Respiratory Effects of Vaping Nicotine and Tetrahydrocannabinol (THC)
Bibliographic record
Abstract
Abstract Rationale: Electronic cigarettes (or vaping) are reported to cause pneumothorax, interstitial lung disease and several forms of non-infectious pneumonia. Their impact on lung function is poorly understood, due to evolving e-cigarette devices and vape liquid formulation. Respiratory oscillometry is an emerging modality of pulmonary function tests (PFTs), which is performed during tidal breathing and is more sensitive than standard PFT (spirometry and plethysmograph) for early detection of lung disease. Objective: To evaluate the respiratory effects of nicotine and THC vape using oscillometry and standard PFTs. Methods: We recruited non-vapers, nicotine only, THC only and dual nicotine-THC vapers between ages 18-45 years old. To be eligible, non-vapers must not have smoked cigarettes or any combustible products, nor have a history of respiratory disease. Vapers were required to have vaped at least 20 days per month for a minimum of one year and must not have smoked more than 100 cigarettes in their lifetime. Consented participants were assessed with both spectral and intrabreath oscillometry, standard PFT (spirometry, lung volumes, diffusing capacity), and computed tomography chest imaging at Toronto General Hospital. Results: We enrolled 81 participants (35 [12M/23F] non-vapers, 18 [9M/9F] nicotine vapers, 26 [10M/16F] THC vapers and 2 [1M/1F] dual nicotine and THC vapers). Dual users were excluded from analysis due to the small number. Standard PFTs and oscillometry were normal for all 3 groups. No statistically significant differences were observed in conventional PFTs amongst the non-vapers, nicotine-only, and THC-only vapers. However, oscillometry revealed statistically significant poorer respiratory mechanics among vapers, particularly THC vapers, compared with non-vapers. Conclusion: Although standard PFT were normal in all groups, oscillometry found worse respiratory mechanics in THC vapers. Further longitudinal analysis is needed to assess whether continuous vape use has an impact on respiratory health.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".