Association between tobacco smoking and drug-resistant tuberculosis
Bibliographic record
Abstract
Ming-Gui Wang,1,* Wei-Wei Huang,1,* Yu Wang,1 Yun-Xia Zhang,1 Miao-Miao Zhang,1 Shou-Quan Wu,1 Andrew J Sandford,2 Jian-Qing He1 1Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People’s Republic of China; 2Centre for Heart Lung Innovation, University of British Columbia and St. Paul’s Hospital, Vancouver, BC, Canada *These authors contributed equally to this work Background: Tobacco smoking is a risk factor for tuberculosis but little is known about the relationship between tobacco smoking and drug-resistant tuberculosis (DR-TB). We undertook a systematic review and meta-analysis to quantitatively assess the association between DR-TB and tobacco smoking.Methods: We searched for relevant studies in the Ovid MEDLINE, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, WANFANG, and WEIPU databases from inception to September 1, 2017. Results were expressed as odds ratios (ORs) with accompanying 95% CIs, and subgroup analyses were performed by study design, smoking type, DR-TB type, and multivariate analysis.Results: Thirty-three studies related to tobacco smoking and DR-TB were included. We found substantial evidence that tobacco smoking is associated with an increased risk of DR-TB (OR 1.57, 95% CI 1.33–1.86). Associations were also found in subgroup analyses: for multidrug-resistant tuberculosis (OR 1.49, 95% CI 1.19–1.86) and for any DR-TB (OR 1.70, 95% CI 1.3–2.23); the pooled OR was 1.45 (95% CI 1.11–1.90) for current smoking, 2.25 (95% CI 1.46–3.47) for past smoking, and 1.56 (95% CI 1.22–1.98) for smoking history; and similar ORs were also observed in study design and multivariate analysis subgroup analysis.Conclusion: This study demonstrated that tobacco smoking is an independent risk factor for DR-TB. Keywords: tobacco smoking, drug-resistant tuberculosis, multidrug-resistant tuberculosis, MDR-TB, meta-analysis
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.014 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".