Antipsychotic prescribing patterns on admission to and at discharge from a tertiary care program for treatment-resistant psychosis
Bibliographic record
Abstract
Retrospective data were collected from 330 individuals who were treated at a tertiary care program for treatment-resistant psychosis between 1994 and 2010. The main objectives were to compare the use of antipsychotic monotherapy to polypharmacy and to characterize within-individual changes in treatment and symptomatology between admission and discharge. At admission, individuals who were prescribed only one antipsychotic were comparable to those who were prescribed at least two antipsychotics with regard to demographics and symptom severity. The use of psychotropic medications other than antipsychotics was also similar between the two groups. However, the magnitude of antipsychotic utilization was greater in individuals who were receiving antipsychotic polypharmacy. In addition, a greater proportion received excessive doses at admission. Similar findings were observed when the two antipsychotic prescribing practices were compared at discharge. Three important patterns were identified when investigating within-individual changes. First, fewer individuals were prescribed more than one antipsychotic at discharge. This was accompanied by a general decrease in the magnitude of antipsychotic utilization. Second, the number of individuals who were prescribed clozapine had increased by discharge. Most who were already prescribed clozapine at admission had their doses increased. Third, improvements in symptomatology were observed across all of the subscales included in the Positive and Negative Symptom Scale (PANSS); 57.9% of individuals experienced a relative reduction in total PANSS scores exceeding 20%. Based on these findings, it is possible to alleviate symptom severity while reducing antipsychotic utilization when patients are treated at a tertiary care program for treatment-resistant psychosis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".