Long-term efficacy of risperidone long-acting injectable in bipolar disorder with psychotic features
Bibliographic record
Abstract
Bipolar disorder (BD) with psychotic features is a difficult-to-treat form of the illness that is associated with a poor prognosis. We hypothesized that treatment with adjunctive risperidone long-acting injectable (RLAI) is well-tolerated and efficacious in treating patients with psychotic BD. Ten patients with BDI or BDII with psychotic features who were refractory to earlier treatments were prescribed adjunctive open-label RLAI 25-62.5 mg q twice weekly. The patients were followed prospectively for 3 years. The severity of mood and psychotic symptoms was measured using clinical rating scales, and information regarding relapses, hospitalizations, extra-pyramidal symptom, weight gain, and other side effects was also gathered. Young Mania Rating Scale scores, Montgomery Asberg Depression Rating Scale scores, psychosis rating scale scores, and the numbers of mood episodes and hospitalizations were reduced during 3 years of RLAI therapy compared with an equivalent pretreatment period. Only three patients experienced relapses with psychotic symptoms. Functional outcomes were also improved, with substantial numbers of previously disabled patients able to return to gainful employment and independent living. RLAI was associated with minimal extra-pyramidal symptom, modest weight gain, and few other side effects. Adjunctive RLAI can be considered as a treatment option in patients with psychotic BD.
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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".