P.3.c.024 Risperidone long-acting formulation in treatment-resistant schizophrenic patients: the predictive value of plasma levels in relation to clinical response and safety

Background: Schizophrenia and schizoaffective disorder are treated with antipsychotic drugs. Some patients show treatment-resistant forms of psychotic disorders and, in this case, they can be treated with clozapine. In these patients and based on previous reviews on novel antipsychotic drugs, it is important to know whether an add-on therapy with new drugs can ameliorate the positive and negative schizophrenic scale (PANSS) total score. Objective: The aim of this review is to suggest an appropriate treatment for patients with treatment-resistant forms of psychotic disorders. A combination of current available antipsychotic drugs with novel antipsychotic or modulating drugs might improve negative schizophrenic symptoms and cognitive function and thereby social functioning and quality of life. Results: The mechanisms of action, the therapeutic effects and the pharmacokinetic profiles of novel antipsychotic drugs such as cariprazine, brexipiprazole and lumateperone are up-dated. Published case reports of patients with treatmentresistant psychoses are also discussed. These patients were treated with clozapine but a high PANSS total score was observed. Only an add-on therapy with cariprazine improved the score and, above all, negative schizophrenic symptoms and cognitive functions. To ensure a constant antipsychotic drug concentration, long-acting injectable antipsychotic drugs may be a choice for a maintenance therapy in schizophrenia. New modulating drugs, such as receptor positive allosteric modulators (N-methyl-D-aspartate receptor; subtype 5 of the metabotropic glutamatergic receptor) and encenicline, an alpha7 nicotinic cholinergic receptor agonist, are being investigated in preclinical and clinical trials. Conclusion: In clinical trials, patients with treatment-resistant forms of psychosis should be examined to know whether a combination therapy with clozapine and a novel antipsychotic drug can ameliorate the PANSS total score. In schizophrenia, long-acting injectable antipsychotic drugs are a safe and tolerable maintenance therapy. In further clinical studies, it should be investigated whether patients with treatment-resistant forms of psychoses can improve negative schizophrenic symptoms and cognitive functions by an add-on therapy with cognition enhancing drugs.

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Development and Evaluation of Computable Phenotypes in Pediatric Epilepsy:3 Cases

Journal of Child Neurology ◽

10.1177/08830738211019578 ◽

2021 ◽

pp. 088307382110195

Author(s):

Sabrina Pan ◽

Alan Wu ◽

Mark Weiner ◽

Zachary M Grinspan

Keyword(s):

Positive Predictive Value ◽

Predictive Value ◽

Juvenile Myoclonic Epilepsy ◽

Myoclonic Epilepsy ◽

Hypoxic Ischemic Encephalopathy ◽

Pediatric Epilepsy ◽

Health Record ◽

Treatment Resistant ◽

Ischemic Encephalopathy ◽

F Measure

Introduction: Computable phenotypes allow identification of well-defined patient cohorts from electronic health record data. Little is known about the accuracy of diagnostic codes for important clinical concepts in pediatric epilepsy, such as (1) risk factors like neonatal hypoxic-ischemic encephalopathy; (2) clinical concepts like treatment resistance; (3) and syndromes like juvenile myoclonic epilepsy. We developed and evaluated the performance of computable phenotypes for these examples using electronic health record data at one center. Methods: We identified gold standard cohorts for neonatal hypoxic-ischemic encephalopathy, pediatric treatment-resistant epilepsy, and juvenile myoclonic epilepsy via existing registries and review of clinical notes. From the electronic health record, we extracted diagnostic and procedure codes for all children with a diagnosis of epilepsy and seizures. We used these codes to develop computable phenotypes and evaluated by sensitivity, positive predictive value, and the F-measure. Results: For neonatal hypoxic-ischemic encephalopathy, the best-performing computable phenotype (HIE ICD-9 /10 and [brain magnetic resonance imaging (MRI) or electroencephalography (EEG) within 120 days of life] and absence of commonly miscoded conditions) had high sensitivity (95.7%, 95% confidence interval [CI] 85-99), positive predictive value (100%, 95% CI 95-100), and F measure (0.98). For treatment-resistant epilepsy, the best-performing computable phenotype (3 or more antiseizure medicines in the last 2 years or treatment-resistant ICD-10) had a sensitivity of 86.9% (95% CI 79-93), positive predictive value of 69.6% (95% CI 60-79), and F-measure of 0.77. For juvenile myoclonic epilepsy, the best performing computable phenotype (JME ICD-10) had poor sensitivity (52%, 95% CI 43-60) but high positive predictive value (90.4%, 95% CI 81-96); the F measure was 0.66. Conclusion: The variable accuracy of our computable phenotypes (hypoxic-ischemic encephalopathy high, treatment resistance medium, and juvenile myoclonic epilepsy low) demonstrates the heterogeneity of success using administrative data to identify cohorts important for pediatric epilepsy research.

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