The Effect of Parental Smoking on the Severity of Asthma in Children: A Cross-Sectional Study
Bibliographic record
Abstract
BACKGROUND: Several environmental factors trigger attacks of asthma by immunological and non-immunological mechanisms. Among these factors are cited the passive or second hand smoking (SHS) which has a deleterious effect on the prognosis of childhood asthma and induces a resistance to treatment by corticosteroids. The aim of the present study was to identify parents of children with asthma who are smokers and to explore the possible negative impact of SHS exposure on the disease of asthmatic children.MATERIALS & METHODS: A cross sectional study was conducted from February 2012 to February 2013.The study population consisted of children with asthma. The information concerning the patients was collected from their medical records filled out by the physician in a clinical setting in direct communication with the patients, or their parents when it is a little child. A group of 100 children age between 2 and 15 years, with asthma were recruited for the study. The study children were divided into two groups: cases with 28 children from smoking families, and controls with 73 children from non-smoking families. Analysis of the number of respiratory infections, asthma exacerbations per year, and the average number of hospitalization was done in both groups.RESULTS: Pearson chi2 test was adopted. We showed that smoking among the father was positively correlated with a higher number of hospitalizations for asthma, higher incidence of lower respiratory tract infections and asthma exacerbations. Similarly, the maternal smoking was positively correlated with a higher number of hospitalizations for asthma, lower respiratory tract infections and asthma exacerbations.CONCLUSION: Passive smoking causes respiratory illness, asthma, poor growth, neurological disorders in children. To avoid the risk of respiratory and allergic diseases by environmental tobacco smoke, absolute smoking cessation by parents is strongly recommended.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".