Vaping-induced acute epiglottitis: a case report
Bibliographic record
Abstract
BACKGROUND: E-cigarette use, or vaping, is an alternative nicotine delivery system that is becoming increasingly prevalent in adolescents and young adults. There is currently a lack of comprehensive research on the adverse effects of vaping on the upper airway. Acute epiglottitis is a potentially life-threatening condition that can lead to airway obstruction. It is commonly caused by bacterial infections such as streptococci, staphylococcus, and Moraxella. Adult patients with acute epiglottitis mainly present with odynophagia, dysphagia, and respiratory difficulties. The diagnosis of epiglottitis is made by direct laryngoscopy, and the mainstay of treatment is antibiotics. Bozella et al. (2020) reported a case of subacute non-infectious epiglottitis associated with e-cigarette use in a pediatric patient (Pediatrics 145(3), 2020). Here we present a case of acute epiglottitis in a healthy young adult after vaping, with a negative infectious workup. To our knowledge, there has been no such reported case of epiglottitis associated with e-cigarette use in an adult patient. CASE DESCRIPTION: A previously healthy 29-year-old male with daily e-cigarette use presented to the emergency department with a severe sore throat, dysphagia, mild hoarseness, and shortness of breath, especially when lying supine. A lateral neck soft tissue radiograph revealed a thickened epiglottis with a thumb sign. Direct bedside laryngoscopy showed a swollen epiglottis, partially obstructing the supraglottic region confirming the diagnosis of acute epiglottitis. Throat and nasal swabs were negative for streptococcus and COVID-19 infection, respectively. The patient's condition improved significantly after receiving intravenous Dexamethasone and antibiotics for 2 days. Repeat laryngoscopy showed the resolution of epiglottis swelling, and subjective symptoms had resolved entirely 2 weeks following the start of the treatment. CONCLUSIONS: Although bacterial infections usually cause acute epiglottitis, this case presents the second report of this condition associated with vaping with negative microbiological investigations. Therefore, we recommend that physicians consider non-infectious causes such as vaping in their differential diagnosis for patients with acute and subacute epiglottitis. More research is warranted on the utility of antibiotics in treating vaping-induced epiglottitis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".