Establishing True Polysomnographic Normative Values: A Systematic Review and Meta-Analysis (S46.006)
Notice bibliographique
Résumé
Objective: Establish normative sleep data for healthy adults stratified by age and sex. Background: Sleep research is often constrained by the need for normative control values, which may be costly. Published “normative” data is based on small samples. This study is a large meta-analysis of polysomnography parameters and establishes normative values based on control values obtained from many smaller studies. Design/Methods: We reviewed English language publications between 2007 and July 31, 2016 that reported polysomnography collected during an in-laboratory study in healthy controls that were scored using the 2007 criteria. We excluded studies with insufficient information. Estimates were pooled using a random effects meta-analysis. Influence of age and sex was ascertained using mixed effects meta-regressions. Results: 169 studies were eligible (N=5273 subjects). For each decade, sleep onset latency increased 1.1 minutes (0.3–1.9), sleep efficiency decreased 2.1% (1.5–2.6), wake after sleep onset increased 9.7 minutes (6.9–12.4), arousal index increased 2.1 events/hour (1.5–2.6), percentage of N1 sleep increased 0.5% (0.1–0.8), apnea–hypopnea index increased 1.2 events/hour (0.9–1.4), minimum oxygen saturation decreased 1.8% (1.3–2.3), and the periodic limb movement index increased 1.2 events/hour (0.8–1.6). Percentages of N3 and REM sleep did not significantly decrease. Male sex was associated with reduced REM latencies (p=0.03) and oxygen saturations (p=0.002), and greater arousal indices (p=0.03) and respiratory event indices (p=0.0004). Compared to first night polysomnograms, studies from later nights reported significantly higher mean total sleep time, efficiency, and percentages of REM sleep. Conclusions: This study provides the largest sample size of normative polysomnographically measured sleep. These values serve as very useful control references for clinicians and future research. Disclosure: Dr. Murray has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with UpToDate. Dr. Kendzerska has received research support from The University of Ottawa, the Department of Medicine Developmental Research Grant, The American Thoracic Society Unrestricted Grant and The Lung Association – Ontario. Dr. Jairam has nothing to disclose. Dr. Mekhael has nothing to disclose. Dr. Im has nothing to disclose. Dr. Boulos has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with BresoTec Inc., CerebraHealth, and HALEO Preventive Health Solutions Inc. Dr. Boulos has received research support from Heart and Stroke Foundation of Canada, Canadian Partnership for Stroke Recovery, Alternative Funding Plan from the Academic Health Sciences Centres of Ontario, and the Sunnybrook Education Advisory Council and Education Research Unit, ResMed Corporation, BresoTec Inc., and SlumberBUMP.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,066 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,010 | 0,015 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».