Examining the Saskatchewan health drug database for antidepressant use: the case of fluoxetine.
Bibliographic record
Abstract
OBJECTIVE: To examine the use of fluoxetine in an adult population in Saskatchewan. METHODS: All adults in the Saskatchewan health care databases who had begun fluoxetine therapy between January 1992 and June 1996 and had not received an antidepressant in the six months before the index fluoxetine prescription were identified. Fluoxetine use for the subsequent six-month period was examined. The rates of completion of six months of fluoxetine, rates of stopping, switching to another serotonin-selective reuptake inhibitor (SSRI) or other class of antidepressant, resumption of fluoxetine, as well as average dosages taken and mean duration of therapy were determined. Rates were summarized as means with standard deviation. RESULTS: Data were obtained for 11,322 subjects, of whom 68.2% were women; 17.4% were 65 years of age or older. The average prescribed daily dose of fluoxetine was 22.5 mg (SD=21.7) and the average duration was 88.1 days (SD=57.2). Only 18.9% of patients filled prescriptions for six months, 7049 (62.3%) stopped fluoxetine at least once for one month or more, and 17.3% were titrated to a higher dose, on average 71 days (SD=44) after the initiation of fluoxetine. The proportion of patients switching to another antidepressant was 13.6% (3.3% to another SSRI, 10.3% to other classes), after a mean of 69 days (SD=51) of fluoxetine treatment. CONCLUSIONS: The authors' data suggest that there is a potential underutilization of fluoxetine in the study population. Further research may be warranted to determine the proportion of depressed patients in this population and to better understand the stop-switch-resume pattern of antidepressant use.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".