Lithium Carbonate Versus Cognitive Therapy as Sequential Combination Treatment Strategies in Partial Responders to Antidepressant Medication
Bibliographic record
Abstract
BACKGROUND: Partial antidepressant response is associated with increased rates of relapse. Despite increasing evidence that full symptomatic remission is the optimal goal of antidepressant therapy, there have been few comparisons between disparate treatment approaches to achieve this goal. METHOD: Forty-four patients with DSM-IV major depressive disorder (MDD) who had a partial response (17-item Hamilton Rating Scale for Depression [HAM-D-17] score of 8-15) during open-label antidepressant treatment for 8 to 14 weeks were randomly assigned to receive cognitive therapy (CT) or lithium augmentation (LA) for a further 8 weeks using a single-blind design. Antidepressant medication was continued throughout the study. Subjects were also reassessed 4 weeks after discontinuation of LA or CT. Patients were enrolled in this study beginning September 1996 and follow-up for all patients was completed in December 2000. RESULTS: Although LA or CT did not significantly decrease symptom severity during sequential combination therapy, there was a significant decrease in HAM-D-17 scores 4 weeks later in LA-treated subjects compared with CT-treated subjects (p =.04). This resulted in 32% of patients achieving remission status, although between-group differences were not significantly different (38% in the LA group compared with 26% in the CT group, p =.39). CONCLUSION: Despite methodological limitations, this preliminary study provides justification for both combination treatments. An adequately powered, randomized, controlled trial to evaluate the relative merits of combination psychotherapy and augmentation of pharmacotherapy in patients with partially remitted MDD is required.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".