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Enregistrement W4392581972 · doi:10.1093/sleep/zsae043

Doctor, can napping help relieve my pain? Research path to assess the potential benefits/harms of napping for individuals with chronic pain

2024· article· en· W4392581972 sur OpenAlexafffundabout
Gilles Lavigne, Gabriel Natan Pires, Cibele Dal Fabbro, Alberto Herrero Babiloni, Marc O. Martel, Charles M. Morin, Mônica L. Andersen, Sérgio Tufik, Luciana Palombini

Notice bibliographique

RevueSLEEP · 2024
Typearticle
Langueen
DomainePsychology
ThématiqueSleep and related disorders
Établissements canadiensUniversité LavalUniversité de MontréalInstitut Universitaire en Santé Mentale de QuébecMcGill UniversityCanadian Sleep & Circadian NetworkCentres Intégré Universitaires de Santé et de Services Sociaux
Organismes subventionnairesCanadian Institutes of Health ResearchNational Institutes of HealthIdorsia PharmaceuticalsAssociação Fundo de Incentivo à PesquisaEisaiConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
Mots-clésMedicineLibrary scienceHumanitiesArt

Résumé

récupéré en direct d'OpenAlex

Chronic pain affects around 30% of the population, and can have a significant impact on sleep quality [1]. Patients with chronic pain, as well as health care providers, may not be aware of the potential benefits of sleep-related interventions with respect to pain, although questions about the general benefits of napping are often asked by patients. However, there is probably not a single or simple answer to the question of whether individual patients should or should not nap, and if they should, there remain questions about what the optimal nap duration is, the best time of day for napping, and the frequency and duration of naps. Moreover, there is no robust evidence on the relationship between napping and pain, and whether napping has a positive effect or not. In order to answer these questions, more research on the participant is required, as is the application of personalized medicine, with proper recognition of the variability in sleep-related phenotypes/endotypes, in order to provide recommendations that are tailored and individualized to each patient, considering their idiosyncrasies and clinical characteristics. The high prevalence of comorbid sleep disorders in individuals with chronic pain, such as insomnia and sleep-disordered breathing, further complicates the task of clinicians in providing robust recommendations to patients [2, 3]. The objectives of this letter are to (1) highlight the need for a scoping or systematic review of the participant, and (2) stimulate research on the interplay between napping and pain by highlighting areas that should be the focus of future studies, so that better evidence-based advice can be provided to patients. In the United States, regular napping is reported by 15% of the general population, and by up to 25% of individuals ages 75–84 years old [4]. Among individuals with chronic pain, napping is even more frequent, with estimates ranging from 39% to 70% [5, 6]. In Japanese home care nurses, working night shifts, frequent naps of 60 minutes or more were associated with reduced musculoskeletal arm and leg pain intensity [7]. Unlike in healthy individuals, the presumed beneficial relationship between sleep and pain is unclear among individuals with chronic pain. Furthermore, it is possible that chronic pain patients with comorbid insomnia and/or sleep apnea use daytime napping to cope with the residual effects of nighttime sleep disturbances. In otherwise healthy individuals, it was observed that a 30-minute sleep extension at night, or daytime napping after sleep restriction can increase pain tolerance and reverse experimental pain sensitivity, respectively [8, 9]. In fibromyalgia patients, a study assessing the effects of daytime napping (<30 minutes) concluded that naps do not produce clinical benefits. The combination of daytime napping and fibromyalgia was associated with greater symptom severity, including increased pain intensity, depression, anxiety, memory difficulties, sleep problems, and fatigue [6]. Conversely, in a study of older individuals with osteoarthritis, napping four times a week or more did not appear to modulate the association between poor sleep and fatigue [10]. Yet it needs to be considered that napping could potentially be a marker of poor health in older adults with comorbidities. A study showed that in patients with episodic migraine, napping on average for 77 minutes was considered to be a coping strategy, and did not appear to contribute to sleep disturbances [11]. However, in patients with chronic migraine, longer naps were associated with greater headache severity and lower sleep efficiency [12]. Thus, these contradictory results make it difficult to come to firm conclusions about the benefits/harms of napping in individuals with chronic pain. Pain, like sleep disorders, cannot be reduced to a simple and single concept, as its presentation is diverse in terms of nosology, pathophysiology, symptom severity, and clinical consequences. It has three main classifications: nociceptive pain (from tissue injury), neuropathic pain (from nerve injury), or nociplastic pan (from a sensitized nervous system) [1]. It also has diverse gender and age presentations, as well as treatment responses to medications or non-pharmacological treatments. We conclude that