1.A child with Kawasaki disease and genetic warfarin sensitivity from CYP2C9 and VKORC1 gene variants
Myeongseob LEE ; Lucy Youngmin EUN
Pediatric Emergency Medicine Journal 2020;7(2):140-144
Kawasaki disease (KD) is a common febrile disease in East Asia. Because KD with coronary artery aneurysm (CAA) may predispose to thrombosis, children with KD-associated CAA may need anticoagulation in addition to aspirin. In this report, we describe a 6-year-old girl with KD and CAA who was found to have unexpected warfarin-induced coagulopathy caused by CYP2C9 and VKORC1 genotype variants, which affect warfarin metabolism.
2.A child with Kawasaki disease and genetic warfarin sensitivity from CYP2C9 and VKORC1 gene variants
Myeongseob LEE ; Lucy Youngmin EUN
Pediatric Emergency Medicine Journal 2020;7(2):140-144
Kawasaki disease (KD) is a common febrile disease in East Asia. Because KD with coronary artery aneurysm (CAA) may predispose to thrombosis, children with KD-associated CAA may need anticoagulation in addition to aspirin. In this report, we describe a 6-year-old girl with KD and CAA who was found to have unexpected warfarin-induced coagulopathy caused by CYP2C9 and VKORC1 genotype variants, which affect warfarin metabolism.
3.Changes in the Prevalences of Obesity, Abdominal Obesity, and Non-Alcoholic Fatty Liver Disease among Korean Children during the COVID-19 Outbreak
Kyungchul SONG ; Juyeon YANG ; Hye Sun LEE ; Su Jin KIM ; Myeongseob LEE ; Junghwan SUH ; Ahreum KWON ; Ho-Seong KIM ; Hyun Wook CHAE
Yonsei Medical Journal 2023;64(4):269-277
Purpose:
We aimed to investigate the prevalences of obesity, abdominal obesity, and non-alcoholic fatty liver disease (NAFLD) among children and adolescents during the coronavirus disease 2019 (COVID-19) outbreak.
Materials and Methods:
This population-based study investigated the prevalences of obesity, abdominal obesity, and NAFLD among 1428 children and adolescents between 2018–2019 and 2020. We assessed the prevalences of obesity, abdominal obesity, and NAFLD according to body mass index, age, sex, and residential district. Logistic regression analyses were performed to determine the relationships among obesity, abdominal obesity, and NAFLD.
Results:
In the obese group, the prevalence of abdominal obesity increased from 75.55% to 92.68%, and that of NAFLD increased from 40.68% to 57.82%. In age-specific analysis, the prevalence of abdominal obesity increased from 8.25% to 14.11% among participants aged 10–12 years and from 11.70% to 19.88% among children aged 13–15 years. In residential district-specific analysis, the prevalence of both abdominal obesity and NAFLD increased from 6.96% to 15.74% in rural areas. In logistic regression analysis, the odds ratio of abdominal obesity for NAFLD was 11.82.
Conclusion
Our results demonstrated that the prevalences of abdominal obesity and NAFLD increased among obese Korean children and adolescents and in rural areas during the COVID-19 outbreak. Additionally, the prevalence of abdominal obesity increased among young children. These findings suggest the importance of closely monitoring abdominal obesity and NAFLD among children during COVID-19, focusing particularly on obese young children and individuals in rural areas.
4.Effectiveness and safety of pamidronate treatment in nonambulatory children with low bone mineral density
Myeongseob LEE ; Ahreum KWON ; Kyungchul SONG ; Hae In LEE ; Han Saem CHOI ; Junghwan SUH ; Hyun Wook CHAE ; Ho-Seong KIM
Annals of Pediatric Endocrinology & Metabolism 2024;29(1):46-53
Purpose:
Nonambulatory pediatric patients may have low bone mineral density (BMD) and increased risk of pathologic fractures. Though bisphosphonate therapy is the mainstream medical intervention in these children, clinical data regarding this treatment are limited. Therefore, this study aimed to evaluate the effectiveness and safety of bisphosphonate therapy in such children.
