Symptoms and Conditions in Children and Adults up to 90 Days after SARS-CoV-2 Infection: A Retrospective Observational Study Utilizing the Common Data Model.

Background/Objectives: There have been widespread reports of persistent symptoms in both children and adults after SARS-CoV-2 infection, giving rise to debates on whether it should be regarded as a separate clinical entity from other postviral syndromes. This study aimed to characterize the clinical presentation of post-acute symptoms and conditions in the Korean pediatric and adult populations. Methods: A retrospective analysis was performed using a national, population-based database, which was encoded using the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). We compared individuals diagnosed with SARS-CoV-2 to those diagnosed with influenza, focusing on the risk of developing prespecified symptoms and conditions commonly associated with the post-acute sequelae of COVID-19. Results: Propensity score matching yielded 1,656 adult and 343 pediatric SARS-CoV-2 and influenza pairs. Ninety days after diagnosis, no symptoms were found to have elevated risk in either adults or children when compared with influenza controls. Conversely, at 1 day after diagnosis, adults with SARS-CoV-2 exhibited a significantly higher risk of developing abnormal liver function tests, cardiorespiratory symptoms, constipation, cough, thrombophlebitis/thromboembolism, and pneumonia. In contrast, children diagnosed with SARS-CoV-2 did not show an increased risk for any symptoms during either acute or post-acute phases. Conclusions: In the acute phase after infection, SARS-CoV-2 is associated with an elevated risk of certain symptoms in adults. The risk of developing post-acute COVID-19 sequelae is not significantly different from that of having postviral symptoms in children in both the acute and post-acute phases, and in adults in the post-acute phase. These observations warrant further validation through studies, including the severity of initial illness, vaccination status, and variant types.

Safety outcomes of antipsychotics classes in drug-naïve patients with first-episode schizophrenia: A nationwide cohort study in South Korea.

INTRODUCTION: Given the similar efficacies across antipsychotic medications for schizophrenia, understanding their safety profiles, particularly concerning receptor-binding differences, is crucial for optimal drug selection, especially for patients with first episode schizophrenia. We aimed to compare the safety outcomes of second-generation antipsychotics. METHODS: We conducted a retrospective cohort study with new user active comparator design using a nationwide claims database in South Korea. Participants were drug-naïve adult patients with first-episode schizophrenia. Three representative drugs with different pharmacologic profiles were compared: risperidone, olanzapine, and aripiprazole. Propensity scores were used to match the study groups, and the Cox proportional hazard model was used to calculate hazard ratios. Sensitivity analyses were performed in various epidemiological settings. Seventeen safety outcomes, including neuropsychiatric, cardiometabolic and gastrointestinal events, were assessed, with upper-respiratory-tract infection as a negative control outcome. RESULTS: A total of 1044, 2078, and 3634 participants were matched for olanzapine vs. risperidone, olanzapine vs. aripiprazole, and risperidone vs. aripiprazole comparisons, respectively. For parkinsonism, there was a significant difference in outcomes between the risperidone and aripiprazole groups (HR 1.80 [95% CI 1.13-2.91]), with consistent sensitivity analysis results. There were no significant differences in other neuropsychiatry outcomes or in the risk of cardiometabolic and gastrointestinal outcomes between any of the comparative group pairs. CONCLUSIONS: The risk of drug-induced parkinsonism was significantly higher with risperidone than with aripiprazole. Although olanzapine is known for its metabolic risk, there were no significant differences in risk between the other pairs.

Scalable Infrastructure Supporting Reproducible Nationwide Healthcare Data Analysis toward FAIR Stewardship.

Transparent and FAIR disclosure of meta-information about healthcare data and infrastructure is essential but has not been well publicized. In this paper, we provide a transparent disclosure of the process of standardizing a common data model and developing a national data infrastructure using national claims data. We established an Observational Medical Outcome Partnership (OMOP) common data model database for national claims data of the Health Insurance Review and Assessment Service of South Korea. To introduce a data openness policy, we built a distributed data analysis environment and released metadata based on the FAIR principle. A total of 10,098,730,241 claims and 56,579,726 patients' data were converted as OMOP common data model. We also built an analytics environment for distributed research and made the metadata publicly available. Disclosure of this infrastructure to researchers will help to eliminate information inequality and contribute to the generation of high-quality medical evidence.