The role of secondhand smoke in sinusitis: a systematic review
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to systematically review existing literature on the association between sinusitis and secondhand smoke (SHS) exposure. METHODS: We performed a literature search encompassing the last 25 years in PubMed, EMBASE, and Cochrane CENTRAL. Inclusion criteria included English language papers containing original human data with at least 7 subjects. Data was systematically collected on study design, patient demographics, clinical characteristics/outcomes, and level-of-evidence (Oxford Center for Evidence-Based Medicine). Quality assessment was performed using the Newcastle-Ottawa scale. Two investigators independently reviewed all manuscripts. RESULTS: The initial search yielded 116 abstracts, of which 19 articles were included. Thirteen (68.4%) of the 19 articles showed a statistically significant association between sinusitis and SHS. Seven (36.8%) studies specifically evaluated chronic rhinosinusitis (CRS) with 5 (71.4%) CRS studies demonstrating a significant association between CRS and SHS. Seventeen articles were case-control studies (Level 3b). For characterizing sinusitis, 6 (31.6%) studies included computed tomography (CT) or endoscopy in the diagnostic criteria, with 5 of these studies following rhinosinusitis taskforce guidelines. For determining presence of SHS, all studies used questionnaires and 2 (10.5%) studies also reported serum or urine cotinine levels. CONCLUSION: A majority of the studies (68.4%) included in this systematic review showed a significant association between sinusitis and SHS. Furthermore, 5 (83.3%) of the 6 studies with objective diagnostic criteria (CT, endoscopy) found a significant association between sinusitis and SHS. Further higher-quality studies with objective diagnosis of sinusitis and quantification of SHS exposure should be performed in the future to better evaluate the relationship between sinusitis and SHS.
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 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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".