Nicotine Toxicity From Repeat Use of Nicotine Pouches
Bibliographic record
Abstract
BACKGROUND: Nicotine pouches have emerged as a novel way to administer concentrated nicotine and come as a white powder in flavored, microfiber pouches placed between the cheek and gums to dissolve without requiring spitting. While marketed as a safe alternative to smoking, nicotine pouches have the potential for toxic exposure to users. CASE PRESENTATION: We present a case of a 21-year-old male with acute nicotine toxicity through repeated administration of nicotine pouches. Over the course of 12 hours, he consumed 15 extra-strength nicotine pouches (10.9 mg per pouch) as a study tool to prepare for the next-day exams. He presented to the emergency department with bizarre behavior requiring admission for persistent confusion and nausea which resolved after 24 hours. CONCLUSIONS: This case represents the first case of acute nicotine toxicity secondary to nicotine pouch use. These pouches are emerging as a novel way to use nicotine and present a serious risk of inadvertent overdose and harm. IMPLICATIONS: Nicotine pouches are emerging as a novel way to use nicotine, and second to e-cigarettes, are the most frequently used nicotine product among youth. These pouches, which lack clear warning labels, are promoted among social media forums and present a serious risk of inadvertent overdose and harm, especially among young adults. Healthcare professionals should be aware of this risk, especially from acute, repeated exposures, and should ensure the public is cautioned appropriately.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".