Wonjin Jang
Seoul National University · Medicine
About the Lab
Professor Wonjin Jang's research lab specializes in pediatric critical care and intensive care medicine, focusing on improving outcomes for critically ill children through advanced monitoring technologies and artificial intelligence. The lab investigates early detection of clinical deterioration using physiological data, including heart rate variability and vital signs, to develop predictive models for sedation levels and rapid response systems. A key focus is on applying innovative technologies such as extracorporeal membrane oxygenation (ECMO) in complex pediatric conditions like bronchopulmonary dysplasia and severe toxic exposures. The lab also explores prognostic factors in high-risk pediatric populations, including those undergoing allogeneic hematopoietic stem cell transplantation.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
6Early identification of clinical deterioration in hospitalized children is essential to improve outcomes and prevent critical events. Over the past two decades, structured approaches such as pediatric early warning scores and rapid response systems have provided a framework for systematic risk detection in general wards. More recently, artificial intelligence and continuous monitoring technologies have begun to transform this field, offering the potential for more timely and accurate recognition
Background Allogeneic HSCT may improve survival in pediatric ALL patients who relapse. In this study, we analyzed the outcome and prognostic factors of 62 ALL patients (35 male, 56.5%) who received allogeneic HSCT in second complete remission (CR) at our institution between April 1st 2009 and December 31st 2019. Methods The median time from diagnosis to relapse was 35.1 months (range, 6.0‒113.6 mo). Fifty-three patients (85.5%) experienced bone marrow relapse only. The number of patients who rec
Background:Optimal sedation assessment in critically ill children remains challenging due to the subjective nature of behavioral scales and intermittent evaluation schedules. This study aimed to develop a deep learning model based on heart rate variability (HRV) parameters and vital signs to predict effective and safe sedation levels in pediatric patients.Methods: This retrospective cross-sectional study was conducted in a pediatric intensive care unit at a tertiary children’s hospital. We devel
Background: Various rapid response systems have been developed to detect clinical deterioration in patients. Few studies have evaluated single-parameter systems in children compared to scoring systems. Therefore, in this study we evaluated a single-parameter system called the acute response system (ARS).Methods: This retrospective study was performed at a tertiary children’s hospital. Patients under 18 years old admitted from January 2012 to August 2023 were enrolled. ARS parameters such as syst
Laundry detergent pod (LDP) exposure has been reported to be fatal in children younger than 2 years, leading to respiratory or central nervous system depression. While gastrointestinal irritation is the most common symptom, there are reported cases of severe acidosis with respiratory depression or pneumonia, resulting in mortality. To our best knowledge, there is no report on a case of LDP exposure presenting with acute respiratory distress syndrome requiring extracorporeal membrane oxygenation
Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are potentially fatal complications in prematurely born infants. Extracorporeal membrane oxygenation (ECMO) may be a life-saving option for managing infants with BPD and PH. We present 2 patients who were successfully weaned off mechanical ventilators (MVs) through the application of ECMO. The patients were transferred to our institution after receiving MV care for 8 and 10 months, respectively, for BPD and PH. We were able to remo
Research Areas
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