Alcohol use disorders and associated chronic disease – a national retrospective cohort study from France
Bibliographic record
Abstract
BACKGROUND: Evidence on diseases caused by or associated with alcohol use disorders (AUDs) has been based on two meta-analyses including rather dated studies. The objective of this contribution was to estimate the risks of all-cause mortality and alcohol-attributable disease categories depending on a diagnosis of AUDs in a national sample for France. METHODS: In a national retrospective cohort study on all inpatient acute and rehabilitation care patients in Metropolitan France 2008-2012 (N = 26,356,361), AUDs and other disease categories were identified from all discharge diagnoses according to standard definitions, and we relied on in-hospital death for mortality (57.4% of all deaths). RESULTS: 704,803 (2.7%) patients identified with AUDs had a threefold higher risk of death (HR = 2.98; 95% CI: 2.96-3.00) and died on average 12.2 years younger (men: 10.4, 95% CI: 10.3-10.5; women: 13.7, 95% CI: 13.6-13.9). AUDs were associated with significantly higher risks of hospital admission for all alcohol-attributable disease categories: digestive diseases, cancers (exception: breast cancer), cardiovascular diseases, dementia, infectious diseases, and injuries. Elevated risks were highest for liver diseases that were associated with about two-third of deaths in patients with AUDs (men: 64.3%; women: 71.1%). CONCLUSIONS: AUDs were associated with marked premature mortality and higher risks of alcohol-attributable disease categories. Our results support the urgent need of measures to reduce the burden of AUDs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".