Methods:
We conducted a retrospective study of 21 nonambulatory children (Gross Motor Function Classification System level V) with BMD z-score ≤ -2.0 who were treated with intravenous pamidronate for at least 1 year. These patients received pamidronate every 4 months at a dose of 1.0 to 3.0 mg/kg for each cycle and had regular follow-ups for at least 1 year. The main outcome measures were changes in BMD, risk rate of fracture, biochemical data, and adverse events.
Results:
The average duration of pamidronate treatment was 2.0±0.9 years, and the mean cumulative dose of pamidronate according to body weight was 7.7±2.5 mg/kg/yr. After treatment, the mean lumbar spine bone mineral content, BMD, and height-for-age-z-score-adjusted BMD z-score (BMDhazZ) significantly improved. The relative risk of fracture after treatment was 0.21 (p=0.0032), suggesting that pamidronate treatment reduced fracture incidence significantly. The increase in the average dose per body weight in each cycle significantly increased the changes in BMDhazZ.
Conclusion
Pamidronate treatment improved the bone health of nonambulatory children with low bone density without any significant adverse events. Independent of cumulative dosage and duration of treatment, the effectiveness of pamidronate increased significantly with an increase in the average dose per body weight in subsequent cycles.
5.Long-term tracking of glycosylated hemoglobin levels across the lifespan in type 1 diabetes: from infants to young adults
Sujin KIM ; Seo Jung KIM ; Kyoung Won CHO ; Kyungchul SONG ; Myeongseob LEE ; Junghwan SUH ; Hyun Wook CHAE ; Ho-Seong KIM ; Ahreum KWON
Annals of Pediatric Endocrinology & Metabolism 2024;29(4):242-249
Purpose:
Glycosylated hemoglobin (HbA1c) is commonly used as a monitoring tool in diabetes. Due to the potential influence of insulin resistance (IR), HbA1c level may fluctuate over a person's lifetime. This study explores the long-term tracking of HbA1c level in individuals diagnosed with type 1 diabetes mellitus (T1DM) from infancy to early adulthood.
Methods:
The HbA1c levels in 275 individuals (121 males, 43.8%) diagnosed with T1DM were tracked for an average of 9.4 years. The distribution of HbA1c levels was evaluated according to age with subgroups divided by gender, use of continuous glucose monitoring (CGM), and the presence of complications.
Results:
HbA1c levels were highest at the age of 1 year and then declined until age 4, followed by a significant increase, reaching a maximum at ages 15–16 years. The levels subsequently gradually decreased until early adulthood. This pattern was observed in both sexes, but it was more pronounced in females. Additionally, HbA1c levels were higher in CGM nonusers compared with CGM users; however, regardless of CGM usage, an age-dependent pattern was observed. Furthermore, diabetic complications occurred in 26.8% of individuals, and the age-dependent pattern was observed irrespective of diabetic complications, although HbA1c levels were higher in individuals with diabetic complications.
Conclusion
HbA1c levels vary throughout the lifespan, with higher levels during adolescence. This trend is observed regardless of sex and CGM usage, potentially due to physiological IR observed during adolescence. Hence, physiological IR should be considered when interpretating HbA1c levels during adolescence.
6.Long-term tracking of glycosylated hemoglobin levels across the lifespan in type 1 diabetes: from infants to young adults
Sujin KIM ; Seo Jung KIM ; Kyoung Won CHO ; Kyungchul SONG ; Myeongseob LEE ; Junghwan SUH ; Hyun Wook CHAE ; Ho-Seong KIM ; Ahreum KWON
Annals of Pediatric Endocrinology & Metabolism 2024;29(4):242-249
Purpose:
Glycosylated hemoglobin (HbA1c) is commonly used as a monitoring tool in diabetes. Due to the potential influence of insulin resistance (IR), HbA1c level may fluctuate over a person's lifetime. This study explores the long-term tracking of HbA1c level in individuals diagnosed with type 1 diabetes mellitus (T1DM) from infancy to early adulthood.
Methods:
The HbA1c levels in 275 individuals (121 males, 43.8%) diagnosed with T1DM were tracked for an average of 9.4 years. The distribution of HbA1c levels was evaluated according to age with subgroups divided by gender, use of continuous glucose monitoring (CGM), and the presence of complications.
