Psychiatric Comorbidities and Schizophrenia in Youths With Attention-Deficit/Hyperactivity Disorder.

Importance: The association between attention-deficit/hyperactivity disorder (ADHD) and schizophrenia has received increased attention; however, evidence on the association between psychiatric comorbidities and subsequent schizophrenia in patients with ADHD is limited. Objective: To investigate the risk of being diagnosed with schizophrenia in children and adolescents with ADHD considering the presence of psychiatric comorbidity. Design, Setting, and Participants: This was a population-based, retrospective cohort study using the Health Insurance Review and Assessment claims database from January 1, 2007, to December 31, 2019. Participants were children and adolescents aged 5 to 19 years who received an ADHD diagnosis between January 1, 2010, and December 31, 2018, in the nationwide claims data of Korea. Data were analyzed from January 2010 to December 2019. Interventions or Exposures: The presence of psychiatric comorbidity was assessed from diagnosis records within 1 year before ADHD diagnosis. Comorbidities were further categorized according to the number of comorbidities and specific comorbid disorders. Main Outcomes and Measures: Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% CIs, examining the association between psychiatric comorbidities and the risk of being diagnosed with schizophrenia. Furthermore, the occurrence of psychiatric comorbidity during the follow-up period was explored among patients without psychiatric comorbidity at baseline. Results: A total of 211 705 patients with newly diagnosed ADHD were included. A total of 157 272 patients (74.3%) were male, and the age of 5 to 9 years showed the highest distribution (115 081 patients [54.4%]). Patients with psychiatric comorbidity had a significantly higher risk of being diagnosed with schizophrenia than those without (adjusted HR, 2.14; 95% CI, 2.05-2.23). The association between schizophrenia and psychiatric comorbidity became progressively greater with the increasing number of comorbidities. Several individual psychiatric disorders showed an association with development of schizophrenia, with ASD, intellectual disability, tic disorder, depression, and bipolar disorder being the top 5 disorders most associated. Furthermore, 3244 patients (73.8%) without psychiatric comorbidities experienced the emergence of other psychiatric disorders before schizophrenia occurrence. Conclusions and Relevance: In this retrospective cohort study involving children and adolescents with ADHD, the presence of psychiatric comorbidity in patients with ADHD was associated with an increased risk of being diagnosed with schizophrenia, with an increased risk observed in multiple comorbidities and a wide variety of comorbidities. These findings highlight the significance of assessing and managing psychiatric comorbidities in patients with ADHD to decrease subsequent schizophrenia risk and allow for early intervention.

Application of tree-based machine learning classification methods to detect signals of fluoroquinolones using the Korea Adverse Event Reporting System (KAERS) database.

BACKGROUND: Safety issues for fluoroquinolones have been provided by regulatory agencies. This study was conducted to identify signals of fluoroquinolones reported in the Korea Adverse Event Reporting System (KAERS) using tree-based machine learning (ML) methods. RESEARCH DESIGN AND METHODS: All adverse events (AEs) associated with the target drugs reported in the KAERS from 2013 to 2017 were matched with drug label information. A dataset containing label-positive and -negative AEs was arbitrarily divided into training and test sets. Decision tree, random forest (RF), bagging, and gradient boosting machine (GBM) were fitted on the training set with hyperparameters tuned using five-fold cross-validation and applied to the test set. The ML method with the highest area under the curve (AUC) scores was selected as the final ML model. RESULTS: Bagging was selected as the final ML model for gemifloxacin (AUC score: 1) and levofloxacin (AUC: 0.9987). RF was selected in ciprofloxacin, moxifloxacin, and ofloxacin (AUC scores: 0.9859, 0.9974, and 0.9999 respectively). We found that the final ML methods detected additional signals that were not detected using the disproportionality analysis (DPA) methods. CONCLUSIONS: The bagging-or-RF-based ML methods performed better than DPA and detected novel AE signals previously unidentified using the DPA methods.

Anti-inflammatory activity of ethanol extract derived from Phaseolus angularis beans.

ETHNOPHARMACOLOGICAL SIGNIFICANCE: Phaseolus angularis Wight (adzuki bean) is an ethnopharmacologically well-known folk medicine that is prescribed for infection, edema, and inflammation of the joints, appendix, kidney and bladder in Korea, China and Japan. AIM OF STUDY: The anti-inflammatory effect of this plant and its associated molecular mechanisms will be investigated. MATERIALS AND METHODS: The immunomodulatory activity of Phaseolus angularis ethanol extract (Pa-EE) in toll like receptor (TLR)-activated macrophages induced by ligands such as lipopolysaccharide (LPS), Poly (I:C), and pam3CSK was investigated by assessing nitric oxide (NO) and prostaglandin (PG)E(2) levels. To identify which transcription factors such as nuclear factor (NF)-κB and their signaling enzymes can be targeted to Pa-EE, biochemical approaches including reporter gene assays, immunoprecipitation, kinase assays, and immunoblot analyses were also employed. Finally, whether Pa-EE was orally available, ethanol (EtOH)/hydrochloric acid (HCl)-induced gastritis model in mice was used. RESULTS: Pa-EE dose-dependently suppressed the release of PGE(2) and NO in LPS-, Poly(I:C)-, and pam3CSK-activated macrophages. Pa-EE strongly down-regulated LPS-induced mRNA expression of inducible NO synthase (iNOS) and cyclooxygenase (COX)-2. Interestingly, Pa-EE markedly inhibited NF-κB, activator protein (AP)-1, and cAMP response element binding protein (CREB) activation; further, according to direct kinase assays and immunoblot analyses, Pa-EE blocked the activation of the upstream signaling molecules spleen tyrosine kinase (Syk), p38, and transforming growth factor ß-activated kinase 1 (TAK1). Finally, orally administered Pa-EE clearly ameliorated EtOH/HCl-induced gastritis in mice. CONCLUSION: Our results suggest that Pa-EE can be further developed as a promising anti-inflammatory remedy because it targets multiple inflammatory signaling enzymes and transcription factors.