Chlorpromazine for schizophrenia: a Cochrane systematic review of 50 years of randomised controlled trials
Bibliographic record
Abstract
BACKGROUND: Chlorpromazine (CPZ) remains one of the most common drugs used for people with schizophrenia worldwide, and a benchmark against which other treatments can be evaluated. Quantitative reviews are rare; this one evaluates the effects of chlorpromazine in the treatment of schizophrenia in comparison with placebo. METHODS: We sought all relevant randomised controlled trials (RCT) comparing chlorpromazine to placebo by electronic and reference searching, and by contacting trial authors and the pharmaceutical industry. Data were extracted from selected trials and, where possible, synthesised and random effects relative risk (RR), the number needed to treat (NNT) and their 95% confidence intervals (CI) calculated. RESULTS: Fifty RCTs from 1955-2000 were included with 5276 people randomised to CPZ or placebo. They constitute 2008 person-years spent in trials. Meta-analysis of these trials showed that chlorpromazine promotes a global improvement (n = 1121, 13 RCTs, RR 0.76 CI 0.7 to 0.9, NNT 7 CI 5 to 10), although a considerable placebo response is also seen. People allocated to chlorpromazine tended not to leave trials early in both the short (n = 945, 16 RCTs, RR 0.74 CI 0.5 to 1.1) and medium term (n = 1861, 25 RCTs, RR 0.79 CI 0.6 to 1.1). There were, however, many adverse effects. Chlorpromazine is sedating (n = 1242, 18 RCTs, RR 2.3 CI 1.7 to 3.1, NNH 6 CI 5 to 8), increases a person's chances of experiencing acute movement disorders, Parkinsonism and causes low blood pressure with dizziness and dry mouth. CONCLUSION: It is understandable why the World Health Organization (WHO) have endorsed and included chlorpromazine in their list of essential drugs for use in schizophrenia. Low- and middle-income countries may have more complete evidence upon which to base their practice compared with richer nations using recent innovations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.043 | 0.005 |
| 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 | 0.000 | 0.000 |
| 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 teacher head, 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".