Antipsychotic Polypharmacy Among Patients With Schizophrenia in Africa: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
OBJECTIVES: In Africa, antipsychotic polypharmacy (APP) is increasing due to a high antipsychotic dose prescribing, repeated psychiatric hospitalization, uncontrolled psychotic symptoms, and greater side effect burden. Therefore, the aim of this review and meta-analysis is to assess the prevalence and correlates of APP among patients with schizophrenia in Africa. METHODS: A systematic search was performed from August 1 to 31, 2020, on PubMed, MEDLINE, Google Scholar, and Science Direct databases to select articles based on the inclusion criteria. Meta-Analysis of Observational studies in Epidemiology guidelines were employed. Cross-sectional observational studies that reported APP and/or its correlates in schizophrenia patients in English language published in peer-reviewed journals without time limits were included in the review. The quality of included articles was assessed using Newcastle-Ottawa quality assessment tool. Prevalence and correlates of APP were the outcome measures of this review and meta-analysis. Open Meta Analyst and RevMan version 5.3 software were used for meta-analysis. A random effect model was used to synthesize data based on the heterogeneity test. RESULTS: Six studies that involved 2154 schizophrenia patients met the inclusion criteria in this review and meta-analysis. The quality of included studies ranges from 6.5 to 10 based on the Newcastle-Ottawa quality assessment tool. The pooled prevalence of APP among patients with schizophrenia was 40.6% with 95% confidence interval: 27.6% to 53.7%. Depot first-generation antipsychotics and oral first-generation antipsychotics were the most commonly prescribed APP combinations. Socio-demographic, clinical, and antipsychotic treatment characteristics were significantly associated with APP. There was a wide variation in the correlates of APP assessed by studies and the way that association/correlations was determined and reported. CONCLUSIONS: APP is common and highly prevalent. Advanced age, male gender, longer duration of schizophrenia, hospital admission, and longer antipsychotic treatment were correlates of APP in Africa.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 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".