Alcohol and pancreatitis mortality at the population level: experiences from 14 western countries
Bibliographic record
Abstract
AIMS: To test if there is relationship between alcohol consumption and pancreatitis mortality at the population level. DATA AND METHODS: Annual pancreatitis death rates for 1950-95 were converted into age-adjusted mortality rates per 100,000 inhabitants. Per capita alcohol consumption was measured by alcohol sales. The relationship was estimated with time-series analysis on data from 14 western countries. Several models were tested with different assumptions about risk function and lag structure. RESULTS: According to the assumed most appropriate model, a positive relationship was found in each country, and statistical significance was reached in all countries except from Finland, Italy and Canada. The magnitude of the association was fairly consistent across countries, with the alcohol effect parameters ranging between 0.05 and 0.14. However, Sweden and Norway deviated from this pattern with estimates between 0.30 and 0.40. CONCLUSIONS: Pancreatitis joins a wide range of causes of death where the mortality rate is influenced by per capita alcohol consumption, and more so in northern Europe. It is suggested that pancreatitis mortality is an important indicator of alcohol-related harm, not least because a large amount of morbidity is likely to be connected to the mortality rate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".