Personality profile and therapeutic response to lithium carbonate and sodium valproate in mania with psychotic features
Bibliographic record
Abstract
Bipolar disorder is one of the major psychiatric disorders. Therefore, determining the factors that predict mood stabilizer response is important. This study aimed to investigate the relationship between personality profile and the response to lithium carbonate and sodium valproate in patients with psychotic mania. In this study, 50 patients with bipolar I disorder (manic episode with psychotic features) were randomly assigned to receive lithium carbonate (up to a serum level of 0.8-1.5 mEq/L) or sodium valproate (20 mg/kg). After stabilization of acute manic phase, Temperament and Character Inventory was completed by the patients themselves. Fifty subjects completed this study. The mean age ± SD of participants in the sodium valproate group and lithium carbonate group was 32.99 ± 9.94 and 30.73±7.94 years, respectively. The responders to sodium valproate had significantly higher scores in novelty seeking, harm avoidance (P = 0.003 and 0.004, respectively) and lower scores in persistence (P = 0.006) than the non-responders, but the responders to lithium carbonate did not have significantly different personality profiles. The results of the present study revealed that the personality profiles in the inpatients with psychotic mania are related to the responses to sodium valproate, but are irrelevant to the responses to lithium carbonate.
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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) | 0.000 | 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) | 0.001 | 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".