Notice bibliographique
Résumé
Introduction: Multiple sclerosis (MS) is a chronic inflammatory disease which affects approximately 2.5 million people worldwide, including approximately 7,000 children. The etiology of MS is unclear, although researchers generally agree that both environmental and genetic factors are involved. It is also unclear why some patients may only have one demyelinating event (acquired demyelinating syndrome, or ADS) and others develop chronic demyelinating disease (MS). Recent evidence suggests an association between smoking and multiple sclerosis (MS) in adults. A question remains if there is a similar association between secondhand tobacco smoke exposure and MS in children. The purpose of this study is to explore the association between tobacco smoke exposure (TSE) and MS risk in a cohort of children with demyelinating disease. Methods: Data was obtained from the Canadian National Demyelinating Disease Study. This study included two disease groups, which are distinguished by a single (ADS) versus chronic demyelinating attacks (MS). Parents’ self-report of their child’s exposure to smoke in the home, as well as biomarker verification by serum cotinine, classified a child as exposed or not exposed. Logistic regression models were created to determine the association between TSE and the odds of MS compared to healthy controls, the odds of ADS compared to healthy controls, and the odds of MS compared to patients with ADS. In order to determine factors and exposures which distinguish MS from ADS, an assessment of interaction was performed to examine the relationship between TSE and MS risk genes, TSE and serum vitamin D levels, and TSE and prior Epstein Barr Virus exposure on the odds for developing MS compared to ADS patients.. Finally, serum cotinine levels were compared to neurologic functional scores in order to assess if a dose response mechanism exists creating impaired function for pediatric MS. Results: TSE was not significantly associated with increased odds for MS compared to healthy controls (OR= 1.84; 95%CI 0.86, 3.95) but was significantly associated with higher odds of monophasic ADS compared to healthy controls (OR=2.24; 95%CI 1.08, 4.63). TSE alone was not associated with increased odds for MS compared to ADS; however, the presence of both TSE and HLA alleles increased the odds for MS by 3.2 (95%CI 1.04, 9.79) when compared to ADS patients. An additive effect was also found between TSE and lower vitamin D, which together increased the odds for MS compared to patients with monophasic ADS (OR=2.89; 95%CI 1.21, 7.46). EBV was individually associated with MS compared to ADS (OR=4.12; 95%CI 1.62, 10.9) and odds for MS appeared to increase further with the addition of TSE (OR=5.13; 95%CI 1.79, 14.9), however sample size limited interpretation of the interaction analysis. TSE had minimal impact on neurological functional score measures, although long-term follow up with regard to exposure could not be properly assessed. Conclusion: Exposure to tobacco smoke through secondhand sources was not related to MS but TSE may increase the odds of monophasic demyelinating disease occurrence (ADS). The finding of additive effects between TSE and other disease modifying factors (HLA, vitamin D) may provide valuable insight into why some children have only one demyelinating attack (monophasic ADS) while others have multiple attacks and are diagnosed with MS. These effects should be further explored in a larger population of pediatric patients and compared to healthy children. Intervention methods should be tailored to help explain to parents the benefits of reducing their child’s exposures to environmental tobacco smoke.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 tête enseignante, 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 ».