Alcohol and Injury: A Risk Function Analysis from the Emergency Room Collaborative Alcohol Analysis Project (ERCAAP)
Bibliographic record
Abstract
While emergency room (ER) studies have documented a strong association of alcohol and injury, less is known about the level of risk at which various quantities of alcohol or particular patterns of drinking place the individual for injury. Comparative risk function analyses are carried out in ER samples in seven countries that cover sites in 14 studies included in the Emergency Room Collaborative Alcohol Analysis Project (ERCAAP). Risk of injury is analyzed for the mean number of drinks consumed per day and the number of occasions in which 5 or more drinks were consumed at one time (5+) during the last year. All countries showed similar increases in injury risk to an average volume of about 2 drinks per day, with a leveling off of risk at higher average daily volumes, with the exception of Italy. Risk of injury increased to 12 or more 5+ days for the USA, Canada and Mexico, but leveled off after only 3 5+ days for Argentina and Spain. Poland showed increased risk to 30 5+ days. Similar risk curves were found for both males and females, although females were at lower risk of injury in all countries expect Spain and Poland. In low detrimental drinking pattern societies, risk curves showed higher risk for any drinking and any frequency of 5+ but at higher levels of each, risk levels decreased nearly to levels found for abstainers. Risk functions were also consistent across gender and age groups in low detrimental drinking pattern societies, with higher risk for males and those <30. For those countries with high detrimental drinking patterns, injury risk increased with volume and 5+ drinking primarily among males. This ER-based risk function analysis suggests that risk of injury increases proportionally with increased alcohol consumption at lower consumption levels, but a threshold effect is achieved at relatively low levels of mean daily consumption and higher consumption times. Risk may be culturally specific, dependent, in part, on the manner in which alcohol is used in the culture.
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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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".