Results:
HbA1c levels were highest at the age of 1 year and then declined until age 4, followed by a significant increase, reaching a maximum at ages 15–16 years. The levels subsequently gradually decreased until early adulthood. This pattern was observed in both sexes, but it was more pronounced in females. Additionally, HbA1c levels were higher in CGM nonusers compared with CGM users; however, regardless of CGM usage, an age-dependent pattern was observed. Furthermore, diabetic complications occurred in 26.8% of individuals, and the age-dependent pattern was observed irrespective of diabetic complications, although HbA1c levels were higher in individuals with diabetic complications.
Conclusion
HbA1c levels vary throughout the lifespan, with higher levels during adolescence. This trend is observed regardless of sex and CGM usage, potentially due to physiological IR observed during adolescence. Hence, physiological IR should be considered when interpretating HbA1c levels during adolescence.
7.Long-term tracking of glycosylated hemoglobin levels across the lifespan in type 1 diabetes: from infants to young adults
Sujin KIM ; Seo Jung KIM ; Kyoung Won CHO ; Kyungchul SONG ; Myeongseob LEE ; Junghwan SUH ; Hyun Wook CHAE ; Ho-Seong KIM ; Ahreum KWON
Annals of Pediatric Endocrinology & Metabolism 2024;29(4):242-249
Purpose:
Glycosylated hemoglobin (HbA1c) is commonly used as a monitoring tool in diabetes. Due to the potential influence of insulin resistance (IR), HbA1c level may fluctuate over a person's lifetime. This study explores the long-term tracking of HbA1c level in individuals diagnosed with type 1 diabetes mellitus (T1DM) from infancy to early adulthood.
Methods:
The HbA1c levels in 275 individuals (121 males, 43.8%) diagnosed with T1DM were tracked for an average of 9.4 years. The distribution of HbA1c levels was evaluated according to age with subgroups divided by gender, use of continuous glucose monitoring (CGM), and the presence of complications.
Results:
HbA1c levels were highest at the age of 1 year and then declined until age 4, followed by a significant increase, reaching a maximum at ages 15–16 years. The levels subsequently gradually decreased until early adulthood. This pattern was observed in both sexes, but it was more pronounced in females. Additionally, HbA1c levels were higher in CGM nonusers compared with CGM users; however, regardless of CGM usage, an age-dependent pattern was observed. Furthermore, diabetic complications occurred in 26.8% of individuals, and the age-dependent pattern was observed irrespective of diabetic complications, although HbA1c levels were higher in individuals with diabetic complications.
Conclusion
HbA1c levels vary throughout the lifespan, with higher levels during adolescence. This trend is observed regardless of sex and CGM usage, potentially due to physiological IR observed during adolescence. Hence, physiological IR should be considered when interpretating HbA1c levels during adolescence.
8.Long-term tracking of glycosylated hemoglobin levels across the lifespan in type 1 diabetes: from infants to young adults
Sujin KIM ; Seo Jung KIM ; Kyoung Won CHO ; Kyungchul SONG ; Myeongseob LEE ; Junghwan SUH ; Hyun Wook CHAE ; Ho-Seong KIM ; Ahreum KWON
Annals of Pediatric Endocrinology & Metabolism 2024;29(4):242-249
Purpose:
Glycosylated hemoglobin (HbA1c) is commonly used as a monitoring tool in diabetes. Due to the potential influence of insulin resistance (IR), HbA1c level may fluctuate over a person's lifetime. This study explores the long-term tracking of HbA1c level in individuals diagnosed with type 1 diabetes mellitus (T1DM) from infancy to early adulthood.
Methods:
The HbA1c levels in 275 individuals (121 males, 43.8%) diagnosed with T1DM were tracked for an average of 9.4 years. The distribution of HbA1c levels was evaluated according to age with subgroups divided by gender, use of continuous glucose monitoring (CGM), and the presence of complications.
Results:
HbA1c levels were highest at the age of 1 year and then declined until age 4, followed by a significant increase, reaching a maximum at ages 15–16 years. The levels subsequently gradually decreased until early adulthood. This pattern was observed in both sexes, but it was more pronounced in females. Additionally, HbA1c levels were higher in CGM nonusers compared with CGM users; however, regardless of CGM usage, an age-dependent pattern was observed. Furthermore, diabetic complications occurred in 26.8% of individuals, and the age-dependent pattern was observed irrespective of diabetic complications, although HbA1c levels were higher in individuals with diabetic complications.
