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Record W3134706546

Tobacco Smoke Exposure and Pediatric Multiple Sclerosis

2016· article· en· W3134706546 on OpenAlexaboutno aff
Amy M. Lavery

Bibliographic record

VenueTUScholarShare (Temple University) · 2016
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisMedicineEnvironmental healthSmokeTobacco smokeImmunologyGeography
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.100
GPT teacher head0.267
Teacher spread0.167 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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