Alcohol Intoxication: an Emerging Public Health Problem
Bibliographic record
Abstract
Background:Alcohol-related disorders are among major public health problems around the world. We aimed to focus on the trends of alcohol intoxication in Mashhad for the recent seven years. Methods: Registry database was analyzed. All admitted cases with alcohol-related intoxication were included during 2004 to 2011. Two national censuses were used for rate calculation. Results: There were 772 admissions due to alcohol (ethanol and methanol) intoxication (1.6% of all poisonings which equals to a prevalence rate of 3.3 per 100,000) during the 7-year period. Mean age was 25±11.9 years, and 90% of subjects were male. Alcohol intoxication prevalence was tripled as compared to 2004. Case fatality rate was higher in women (7.5% vs. 6.6%). Males who were self-employed or unemployed and females who were housekeepers or students were at greatest risk. The age-specific prevalence rate was highest in 10-20 (6.25 per 100,000), and the age-specific mortality rate was highest in 30-40 (2.13 per 100,000) age group. Conclusion: It seems that current health policies need to improve regarding complications of alcohol use in the area to effectively control the increasing rates. Further national studies are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".