Diagnosis and management of acute alcohol withdrawal
Bibliographic record
Abstract
ALCOHOL ABUSE PRODUCES A CONSIDERABLE BURDEN OF ILLNESS in the Canadian popu-lation. The diagnosis of alcohol dependence and withdrawal can be difficult, particularly in the setting of covert intake or comorbidity. Two validated scales, the CAGE questionnaire to screen for alcohol abuse and dependence and the Clinical Institute Withdrawal Assessment for Alcohol (CIWA-Ar) scale to assess the severity of withdrawal, are valuable tools for clinicians to use on a regular basis. For the treatment of alcohol withdrawal, compelling anecdotal evidence supports the routine administration of thiamine, but not necessarily other vita-mins. Phenytoin has not been shown to be superior to placebo for uncompli-cated withdrawal seizures. Neuroleptics are not recommended for routine use. Sedation with benzodiazepines guided by the CIWA-Ar results is recommended. There is good evidence that the management of alcohol withdrawal can be im-proved with the routine use of the CIWA-Ar scale to assess severity, treatment with adequate doses of benzodiazepines and follow-up monitoring of patients in
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".