Cause-specific mortality risk in alcohol use disorder treatment patients: a systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Alcohol use disorders (AUD) are highly disabling. Recent studies reported much higher relative risks for all-cause mortality in AUD patients compared with earlier studies. Systematic evidence regarding cause-specific mortality among AUD patients has been unavailable to date. METHODS: Studies were identified through MEDLINE, EMBASE and Web of Science up to August 2012. Following MOOSE guidelines, prospective and historical cohort studies assessing cause-specific mortality risk from AUD patients at baseline compared with the general population were selected. Data on several study characteristics, including AUD assessment, follow-up period, setting, location and cause-specific mortality risk compared with the general population were abstracted. Random-effect meta-analyses were conducted. RESULTS: Overall, 17 observational studies with 6420 observed deaths among 28 087 AUD patients were included. Pooled standardized mortality ratios (SMRs) after 10 years of follow-up among men were 14.8 (95% confidence interval: 8.7-24.9) for liver cirrhosis, 18.0 (11.2-30.3) for mental disorders, 6.6 (5.0-8.8) for death by injury and around 2 for cancer and cardiovascular diseases. SMRs were substantially higher in women, with fewer studies available. For many outcomes the risk has been increasing substantially over time. CONCLUSIONS: Cause-specific mortality among AUD patients was high in all major categories compared with the general population. There has been a lack of recent research, and future studies should focus on the influence of comorbidities on excess mortality risk among AUD patients. Efforts to reduce these risks should be a priority, given that successful treatment reduces mortality risk substantially for a relatively common psychiatric disease.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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 it