Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background/Aims: Infliximab treatment failure in patients with inflammatory bowel disease may result from sub-optimal infliximab trough level. An understanding of pharmacokinetics (PKs) is important to maintain an optimal trough level. PK studies of the switch to subcutaneous (SC) infliximab from intravenous (IV) infliximab using real-world data are lacking. We aimed to develop a population PK model of IV and SC infliximab to predict individual infliximab exposure during maintenance therapy. Methods: We used data from prospectively collected data on IV and SC infliximab concentrations in patients with inflammatory bowel disease receiving maintenance treatment from February 2020 to December 2022 at Samsung Medical Center. Population PK analysis was conducted by using a two-compartment model with first-order absorption and first-order elimination. Goodness-of-fit plots and visual predictive check were used to evaluate the PK model. Results: A total of 2,132 samples from 181 patients (149 Crohn’s disease and 32 ulcerative colitis) were analyzed. We developed an infliximab population PK model using body mass index, albumin, C-reactive protein level, and the anti-drug antibody level and validated its predictive performance. Conclusions It may be possible to predict the infliximab trough level of both IV and SC infliximab in patients with inflammatory bowel disease during maintenance treatment by using our model in real-world practice.

Background/Aims: Infliximab treatment failure in patients with inflammatory bowel disease may result from sub-optimal infliximab trough level. An understanding of pharmacokinetics (PKs) is important to maintain an optimal trough level. PK studies of the switch to subcutaneous (SC) infliximab from intravenous (IV) infliximab using real-world data are lacking. We aimed to develop a population PK model of IV and SC infliximab to predict individual infliximab exposure during maintenance therapy. Methods: We used data from prospectively collected data on IV and SC infliximab concentrations in patients with inflammatory bowel disease receiving maintenance treatment from February 2020 to December 2022 at Samsung Medical Center. Population PK analysis was conducted by using a two-compartment model with first-order absorption and first-order elimination. Goodness-of-fit plots and visual predictive check were used to evaluate the PK model. Results: A total of 2,132 samples from 181 patients (149 Crohn’s disease and 32 ulcerative colitis) were analyzed. We developed an infliximab population PK model using body mass index, albumin, C-reactive protein level, and the anti-drug antibody level and validated its predictive performance. Conclusions It may be possible to predict the infliximab trough level of both IV and SC infliximab in patients with inflammatory bowel disease during maintenance treatment by using our model in real-world practice.

Background/Aims: Infliximab treatment failure in patients with inflammatory bowel disease may result from sub-optimal infliximab trough level. An understanding of pharmacokinetics (PKs) is important to maintain an optimal trough level. PK studies of the switch to subcutaneous (SC) infliximab from intravenous (IV) infliximab using real-world data are lacking. We aimed to develop a population PK model of IV and SC infliximab to predict individual infliximab exposure during maintenance therapy. Methods: We used data from prospectively collected data on IV and SC infliximab concentrations in patients with inflammatory bowel disease receiving maintenance treatment from February 2020 to December 2022 at Samsung Medical Center. Population PK analysis was conducted by using a two-compartment model with first-order absorption and first-order elimination. Goodness-of-fit plots and visual predictive check were used to evaluate the PK model. Results: A total of 2,132 samples from 181 patients (149 Crohn’s disease and 32 ulcerative colitis) were analyzed. We developed an infliximab population PK model using body mass index, albumin, C-reactive protein level, and the anti-drug antibody level and validated its predictive performance. Conclusions It may be possible to predict the infliximab trough level of both IV and SC infliximab in patients with inflammatory bowel disease during maintenance treatment by using our model in real-world practice.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Background/Aims: Infliximab treatment failure in patients with inflammatory bowel disease may result from sub-optimal infliximab trough level. An understanding of pharmacokinetics (PKs) is important to maintain an optimal trough level. PK studies of the switch to subcutaneous (SC) infliximab from intravenous (IV) infliximab using real-world data are lacking. We aimed to develop a population PK model of IV and SC infliximab to predict individual infliximab exposure during maintenance therapy. Methods: We used data from prospectively collected data on IV and SC infliximab concentrations in patients with inflammatory bowel disease receiving maintenance treatment from February 2020 to December 2022 at Samsung Medical Center. Population PK analysis was conducted by using a two-compartment model with first-order absorption and first-order elimination. Goodness-of-fit plots and visual predictive check were used to evaluate the PK model. Results: A total of 2,132 samples from 181 patients (149 Crohn’s disease and 32 ulcerative colitis) were analyzed. We developed an infliximab population PK model using body mass index, albumin, C-reactive protein level, and the anti-drug antibody level and validated its predictive performance. Conclusions It may be possible to predict the infliximab trough level of both IV and SC infliximab in patients with inflammatory bowel disease during maintenance treatment by using our model in real-world practice.