the relationship between napping and chronic pain is complex, and that existing research has not yet been sufficient to fully elucidate this relationship. Moreover, we do not think that simple generic recommendations will be valid for all types of pain or for different individuals. As a first step to overcome these difficulties, we propose that the quality of the available evidence on the interplay between napping, and sleep or pain variables should be assessed in a scoping or systematic review. In addition, to address these issues, future studies should be encouraged to: Focus on research designs that allow the identification of a causal relationship. Studies that associate napping with increased pain are usually of cross-sectional nature. In such cases, napping in individuals with chronic pain could be a consequence of the effects of pain on nighttime sleep, rather than a direct effect of napping on pain sensitivity. In other words, pain during the night might fragment sleep, therefore increasing sleep pressure during the day and increasing the likelihood of daytime napping. Randomized control trials assessing the effects of napping (either encouraging or avoiding it) in people with chronic pain would produce clearer evidence about potential cause-and-effect relationships. Daily diary studies based on ecological momentary assessment procedures could also examine day-to-day napping patterns and pain symptoms among persons with chronic pain. Identify the influence of potential confounders. Chronotypes (evening or morning types), sleep scheduling, or the effects of environmental factors on napping, are among the variables that may modify the association between napping and pain sensitivity, or influence clinical pain self-reports. Identify the factors contributing to napping behavior in individuals with chronic pain. Clarify whether napping is a genetically driven behavior, the result of an environmental or cultural influence or an adaptation to cope with the impact of chronic pain on quality of life, quality of sleep, cooccurring insomnia or sleep apnea, and other factors. Evaluate different types of napping. Naps are not equal, and their effects are very different depending on their characteristics. Research should compare the benefits and harms of various nap durations (short power naps, <30 minutes, 30 minutes or more, and >60 minutes), and their organization (planned or unplanned). Nap timing. The time when the nap takes place in the sleep–wake cycle of a given individual may influence mood, pain perception, and pain sensitivity. Evaluate nap frequency. Research should seek to establish what the ideal number of naps per day or week should be. The relationship between napping and pain is likely to be different depending on the nap frequency, which might range from every day (e.g. in a siesta-like pattern) to when needed (e.g. among individuals with migraine). Identify covariates and confounding factors such as: (1) gender and age across the life cycle, (2) mood and cognitive function, (3) physical activity, (4) sedentary behavior, (5) medications such as opioids, Z-pills, muscle relaxants, antidepressants, gabapentinoids, melatonin or cannabis that are often used by individuals with chronic pain, (6) the influence of comorbidities such as obstructive sleep apnea, insomnia, periodic limb movement, etc. (7) persistent and episodic pain, (8) biomarkers (e.g. inflammation) and related-physiological activities (e.g. autonomic response, pain perception modulation) and their correlates in healthy individuals and chronic pain populations [13, 14]. In conclusion, although napping in individuals reporting chronic pain is a recurrent topic of discussion in clinical practice, the actual effects of napping on pain-related variables are still not fully understood. Therefore, caution and personalized assessment are needed whenever providing advice to patients on this matter. There is a need for evidence-based data with respect to the benefits/harms of napping, with study designs addressing phenotypes and endotypes in individuals with chronic pain. GNP, MLA, ST, and LP are supported by the Associação Fundo de Incentivo à Pesquisa (AFIP). MLA is a recipient of a Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) fellowship and a grant from the São Paulo Research Foundation (FAPESP, grant 2020/13467-8); CM has received research grants from the Canadian Institutes of Health Research, the National Institutes of Health, Eisai, Idorsia, and Lallemand, and has served as consultant for Eisai and Idorsia. Financial disclosure: no financial arrangements or connections are reported for this paper. Nonfinancial disclosure: no potential conflicts of interest are reported for this paper. COI: No direct COI in relation to this letter.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,006
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,717
Score d'incertitude au seuil0,664

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0060,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,048
Tête enseignante GPT0,347
Écart entre enseignants0,299 · 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 tête enseignante, 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
GenreEmpirique

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

En bref

Citations0
Publié2024
Routes d'admission3
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