1.Long-Term Incidence of Gastrointestinal Bleeding Following Ischemic Stroke
Jun Yup KIM ; Beom Joon KIM ; Jihoon KANG ; Do Yeon KIM ; Moon-Ku HAN ; Seong-Eun KIM ; Heeyoung LEE ; Jong-Moo PARK ; Kyusik KANG ; Soo Joo LEE ; Jae Guk KIM ; Jae-Kwan CHA ; Dae-Hyun KIM ; Tai Hwan PARK ; Kyungbok LEE ; Hong-Kyun PARK ; Yong-Jin CHO ; Keun-Sik HONG ; Kang-Ho CHOI ; Joon-Tae KIM ; Dong-Eog KIM ; Jay Chol CHOI ; Mi-Sun OH ; Kyung-Ho YU ; Byung-Chul LEE ; Kwang-Yeol PARK ; Ji Sung LEE ; Sujung JANG ; Jae Eun CHAE ; Juneyoung LEE ; Min-Surk KYE ; Philip B. GORELICK ; Hee-Joon BAE ;
Journal of Stroke 2025;27(1):102-112
Background:
and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes.
Methods:
We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data.
Results:
Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4.
Conclusion
Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.
2.Early Administration of Nelonemdaz May Improve the Stroke Outcomes in Patients With Acute Stroke
Jin Soo LEE ; Ji Sung LEE ; Seong Hwan AHN ; Hyun Goo KANG ; Tae-Jin SONG ; Dong-Ick SHIN ; Hee-Joon BAE ; Chang Hun KIM ; Sung Hyuk HEO ; Jae-Kwan CHA ; Yeong Bae LEE ; Eung Gyu KIM ; Man Seok PARK ; Hee-Kwon PARK ; Jinkwon KIM ; Sungwook YU ; Heejung MO ; Sung Il SOHN ; Jee Hyun KWON ; Jae Guk KIM ; Young Seo KIM ; Jay Chol CHOI ; Yang-Ha HWANG ; Keun Hwa JUNG ; Soo-Kyoung KIM ; Woo Keun SEO ; Jung Hwa SEO ; Joonsang YOO ; Jun Young CHANG ; Mooseok PARK ; Kyu Sun YUM ; Chun San AN ; Byoung Joo GWAG ; Dennis W. CHOI ; Ji Man HONG ; Sun U. KWON ;
Journal of Stroke 2025;27(2):279-283
3.Long-Term Incidence of Gastrointestinal Bleeding Following Ischemic Stroke
Jun Yup KIM ; Beom Joon KIM ; Jihoon KANG ; Do Yeon KIM ; Moon-Ku HAN ; Seong-Eun KIM ; Heeyoung LEE ; Jong-Moo PARK ; Kyusik KANG ; Soo Joo LEE ; Jae Guk KIM ; Jae-Kwan CHA ; Dae-Hyun KIM ; Tai Hwan PARK ; Kyungbok LEE ; Hong-Kyun PARK ; Yong-Jin CHO ; Keun-Sik HONG ; Kang-Ho CHOI ; Joon-Tae KIM ; Dong-Eog KIM ; Jay Chol CHOI ; Mi-Sun OH ; Kyung-Ho YU ; Byung-Chul LEE ; Kwang-Yeol PARK ; Ji Sung LEE ; Sujung JANG ; Jae Eun CHAE ; Juneyoung LEE ; Min-Surk KYE ; Philip B. GORELICK ; Hee-Joon BAE ;
Journal of Stroke 2025;27(1):102-112
Background:
and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes.
Methods:
We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data.
Results:
Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4.
Conclusion
Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.
4.Early Administration of Nelonemdaz May Improve the Stroke Outcomes in Patients With Acute Stroke
Jin Soo LEE ; Ji Sung LEE ; Seong Hwan AHN ; Hyun Goo KANG ; Tae-Jin SONG ; Dong-Ick SHIN ; Hee-Joon BAE ; Chang Hun KIM ; Sung Hyuk HEO ; Jae-Kwan CHA ; Yeong Bae LEE ; Eung Gyu KIM ; Man Seok PARK ; Hee-Kwon PARK ; Jinkwon KIM ; Sungwook YU ; Heejung MO ; Sung Il SOHN ; Jee Hyun KWON ; Jae Guk KIM ; Young Seo KIM ; Jay Chol CHOI ; Yang-Ha HWANG ; Keun Hwa JUNG ; Soo-Kyoung KIM ; Woo Keun SEO ; Jung Hwa SEO ; Joonsang YOO ; Jun Young CHANG ; Mooseok PARK ; Kyu Sun YUM ; Chun San AN ; Byoung Joo GWAG ; Dennis W. CHOI ; Ji Man HONG ; Sun U. KWON ;
Journal of Stroke 2025;27(2):279-283
5.Long-Term Incidence of Gastrointestinal Bleeding Following Ischemic Stroke
Jun Yup KIM ; Beom Joon KIM ; Jihoon KANG ; Do Yeon KIM ; Moon-Ku HAN ; Seong-Eun KIM ; Heeyoung LEE ; Jong-Moo PARK ; Kyusik KANG ; Soo Joo LEE ; Jae Guk KIM ; Jae-Kwan CHA ; Dae-Hyun KIM ; Tai Hwan PARK ; Kyungbok LEE ; Hong-Kyun PARK ; Yong-Jin CHO ; Keun-Sik HONG ; Kang-Ho CHOI ; Joon-Tae KIM ; Dong-Eog KIM ; Jay Chol CHOI ; Mi-Sun OH ; Kyung-Ho YU ; Byung-Chul LEE ; Kwang-Yeol PARK ; Ji Sung LEE ; Sujung JANG ; Jae Eun CHAE ; Juneyoung LEE ; Min-Surk KYE ; Philip B. GORELICK ; Hee-Joon BAE ;
Journal of Stroke 2025;27(1):102-112
Background:
and Purpose Previous research on patients with acute ischemic stroke (AIS) has shown a 0.5% incidence of major gastrointestinal bleeding (GIB) requiring blood transfusion during hospitalization. The existing literature has insufficiently explored the long-term incidence in this population despite the decremental impact of GIB on stroke outcomes.
