Sleep architecture in ziprasidone-treated bipolar depression: a pilot study
Bibliographic record
Abstract
OBJECTIVES: This study investigated the effect of ziprasidone augmentation therapy on sleep architecture in bipolar depression. METHODS: We conducted a double-blind, randomized, placebo-controlled clinical pilot trial of ziprasidone versus placebo in Diagnostic and Statistical Manual of Mental Disorders, fourth edition bipolar disorder with current major depressive episode. The effects during acute (2-5 days) and continuation treatment (28-31 days) were measured. Main outcomes were sleep architecture variables including rapid eye movement sleep (REM) and slow wave sleep (SWS) measured by polysomnography. Secondary outcomes included subjective sleep quality measures and illness severity measures including the 17-item Hamilton Depression Rating Scale (HAMD-17), Montgomery Asberg Depression Rating Scale (MADRS), Hamilton Anxiety Rating Scale (HAMA) and Clinical Global Illness Severity (CGI-S) scores. RESULTS: The completer analysis comprised of 14 patients (ziprasidone, N = 8 and placebo, N = 6). Latency to REM, duration of SWS, duration of stage 2 sleep, total sleep time, onset to sleep latency, number of awakenings and overall sleep efficiency significantly improved in ziprasidone-treated participants over placebo. CGI-S and HAMA scores also significantly improved. No significant difference between treatment groups was seen on the HAMD-17, MADRS or in self-reported sleep quality. Increase in SWS duration significantly correlated with improvement in CGI-S, however, this finding did not withstand Bonferroni correction. CONCLUSION: Adjunctive ziprasidone treatment alters sleep architecture in patients with bipolar depression, which may partially explain its mechanism of action and merits further investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".