Olanzapine plus carbamazepine<i>v.</i>carbamazepine alone in treating manic episodes
Bibliographic record
Abstract
BACKGROUND: Combinations of olanzapine and carbamazepine are often used in clinical practice in the management of mania. AIMS: To assess the efficacy and safety of olanzapine plus carbamazepine in mixed and manic bipolar episodes. METHOD: Randomised, double-blind, 6-week trial of olanzapine (10-30 mg/day) plus carbamazepine (400-1200 mg/day; n=58) v. placebo plus carbamazepine (n=60) followed by open-label, 20-week olanzapine (10-30 mg/day) plus carbamazepine (400-1200 mg/day, n=86), with change in manic symptoms as main outcome measure. Safety and pharmacokinetics were also evaluated. RESULTS: There were no significant differences (baseline to endpoint) in efficacy measures between treatment groups, but at 6 weeks triglyceride levels were significantly higher (P=0.008) and potentially clinically significant weight gain (>or=7%) occurred more frequently (24.6% v. 3.4%, P=0.002) in the combined olanzapine and carbamazepine group. Carbamazepine reduced olanzapine concentrations but olanzapine had no effect on carbamazepine concentrations. CONCLUSIONS: The combination of olanzapine and carbamazepine did not have superior efficacy to carbamazepine alone. The increases in weight and triglycerides observed during combination treatment are a matter of concern.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".