Meta-Analyses of Mood Stabilizers, Antidepressants and Antipsychotics in the Treatment of Borderline Personality Disorder: Effectiveness for Depression and Anger Symptoms
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Bibliographic record
Abstract
The objective of our study was to complete separate meta-analyses of randomized controlled trials of mood stabilizers, antidepressants and antipsychotics to determine whether these medications are efficacious for depression and anger symptoms in borderline personality disorder (BPD). Studies were obtained from OVID Medline, Cochrane Central Register of Controlled Trials, and PsychInfo. References of all original papers and reviews were searched for additional studies. Index terms included: BPD, randomized controlled trials, drug therapy, medication, and treatment. Studies were included if they were randomized double-blind placebo-controlled trials, published in a peer reviewed journal, had a majority of patients with BPD or included patients with BPD where anger was a target of treatment. Preference was given to studies using outcome measures that were well known, validated, objective, and based on intent-to-treat data. Where available, measures of anger that incorporated verbal and other indirect forms of aggression were utilized. The StatsDirect meta-analysis program was used to calculate an effect size and 95% confidence interval for each study. Mood stabilizers, with the exception of divalproic acid, were found to have a large pooled effect size (-1.75, 95% CI = -2.77 to -0.74) for anger. Divalproic acid and carbamazepine had a moderate effect on depression. Antidepressants had a moderate effect on anger reduction, but a small effect on depression. Antipsychotics had a moderate effect on anger; however aripiprazole had a much larger effect-size than other antipsychotics. Antipsychotics did not have an effect for depression. Sources of variation between studies included length of treatment (5-24 weeks), drop out rates (5% to 65%), proportion of patients in psychotherapy (0-100%) and with comorbid mood disorders (0-100%). Unfortunately most studies excluded patients with alcohol and substance abuse, suicidality, and self-harm behaviors. This may limit the ability to generalize our findings to usual clinical practice.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| 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) | 0.000 | 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 it