Background: The World Health Organization has declared the end of the coronavirus disease 2019 (COVID-19) public health emergency. However, this did not indicate the end of COVID-19. Several months after the infection, numerous patients complain of respiratory or nonspecific symptoms; this condition is called long COVID. Even patients with mild COVID-19 can experience long COVID, thus the burden of long COVID remains considerable. Therefore, we conducted this study to comprehensively analyze the effects of long COVID using multi-faceted assessments. Materials and Methods: We conducted a prospective cohort study involving patients diagnosed with COVID-19 between February 2020 and September 2021 in six tertiary hospitals in Korea. Patients were followed up at 1, 3, 6, 12, 18, and 24 months after discharge. Long COVID was defined as the persistence of three or more COVID-19-related symptoms. The primary outcome of this study was the prevalence of long COVID after the period of COVID-19. Results: During the study period, 290 patients were enrolled. Among them, 54.5 and 34.6% experienced long COVID within 6 months and after more than 18 months, respectively. Several patients showed abnormal results when tested for post-traumatic stress disorder (17.4%) and anxiety (31.9%) after 18 months. In patients who underwent follow-up chest computed tomography 18 months after COVID-19, abnormal findings remained at 51.9%. Males (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.05–0.53; P=0.004) and elderly (OR, 1.04; 95% CI, 1.00–1.09; P=0.04) showed a significant association with long COVID after 12–18 months in a multivariable logistic regression analysis. Conclusion Many patients still showed long COVID after 18 months post SARS-CoV-2 infection. When managing these patients, the assessment of multiple aspects is necessary.

Purpose: The purpose of this study is to determine the impact of adverse childhood experiences, positive childhood experiences, and community integration on resilience in psychiatric outpatients. Methods: The study subjects were 166 psychiatric outpatients in one general hospital in South Korea who were diagnosed with schizophrenia spectrum disorder, bipolar disorder, or depression disorder. The collected data were analyzed with the t-test, ANOVA, Pearson’s correlation coefficient, multiple regression analysis, using the SPSS/WIN 24 program. Results: There were statistically significant differences in resilience in psychiatric outpatients according to age, religion, occupation, type of household, type of diagnosed disorder. In psychiatric outpatients, resilience showed a significant positive correlation with benevolent childhood experiences and community integration, but had a negative correlation with adverse childhood experiences. Multiple regression analysis for resilience in psychiatric outpatients revealed that the significant factors affecting resilience were community integration, benevolent childhood experiences, adverse childhood experiences, housing facilities (type of household), ages 40-49, and living alone (type of household). These factors explained 52.2% of the variance. Conclusion In order to improve the resilience of mentally ill people, a campaign is needed to increase the accessibility of community participation programs in mental health services for community integration and to publicize the influence of benevolent childhood experiences and adverse childhood experiences. Furthermore, it is necessary to identify individual factors such as residence type and age of mentally ill people, build a customized support system by considering their specific needs, and develop intervention programs to strengthen resilience.

Purpose: The purpose of this study is to determine the impact of adverse childhood experiences, positive childhood experiences, and community integration on resilience in psychiatric outpatients. Methods: The study subjects were 166 psychiatric outpatients in one general hospital in South Korea who were diagnosed with schizophrenia spectrum disorder, bipolar disorder, or depression disorder. The collected data were analyzed with the t-test, ANOVA, Pearson’s correlation coefficient, multiple regression analysis, using the SPSS/WIN 24 program. Results: There were statistically significant differences in resilience in psychiatric outpatients according to age, religion, occupation, type of household, type of diagnosed disorder. In psychiatric outpatients, resilience showed a significant positive correlation with benevolent childhood experiences and community integration, but had a negative correlation with adverse childhood experiences. Multiple regression analysis for resilience in psychiatric outpatients revealed that the significant factors affecting resilience were community integration, benevolent childhood experiences, adverse childhood experiences, housing facilities (type of household), ages 40-49, and living alone (type of household). These factors explained 52.2% of the variance. Conclusion In order to improve the resilience of mentally ill people, a campaign is needed to increase the accessibility of community participation programs in mental health services for community integration and to publicize the influence of benevolent childhood experiences and adverse childhood experiences. Furthermore, it is necessary to identify individual factors such as residence type and age of mentally ill people, build a customized support system by considering their specific needs, and develop intervention programs to strengthen resilience.

Purpose: The purpose of this study is to determine the impact of adverse childhood experiences, positive childhood experiences, and community integration on resilience in psychiatric outpatients. Methods: The study subjects were 166 psychiatric outpatients in one general hospital in South Korea who were diagnosed with schizophrenia spectrum disorder, bipolar disorder, or depression disorder. The collected data were analyzed with the t-test, ANOVA, Pearson’s correlation coefficient, multiple regression analysis, using the SPSS/WIN 24 program. Results: There were statistically significant differences in resilience in psychiatric outpatients according to age, religion, occupation, type of household, type of diagnosed disorder. In psychiatric outpatients, resilience showed a significant positive correlation with benevolent childhood experiences and community integration, but had a negative correlation with adverse childhood experiences. Multiple regression analysis for resilience in psychiatric outpatients revealed that the significant factors affecting resilience were community integration, benevolent childhood experiences, adverse childhood experiences, housing facilities (type of household), ages 40-49, and living alone (type of household). These factors explained 52.2% of the variance. Conclusion In order to improve the resilience of mentally ill people, a campaign is needed to increase the accessibility of community participation programs in mental health services for community integration and to publicize the influence of benevolent childhood experiences and adverse childhood experiences. Furthermore, it is necessary to identify individual factors such as residence type and age of mentally ill people, build a customized support system by considering their specific needs, and develop intervention programs to strengthen resilience.