Bibliographic record
Abstract
While clozapine has been demonstrated to be efficacious in refractory schizophrenia and possibly schizoaffective as well as bipolar disorders, a substantial number of patients still remain unresponsive. One strategy in treating these refractory patients is to augment clozapine with other somatic treatments. This article reviews the efficacy and safety of the combination of clozapine with other somatic treatments. A total of 70 articles were obtained from a manual, as well as computerized (Medline), search of the English language literature from 1978 to March 1998. Few controlled studies exist; most were case reports/series. From these data, the greatest risk of adverse effects seems to be associated with clozapine combined with benzodiazepines, valproate, or lithium, but no currently evaluated combination is absolutely unsafe. In terms of efficacy, the data suggest a number of potential augmentation strategies, although controlled data are few. Combination therapies with clozapine are common in clinical practice, despite a lack of empirical data, and the benefits and risks of these combinations need to be systematically reviewed.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".