The association between secondhand smoke and sleep‐disordered breathing in children: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review existing literature on the association between secondhand smoke and sleep-disordered breathing in children. DATA SOURCES: PubMed, Embase, Cochrane CENTRAL, Web of Science, and Scopus. REVIEW METHODS: Inclusion criteria included English-language papers containing original human data, with seven or more subjects and age <18 years. Data were systematically collected on study design, patient demographics, clinical characteristics/outcomes, and level of evidence. Two investigators independently reviewed all manuscripts. RESULTS: The initial search yielded 72 abstracts; 18 articles were ultimately included with a total study population of 47,462 patients. Fifteen (83%) articles found a statistically significant association between secondhand smoke and sleep-disordered breathing. All were case-control studies. Quality of articles based on the Newcastle-Ottawa scale averaged 5.8/9 stars. Secondhand smoke was characterized by serum cotinine testing in only two (11%) studies. Sleep-disordered breathing was quantified by polysomnography in only four (22%) of the studies and only one (6%) classified subject using polysomnography exclusively. Habitual snoring was the most common form of sleep-disordered breathing studied in 14/18 (78%) studies, whereas obstructive sleep apnea was reported in one (6%) study and sleep-related hypoxia in another (6%) study. CONCLUSIONS: Although the majority of studies included in this review found a significant association between secondhand smoke and sleep-disordered breathing, all of them were evidence level 3b, for an overall grade of B (Oxford Centre for Evidence-based Medicine). Further higher-quality studies should be performed in the future to better evaluate the relationship between second- smoke and sleep-disordered breathing in children.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".