An Episode of Psychosis After Nitrous Oxide Abuse During a Pandemic: A Case Report
Bibliographic record
Abstract
The abuse of inhalants like nitrous oxide (N2O), readily available worldwide, has remained a prominent public health problem during the last few decades. Literature reveals increased use during the previous pandemic, particularly regarding recreational use. There is limited evidence-based data available to relate the abuse of N2O with psychosis. Therefore, this case report of a 22-year-old adult with no previous psychiatry history, reportedly abusing 75-100 canisters of N2O per day during the last pandemic COVID-19 lockdown, highlights the relationship between (N2O) abuse and the symptoms evolved including delusions, auditory hallucinations, and disorganized cognition. All the laboratory findings and results from imaging modalities were inconsistent for any organic cause of the symptoms. The case then underwent treatment with antipsychotic medications and a multidisciplinary model, which improved the symptoms gradually. The case, in particular, discusses N2O abuse, which is widespread in European Union countries, including the UK and the Republic of Ireland, and its chronic use puts one at a higher risk of developing psychosis, personality changes, affective lability, anxiety, depression, cognitive impairment, and myeloneuropathy. The sale of N2O for its psychoactive properties is prohibited in many countries, including the Republic of Ireland, as per legislation. However, N2O is not a controlled drug, meaning it is not a crime to possess N2O. This case report manifests the psychopathy caused by abuse of N2O, which would further attract specialists in the field to conduct epidemiological studies for prevention at the primary level.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| 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".