Early Use of Clozapine for Poorly Responding First-Episode Psychosis
Bibliographic record
Abstract
Although most patients treated for first-episode schizophrenia will experience considerable improvement with initial antipsychotic therapy, a subgroup experiences significant ongoing positive symptoms. Clozapine has unique efficacy in improving treatment-resistant patients with chronic schizophrenia, but its role in the treatment of first-episode patients remains unclear. A standardized treatment algorithm was implemented in our First Episode Psychosis Program, with patients receiving 2 trials with 2 second-generation antipsychotics (olanzapine, quetiapine, or risperidone at low, medium, and high doses), followed by a trial of clozapine as early as 25 weeks into the start of their treatment. Patients progress along the algorithm according to their response as defined by clinical rating scales. To date, 123 patients with first-episode schizophrenia have been treated according to the algorithm. Of these, 93 (76%) responded to the first trial of an antipsychotic. Only 7 (23%) of the remaining 30 patients responded to a second antipsychotic trial; 13 of the remaining 23 individuals agreed to a trial of clozapine. We compared the clozapine-treated group with a group of 9 patients who refused clozapine and chose to continue the same antipsychotic treatment as before. Subjects who received clozapine experienced a mean Brief Psychiatric Rating Scale change of 19 points (from 53.5 to 34.5) and a change in the Clinical Global Inventory severity rating from 5.4 to 3.5 (from severely ill to mildly ill); those who refused clozapine had a 2-point increase in mean Brief Psychiatric Rating Scale (from 53 to 55) and a 0.6-point increase in the mean Clinical Global Inventory severity rating from 5.4 to 6 (remaining markedly to severely ill). In clinical practice, there is a hesitancy to switch individuals to clozapine given its side effect profile and position as treatment of "last resort." The present findings suggest that clozapine may have an important role in the early treatment of first-episode patients whose psychosis does not remit with other second-generation antipsychotics during the first months of treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".