Conclusion
HbA1c levels vary throughout the lifespan, with higher levels during adolescence. This trend is observed regardless of sex and CGM usage, potentially due to physiological IR observed during adolescence. Hence, physiological IR should be considered when interpretating HbA1c levels during adolescence.
9.Bone Age Estimation and Prediction of Final Adult Height Using Deep Learning
Junghwan SUH ; Jinkyoung HEO ; Su Jin KIM ; Soyeong PARK ; Mo Kyung JUNG ; Han Saem CHOI ; Youngha CHOI ; Jun Suk OH ; Hae In LEE ; Myeongseob LEE ; Kyungchul SONG ; Ahreum KWON ; Hyun Wook CHAE ; Ho-Seong KIM
Yonsei Medical Journal 2023;64(11):679-686
Purpose:
The appropriate evaluation of height and accurate estimation of bone age are crucial for proper assessment of the growth status of a child. We developed a bone age estimation program using a deep learning algorithm and established a model to predict the final adult height of Korean children.
Materials and Methods:
A total of 1678 radiographs from 866 children, for which the interpretation results were consistent between two pediatric endocrinologists, were used to train and validate the deep learning model. The bone age estimation algorithm was based on the convolutional neural network of the deep learning system. The test set simulation was performed by a deep learning program and two raters using 150 radiographs and final height data for 100 adults.
Results:
There was a statistically significant correlation between bone age interpreted by the artificial intelligence (AI) program and the reference bone age in the test set simulation (r=0.99, p<0.001). In the test set simulation, the AI program showed a mean absolute error (MAE) of 0.59 years and a root mean squared error (RMSE) of 0.55 years, compared with reference bone age, and showed similar accuracy to that of an experienced pediatric endocrinologist (rater 1). Prediction of final adult height by the AI program showed an MAE of 4.62 cm, compared with the actual final adult height.
Conclusion
We developed a bone age estimation program based on a deep learning algorithm. The AI-derived program demonstrated high accuracy in estimating bone age and predicting the final adult height of Korean children and adolescents.
10.Psychosocial factors affecting sleep quality of pre-employed firefighters:a cross-sectional study
MyeongSeob LIM ; Solam LEE ; Kwanghyun SEO ; Hyun-Jeong OH ; Ji-Su SHIN ; Sung-Kyung KIM ; Hee-Tae KANG ; Kyeong-Sook JEONG ; Sung-Soo OH ; Sang-Baek KOH ; Yeon-Soon AHN
Annals of Occupational and Environmental Medicine 2020;32(1):e12-
Background:
There have been no health-related studies of pre-employed firefighters without firefighter-specific job-related factors (FSJRF). This study aimed to evaluate the sleep quality of pre-employed firefighters and to examine the relationship between sleep quality and psychosocial factors.
Methods:
We conducted a self-report questionnaire survey for 602 pre-employed firefighters at 3 Fire Service Academies after brief lecture about sleep. Sleep quality and psychosocial variables such as depression, anxiety, stress and social support were evaluated. The independent 2 sample t-test, χ2 test and multiple logistic regression analysis were used to evaluate the effect of the variables on the sleep quality of pre-employed firefighters.
Results:
Among a total of 602 people, 347 (57.6%) had good sleep quality and 255 (42.4%) had poor sleep quality. Pittsburgh Sleep Quality Index score of them was 3.29 ± 1.41) and 7.87 ± 2.20), respectively. 24 (4.0%) were evaluated to have insomnia by Insomnia Severity Index.Logistic regression analyses showed that the depression (adjusted odds ratio [aOR]: 5.940, 95% confidence interval [CI]: 3.124–11.292), anxiety (aOR: 4.233, 95% CI: 2.138–8.381), stress (aOR: 2.880, 95% CI: 1.915–4.330) and social support (aOR: 0.959, 95% CI: 0.939–0.980) have a significant effect on sleep quality after adjusted by sex, age, smoking status, drinking status, caffeine intake, past shift working and circadian rhythm type.
Conclusions
Depression, anxiety, stress and social support were associated with sleep quality among pre-employed firefighters. Repeated follow-up studies of pre-employed firefighters are needed to further assess their change of sleep quality and identify the FSJRF that may affect the sleep quality of firefighters.