Escitalopram in the treatment of major depressive disorder in primary-care settings: an open-label trial
Bibliographic record
Abstract
BACKGROUND: The present trial was designed to assess the efficacy and safety of escitalopram prescribed to patients seeking treatment of major depressive disorder (MDD) in a Canadian primary-care setting. METHODS: Investigators (mainly primary-care physicians) enrolled patients with MDD from their daily practice. Patients were treated with escitalopram (flexible dose 10-20 mg/day) for up to 24 weeks. Efficacy assessments included the Montgomery-Asberg Depression Rating Scale (MADRS), the Clinical Global Impression-Improvement and -Severity scales (CGI-I, CGI-S), the Patient Global Evaluation (PGE), and the Medical Outcome Study 36-item Short Form (SF-36). RESULTS: Out of the 647 patients enrolled, 461 (71%) completed 24 weeks of treatment. The most common reason for discontinuation was adverse events (10%). The mean MADRS score decreased from 30.7 at baseline to 10.9 at the end of 24 weeks (last observation carried forward, LOCF). Remission (MADRS<or=12) was achieved by 65.5% of patients (LOCF). Symptom improvements were confirmed by global ratings of improvement made by physicians (CGI-I) as well as patients PGE. There was improvement on all dimensions of the SF-36, suggesting an overall improvement in quality of life. CONCLUSIONS: Escitalopram was well tolerated, safe, and efficacious. Escitalopram can be used with confidence to treat patients with MDD in Canadian primary-care settings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".