A Review of Electronic Cigarettes and Liquid Nicotine Poisoning Exposure Cases in the United States
Bibliographic record
Abstract
PURPOSE: In 2007, electronic cigarettes (e-cigarette) were introduced as a smoking cessation device. Since then, its sale and marketing has been expanded annually. Concomitantly, there is an increase in the electronic cigarette (e-cigarette) and liquid nicotine exposure cases reported to the United States (US) poison control centers. The purpose of this review is to assess the exposure cases reported to US poison control centers to characterize the adverse health effects of e-cigarette and liquid nicotine use. METHODS: The PubMed database was searched for e-cigarette and e-liquid exposure reports since 2010. The qualitative analysis was conducted to depict the characteristics related to the incident cases and health outcomes of e-cigarette and e-liquid exposure to support public awareness. RESULTS: Since 2010, there was an increase in e-cigarette exposure incidents with ingestion, inhalation, ocular and dermal identified as the commonly reported routes of exposure in both children and adults. The clinical symptoms were well characterized based upon the specific route of exposure. The exposure incidents were categorized into age, sex, type of exposure, symptoms, management site and medical outcome. The children less than 5 years of age were unintentionally exposed followed by both unintentional and intentional exposure in adults. The reported medical outcomes have a range from minor effects exhibiting symptoms that were not bothersome to major effects with life-threatening symptoms, and death. The short-term or acute exposure was mostly associated with mishandling or misuse of the e-cigarette device or e-liquid. The case reports of young adult males who are linked to intensive use of e-cigarettes show lung injury. CONCLUSION: E-liquid and e-cigarette use continue to pose a serious health risk for both adults and children. There is accumulating data of incidents associated with short-term e-cigarette use or intensive use of e-cigarettes. However, monitoring of the long-term health effect of e-cigarettes is needed in order to raise public awareness among young adults.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".