Original research paper. Switching antipsychotics: Results of 16-month non-interventional, prospective, observational clinical research of inpatients with schizophrenia spectrum disorders

Predictors of antipsychotics switching among ambulatory patients with schizophrenia in Ethiopia: a multicenter hospital-based cross-sectional study

INTRODUCTION

A change of therapy from one to another antipsychotic medication is currently the main challenge of therapy. This study aimed to assess the prevalence of antipsychotic medication switches and determinants among patients with schizophrenia in Northwest Ethiopia.

METHODS

Multi-center hospital-based cross-sectional study was conducted at five Comprehensive Specialized Hospitals found in Northwest Ethiopia from April 30, 2021, to August 30, 2021. Data were extracted from both patients' medical charts and interviews. Data were entered into Epi-data software version 3.5.1 and exported to SPSS version 25.0 for analysis. A multivariable logistic regression model was fitted to identify factors associated with medication regimen switch. The level of significance of the study was kept at a p-value of 0.05 with a 95% confidence interval.

RESULT

A total of 414 patients are involved in the study, and 188 (45.5%) of patients switched antipsychotics within one year. The unavailability of the medication is the commonest reason for switching. Being male [AOR = 2.581, 95% CI (1.463, 4.552)], having relapse [AOR = 2.341,95% CI (1.169,4.687)], history of hospitalization in the past year [AOR = 3.00,95% CI (1.478,5.715)] and taking typical antipsychotics [AOR = 3.340, CI (1.76, 6.00)] had a significant association with antipsychotics switching.

CONCLUSIONS AND RECOMMENDATIONS

There is a high prevalence of antipsychotic switches among schizophrenia patients. Prescribers need to be careful while dosing, selecting, and switching antipsychotics, hence may help reduce discontinuation and unnecessary switch and thus achieve optimal clinical management.

Potential Drug-Drug Interactions among Patients with Schizophrenia Spectrum Disorders: Prevalence, Association with Risk Factors, and Replicate Analysis in 2021

Background and Objectives: Patients with schizophrenia are often exposed to polypharmacotherapy, which may lead to drug-drug interactions. The aim of the study was to investigate the prevalence of potential drug-drug interactions (pDDIs) in hospitalized patients with schizophrenia spectrum disorders and to identify factors associated with pDDIs and manifested symptoms and signs. Materials and Methods: This cross-sectional observational study included 311 inpatients admitted to a psychiatric hospital. The LexiComp drug interaction program was used to identify pDDIs in 2014. Factors associated with the prevalence of pDDIs and factors related to clinically observed symptoms and signs were assessed using multivariable regression. In addition, replicate analysis of pDDI was performed using 2021 program updates. Results: The prevalence of pDDIs was 88.7%. Our study showed that more than half of the patients received at least one drug combination that should be avoided. The most common pDDIs involved combinations of two antipsychotics or combinations of antipsychotics and benzodiazepines, which can lead to cardio-respiratory depression, sedation, arrhythmias, anticholinergic effects, and neuroleptic malignant syndrome. The number of prescribed drugs was a risk factor for pDDIs (OR 2.85; 95% CI 1.84-5.73). All groups of clinically observed symptoms and signs were associated with the number of drugs. In addition, symptoms and signs characteristic of the nervous system and psychiatric disorders were associated with antipsychotic dosage (IRR 1.33; 95% CI 1.12-1.58), which could contribute to the development of extrapyramidal syndrome, insomnia, anxiety, agitation, and bipolar mania. The 2021 version of the drug interaction program showed a shift in drug interactions toward a lower risk rating, implying less severe patient management and possibly less alert fatigue. Conclusions: Patients with schizophrenia spectrum disorders are at high risk of developing drug-drug interactions. Optimization of drug therapy, patient monitoring, and use of drug interaction programs could help to prevent pDDIs and subsequent adverse drug events.