ABSTRACT
The augmentation of clozapine with electroconvulsive therapy (ECT) has been an optimal treatment option for patients with treatment- or clozapine-resistant schizophrenia. Using data from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics survey, which was the largest international psychiatry research collaboration in Asia, our study aimed to develop a machine learning algorithm-based substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in terms of precision medicine. A random forest model and least absolute shrinkage and selection operator (LASSO) model were used to develop a substantial prediction model for the augmented use of clozapine with ECT. Among the 3744 Asian patients with schizophrenia, those treated with a combination of clozapine and ECT were characterized by significantly greater proportions of females and inpatients, a longer duration of illness, and a greater prevalence of negative symptoms and social or occupational dysfunction than those not treated. In the random forest model, the area under the curve (AUC), which was the most preferred indicator of the prediction model, was 0.774. The overall accuracy was 0.817 (95% confidence interval, 0.793−0.839). Inpatient status was the most important variable in the substantial prediction model, followed by BMI, age, social or occupational dysfunction, persistent symptoms, illness duration > 20 years, and others. Furthermore, the AUC and overall accuracy of the LASSO model were 0.831 and 0.644 (95% CI, 0.615−0.672), respectively. Despite the subtle differences in both AUC and overall accuracy of the random forest model and LASSO model, the important variables were commonly shared by the two models. Using the machine learning algorithm, our findings allow the development of a substantial prediction model for the augmented use of clozapine with ECT in Asian patients with schizophrenia. This substantial prediction model can support further studies to develop a substantial prediction model for the augmented use of clozapine with ECT in patients with schizophrenia in a strict epidemiological context.
ABSTRACT
The symptom heterogeneity of schizophrenia is consistent with Wittgenstein's analogy of a language game. From the perspective of precision medicine, this study aimed to estimate the symptom presentation and identify the psychonectome in Asian patients, using data obtained from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics. We constructed a network structure of the Brief Psychiatric Rating Scale (BPRS) items in 1438 Asian patients with schizophrenia. Furthermore, all the BPRS items were considered to be an ordered categorical variable ranging in value from 1-7. Motor retardation was situated most centrally within the BPRS network structure, followed by depressive mood and unusual thought content. Contrastingly, hallucinatory behavior was situated least centrally within the network structure. Using a community detection algorithm, the BPRS items were organized into positive, negative, and general symptom clusters. Overall, DSM symptoms were not more central than non-DSM symptoms within the symptom network of Asian patients with schizophrenia. Thus, motor retardation, which results from the unmet needs associated with current antipsychotic medications for schizophrenia, may be a tailored treatment target for Asian patients with schizophrenia. Based on these findings, targeting non-dopamine systems (glutamate, γ-aminobutyric acid) may represent an effective strategy with respect to precision medicine for psychosis.
ABSTRACT
BACKGROUND: Although an inverse relationship between body mass index (BMI) and Parkinson disease (PD) has been repeatedly reported, to our knowledge, the relationship between BMI and antipsychotic-induced extrapyramidal symptoms (EPS) has rarely been studied in patients with schizophrenia. Our study aimed to evaluate the relationship between BMI and EPS in patients with schizophrenia. SUBJECTS AND METHODS: Using data from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics (REAP-AP) study, we compared the prevalence of EPS in 1448 schizophrenia patients stratified as underweight, normal range, overweight pre-obese, overweight obese I, overweight obese II, and overweight obese III according to the World Health Organization (WHO) classification system for body weight status, and with underweight, normal range, overweight at risk, overweight obese I, and overweight obese II according to the Asia-Pacific obesity classification. RESULTS: In the first step of the WHO classification system for body weight status, adjusting for the potential effects of confounding factors, the multinomial logistic regression model revealed that underweight was significantly associated with greater rates of bradykinesia and muscle rigidity, and a lower rate of gait disturbance. In the second step of the Asia-Pacific obesity classification, adjusting for the potential effects of confounding factors, the multinomial logistic regression model revealed that underweight was significantly associated with a higher rate of muscle rigidity. CONCLUSION: Findings of the present study consistently revealed that underweight was associated with a greater rate of muscle rigidity in a stepwise pattern among Asian patients with schizophrenia. Although the mechanism underlying the inverse relationship between BMI and muscle rigidity cannot be sufficiently explained, it is speculated that low BMI may contribute to the development of muscle rigidity regardless of antipsychotic "typicality" and dose in patients with schizophrenia.
