Levomepromazine versus chlorpromazine in treatment-resistant schizophrenia: a double-blind randomized trial
Bibliographic record
Abstract
OBJECTIVE: We compared the effect of levomepromazine (LMP) with chlorpromazine (CPZ) in treatment-resistant schizophrenia (TRS). METHODS: We carried out a double-blind, parallel group study (n = 19/arm) with balanced randomization in blocks of 4 and stratification by sex. Subjects entered a 30-week trial, of which phases I-III were open: phase I (wk 0-6) baseline; phase II (wk 7-9) stepwise transition to haloperidol (HAL), 30 mg/d, plus benztropine (BT), 4 mg/d; phase III (wk 10-15) HAL, 40-60 mg/d, plus BT, 4-6 mg/d; phase IV (wk 16-20) stepwise transition to LMP or CPZ (500 mg/d) following randomization; phase V (wk 21-28) stepwise increase of LMP or CPZ (600-1000 mg/d, dose reduction permitted) to establish optimum dose; and phase VI (wk 29-30) optimized dose maintained. Criteria for TRS were based on those established by Kane et al in 1988. The criterion for a response to treatment was a reduction of 25% or more in total Brief Psychiatric Rating Scale score. RESULTS: Both LMP (p = 0.007) and CPZ (p = 0.030) improved TRS relative to baseline. Although there was no significant difference between the 2 groups in treatment response at study end point, hierarchical linear modelling of longitudinal outcome revealed a significant (p = 0.006) advantage of LMP over CPZ for the BPRS total score. Ten of 19 participants on LMP and 8 of 19 on CPZ met the criterion for treatment response, and 9 of the 18 responders did so on 200-700 mg/d phenothiazine. The mean dose of responders was 710 (standard deviation [SD] 265) mg/d (LMP) and 722 (SD 272) mg/d (CPZ). Akathisia was associated with a nonresponse to phenothiazines (p = 0.010). BPRS scores increased significantly on HAL (p = 0.006). Two of 19 participants on LMP and 5 of 19 on CPZ withdrew early from the study. CONCLUSION: LMP and CPZ may be useful in the management of TRS. A modest advantage of LMP compared with CPZ was seen in longitudinal analysis. High doses of neuroleptics may contribute to TRS; reduction of neuroleptics to modest or moderate doses should be considered before categorizing a patient as treatment resistant.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".