NIRS has provided insights into the relative changes in cerebral oxygenation and perfusion during PLMS. Studies with NIRS demonstrated that PLMS disrupt regional cerebral oxygenation and autoregulatory capacity, further linking these movements to vascular dysregulation [13–15]. This impaired autoregulation may exacerbate the burden of CSVD by contributing to endothelial damage, WMHs, and other markers of CSVD [16]. Future studies leveraging NIRS and other imaging modalities could provide a deeper understanding of the temporal relationship between PLMS, cerebrovascular dysfunction, and associated clinical outcomes. Furthermore, medications such as antidepressants—particularly selective serotonin reuptake inhibitors—may play a significant role in exacerbating sleep-related motor disturbances, including PLMS. Antidepressants have been shown to increase chin muscle tone across all sleep stages [17], and their potential contribution to PLMS, as highlighted by a meta-analysis linking antidepressant use with increased PLMS [18], warrants further investigation. Future studies should focus on disentangling the effects of these medications from the underlying pathophysiological mechanisms driving PLMS. Additionally, the duration of the presence of PLMS may be a critical factor in their impact on cerebrovascular health, as Ferri et al. [19] emphasized the challenges in assessing this variable in studies exploring the relationship between PLMS, restless legs syndrome (RLS), and silent CSVD. Despite these advances, the study leaves critical questions unanswered. For instance, it remains unclear whether treating PLMS can mitigate WMH progression or improve clinical outcomes in stroke/TIA patients. Additionally, the role of systemic inflammation as a mediator between PLMS and CSVD warrants further exploration, particularly through biomarkers or longitudinal studies [20]. The findings have significant implications for both clinicians and researchers. For clinicians, the study emphasizes the importance of assessing PLMS in stroke and TIA patients, not merely as a symptom but as a potential marker of cerebrovascular burden. Polysomnography, often reserved for diagnosing OSA, could be expanded to include PLMS evaluations in high-risk populations. For researchers, the study underscores the need for longitudinal designs to determine causality and explore interventional strategies. Could therapies targeting PLMS, such as dopaminergic agents or nonpharmacological interventions, reduce the risk of CSVD progression? Moreover, expanding the study to include diverse populations, such as stroke-free individuals or those with different CSVD phenotypes, could provide a more comprehensive understanding of this complex interplay. Currently, there are no established clinical guidelines or indications for the treatment of PLMS, as their role in long-term health outcomes, including cerebrovascular disease, remains incompletely understood. While treatments such as anticonvulsants, dopaminergic agents, iron supplementation, and opioids are used to manage related conditions like RLS and periodic limb movement disorder [21], their utility in targeting isolated PLMS has not been systematically studied. The growing evidence linking PLMS to CSVD, including the findings by Veitch et al. [1], highlights the potential need for interventional trials. These studies could explore whether addressing PLMS, either through pharmacological or nonpharmacological approaches, might reduce the burden of CSVD or improve clinical outcomes in high-risk populations. However, until causality and the mechanisms of this association are better established, recommendations for routine treatment of PLMS remain premature. Veitch et al.’s study [1] marks a significant step forward in elucidating the relationship between PLMS and CSVD. By addressing prior limitations and introducing methodological innovations, the research not only strengthens the evidence base but also highlights critical gaps for future exploration. As our understanding of the neurovascular impacts of sleep disruptions deepens, studies like this pave the way for integrated approaches to cerebrovascular health, linking sleep science with neurology and cardiovascular medicine. Financial disclosure: none. Nonfinancial disclosure: none.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,021
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,038
Score d'incertitude au seuil0,019

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,021
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,003
Communication savante0,0020,003
Science ouverte0,0020,001
Intégrité de la recherche0,0380,024
Charge utile insuffisante (le modèle a refusé de juger)0,0050,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,028
Tête enseignante GPT0,284
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentnon

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