Effects of citalopram and a brief psycho-social intervention on alcohol intake, dependence and problems
Bibliographic record
Abstract
Citalopram (C) decreased alcohol intake and desire to drink in short-term (2-4 weeks) studies with no other treatment. We tested the long-term effects of C combined with a brief psycho-social intervention. After a 2-week baseline, mildly/moderately dependent alcoholics (35 males, 27 females) were randomized, double-blind to 12 weeks of C 40 mg/day (n = 31) or placebo (P) (n = 31) and a brief psycho-social intervention with follow-ups at 4 and 8 weeks post-treatment. Alcohol intake was monitored daily and alcohol dependence (ADS) and problems (MAST) were assessed at intake and post-treatment. During the first week, the decrease (%) from baseline daily alcoholic drinks (mean +/- SEM) was greater with C (47.9 +/- 5.1 from 6.5 +/- 0.6) than with P (26.1 +/- 4.2 from 5.8 +/- 0.4) (p < 0.01). However, the 12-week decreases with C (35.1%) and P (38.8%) were similar. There were gender differences within the C group. The males had higher MAST scores at intake (mean +/0 SEM = 10.4 +/- 0.8; n = 15) than the females (6.4 +/- 0.9, n = 16) (p < 0.01) and were slightly heavier drinkers during baseline (7.1 +/- 0.9 vs. 5.9 +/- 0.9 drinks/day, NS). The response to C was greater in males (44% decrease) than females (26%) (p < 0.05) and correlated with MAST scores (r = 0.44, p = 0.01), but not with baseline alcohol intake (r = 0.2, NS). Craving and liking for alcohol and alcohol dependence (ADS) and problems (MAST) decreased similarly with C and P (p < 0.01). Thus, the short-term effects of C were replicated but no long-term effect was detected. Tolerance to citalopram, perhaps through some adaptive neurobiological changes, may have developed. The potential therapeutic use of C as a useful pharmacological adjunct in alcoholics remains to be determined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".