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Enregistrement W1850376719 · doi:10.1093/sleep/33.9.1133

Metabolic Disease in Sleep Disordered Breathing: Puberty! Puberty!

2010· letter· en· W1850376719 sur OpenAlexaff
Rakesh Bhattacharjee, David Gozal

Notice bibliographique

RevueSLEEP · 2010
Typeletter
Langueen
DomaineMedicine
ThématiqueObstructive Sleep Apnea Research
Établissements canadiensSickKids FoundationUniversity of TorontoHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésMedicineFailure to thriveContext (archaeology)Obstructive sleep apneaDiseasePediatricsNeurocognitiveObesityInternal medicinePsychiatryCognitionBiology

Résumé

récupéré en direct d'OpenAlex

THE EMERGENCE OF CLASSIC PATTERNS OF “ADULT-ONSET” DISEASE IN CHILDREN HAS CHANGED THE PARADIGM OF PEDIATRIC MEDICINE FROM ONE that focused mainly on diseases of genetic and/or developmental origin to a field that now includes management of children with acquired lifelong diseases. The most prominent of those “adult diseases” is undoubtedly obesity and its associated complications. Pediatric obstructive sleep apnea (OSA) is a frequent condition in children that was initially viewed as attributable to underlying genetic and developmentally regulated mechanisms, specifically involving upper airway structure and neuromuscular factors, all of which cumulatively promoted marked increases in upper airway resistance during sleep. In this context, the childhood obesity pandemic has been accompanied by a remarkable increase in the incidence of OSA1 in obese children, in whom the clinical presentation, findings on physical examination, and even the response to standard treatment greatly differ from the traditional pediatric OSA phenotype.2,3 Furthermore, the array of morbid consequences ascribed to pediatric OSA, which initially involved failure to thrive, enuresis, and neurocognitive behavioral consequences, has now been greatly expanded to include cardiovascular and metabolic dysfunction and liver steatosis, thereby mimicking the pattern of disease previously restricted to adult OSA.4,5 In the paper by Kelley and colleagues in this issue of SLEEP,6 the authors have explored the risk factors potentially contributing to metabolic disease in the context of pediatric OSA. To this effect, they not only examined an array of systemic biomarkers, including those reflecting disordered glucose and fatty acid metabolism and those suggestive of up-regulation of sympathetic nervous activity, but also adjusted their analyses for the effects of puberty and obesity. Specifically, the authors carefully selected children with and without symptoms of suspected OSA, and separated them into two cohorts; a prepubertal and pubertal cohort, with pubertal status being determined through a validated questionnaire. Kelley and colleagues6 found normal sleep studies in 33 of 100 children and these were assigned as controls; however, it should be emphasized that the vast majority of the children recruited (82 of 100) originated from the Sleep clinic, and hence the cohort was skewed to primarily symptomatic subjects (snoring or excessive daytime sleepiness), with only 18 children being effectively symptom free. Further, the proportion of prepubertal children with moderate or severe OSA was rather minute (only 3 of 37 meeting OSA criteria [AHI ≥ 5 events/hr]). In the pubertal cohort, 34 of 61 subjects had AHI > 1.5 events/hr, but the proportion of those with moderate to severe OSA was not reported. Notwithstanding the aforementioned limitations, the authors reported on some rather intriguing associations, particularly in the pubertal cohort. Indeed, overall fasting insulin levels were increased in pubertal children, and several indices of OSA, namely AHI and oxygen saturation nadir, were associated with an elevated homeostasis model assessment (HOMA), a calculated measure of insulin resistance.6 However, the significance of such associations disappeared after adjustment for BMI-z score, thereby confirming the initial assumption on the importance of controlling for obesity, particularly when attempting to establish pathophysiological links between OSA and metabolic disease. Thus their findings strongly confirm previous studies by several investigators, whereby no significant changes in HOMA were apparent in non-obese children with OSA.4,7,8 In contrast, indices of OSA were strongly associated with lower levels of adiponectin in the pubertal cohort, even after adjustment for BMI-z score.6 Adiponectin is a hormone that is secreted by adipose tissue and functions to decrease liver glucose production and increase β oxidation of fatty acid by muscle.9 Thus, decreased levels of adiponectin would imply diminished metabolic control of glucose and fatty acid homeostasis. Not surprisingly, reduced adiponectin levels are associated with obesity and type 2 diabetes.10 The findings of Kelley et al.6 suggest that in at least pubertal children, morning adiponectin plasma levels appear to be a more specific indicator of metabolic dysfunction in the context of OSA than the traditional markers of fasting insulin and glucose concentrations. Since a previous report in SLEEP does not support this conclusion,11 future large-scale populations studies will be needed to confirm these observations. Furthermore, it is difficult to ascertain whether the effects seen by Kelley et al.6 with OSA on adipokines were indeed related to children who were undergoing puberty at the time of analysis, or whether the significant effects of OSA only occur after puberty. Of note, fasting insulin levels do increase during puberty and will decrease to near prepubertal levels upon completion of puberty.12 Kelley and colleagues6 collected 24-hour urine samples that were assayed for urinary catecholamines, since increases in the overall release of these amines in the context of OSA could also alter glycemic control. They found that urinary normetanephrine, and to a lesser degree urinary norepinehprine levels were associated with OSA severity, thus confirming previous studies.13,14 Based on these findings, OSA in children is clearly accompanied by an up-regulation of tonic and reactive sympathetic nervous activity, which may amount to elevated risks for both metabolic and cardiovascular disease. Taken together the findings from Kelley et al.6 suggest that particularly in pubertal children, OSA confers a higher risk for the development of metabolic syndrome as evidenced by reduced levels of adiponectin (after adjustment of BMI z-score) and perhaps the contributory effects of heightened sympathetic nervous activity, as evidenced by elevated levels of urinary normetanephrine. Obesity, rather than OSA, has been previously shown to be the major contributor to adipokine levels in children.11,15 The study by Kelley et al.6 suggests that in pubertal children, the effects of OSA may occur independent of obesity. A final comment intended to further foster the ongoing debate pertains to the question as to whether the usage of pediatric OSA severity criteria applies to pubertal children.16 Although this question will remain unanswered, we should point out that if adult diagnostic criteria for OSA had been implemented among pubertal children, the conclusions from this study6 would have been quite different. In summary, the findings of Kelley et al.6 confirm that metabolic derangements are accentuated by the presence of obesity, and further worsened by OSA, particularly during puberty. This should prompt pediatricians to proactively screen and treat obesity and OSA, rather than consider these conditions as “adult-onset” diseases. Such change in conceptual and pragmatic approaches is integral to the effective reversal of metabolic and cardiovascular morbidities in children.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesIntégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,382
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,001
Intégrité de la recherche0,0030,014
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

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 Opus0,016
Tête enseignante GPT0,279
Écart entre enseignants0,262 · 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

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

Citations3
Publié2010
Routes d'admission1
Résumé présentoui

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