Methods:
We analyzed the data from a cohort of patients with AIS admitted to 14 hospitals as part of a nationwide multicenter prospective stroke registry between 2011 and 2013. These patients were followed up for up to 6 years. The occurrence of major GIB events, defined as GIB necessitating at least two units of blood transfusion, was tracked using the National Health Insurance Service claims data.
Results:
Among 10,818 patients with AIS (male, 59%; mean age, 68±13 years), 947 (8.8%) experienced 1,224 episodes of major GIB over a median follow-up duration of 3.1 years. Remarkably, 20% of 947 patients experienced multiple episodes of major GIB. The incidence peaked in the first month after AIS, reaching 19.2 per 100 person-years, and gradually decreased to approximately one-sixth of this rate by the 2nd year with subsequent stabilization. Multivariable analysis identified the following predictors of major GIB: anemia, estimated glomerular filtration rate <60 mL/min/1.73 m2 , and a 3-month modified Rankin Scale score of ≥4.
Conclusion
Patients with AIS are susceptible to major GIB, particularly in the first month after the onset of AIS, with the risk decreasing thereafter. Implementing preventive strategies may be important, especially for patients with anemia and impaired renal function at stroke onset and those with a disabling stroke.
6.Early Administration of Nelonemdaz May Improve the Stroke Outcomes in Patients With Acute Stroke
Jin Soo LEE ; Ji Sung LEE ; Seong Hwan AHN ; Hyun Goo KANG ; Tae-Jin SONG ; Dong-Ick SHIN ; Hee-Joon BAE ; Chang Hun KIM ; Sung Hyuk HEO ; Jae-Kwan CHA ; Yeong Bae LEE ; Eung Gyu KIM ; Man Seok PARK ; Hee-Kwon PARK ; Jinkwon KIM ; Sungwook YU ; Heejung MO ; Sung Il SOHN ; Jee Hyun KWON ; Jae Guk KIM ; Young Seo KIM ; Jay Chol CHOI ; Yang-Ha HWANG ; Keun Hwa JUNG ; Soo-Kyoung KIM ; Woo Keun SEO ; Jung Hwa SEO ; Joonsang YOO ; Jun Young CHANG ; Mooseok PARK ; Kyu Sun YUM ; Chun San AN ; Byoung Joo GWAG ; Dennis W. CHOI ; Ji Man HONG ; Sun U. KWON ;
Journal of Stroke 2025;27(2):279-283
7.Efficacy and Safety of Metformin and Atorvastatin Combination Therapy vs. Monotherapy with Either Drug in Type 2 Diabetes Mellitus and Dyslipidemia Patients (ATOMIC): Double-Blinded Randomized Controlled Trial
Jie-Eun LEE ; Seung Hee YU ; Sung Rae KIM ; Kyu Jeung AHN ; Kee-Ho SONG ; In-Kyu LEE ; Ho-Sang SHON ; In Joo KIM ; Soo LIM ; Doo-Man KIM ; Choon Hee CHUNG ; Won-Young LEE ; Soon Hee LEE ; Dong Joon KIM ; Sung-Rae CHO ; Chang Hee JUNG ; Hyun Jeong JEON ; Seung-Hwan LEE ; Keun-Young PARK ; Sang Youl RHEE ; Sin Gon KIM ; Seok O PARK ; Dae Jung KIM ; Byung Joon KIM ; Sang Ah LEE ; Yong-Hyun KIM ; Kyung-Soo KIM ; Ji A SEO ; Il Seong NAM-GOONG ; Chang Won LEE ; Duk Kyu KIM ; Sang Wook KIM ; Chung Gu CHO ; Jung Han KIM ; Yeo-Joo KIM ; Jae-Myung YOO ; Kyung Wan MIN ; Moon-Kyu LEE
Diabetes & Metabolism Journal 2024;48(4):730-739
Background:
It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia.
Methods:
This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment.
Results:
After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events.
Conclusion
The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.
8.Study Design and Protocol for a Randomized Controlled Trial to Assess Long-Term Efficacy and Safety of a Triple Combination of Ezetimibe, Fenofibrate, and Moderate-Intensity Statin in Patients with Type 2 Diabetes and Modifiable Cardiovascular Risk Factors (ENSEMBLE)
Nam Hoon KIM ; Juneyoung LEE ; Suk CHON ; Jae Myung YU ; In-Kyung JEONG ; Soo LIM ; Won Jun KIM ; Keeho SONG ; Ho Chan CHO ; Hea Min YU ; Kyoung-Ah KIM ; Sang Soo KIM ; Soon Hee LEE ; Chong Hwa KIM ; Soo Heon KWAK ; Yong‐ho LEE ; Choon Hee CHUNG ; Sihoon LEE ; Heung Yong JIN ; Jae Hyuk LEE ; Gwanpyo KOH ; Sang-Yong KIM ; Jaetaek KIM ; Ju Hee LEE ; Tae Nyun KIM ; Hyun Jeong JEON ; Ji Hyun LEE ; Jae-Han JEON ; Hye Jin YOO ; Hee Kyung KIM ; Hyeong-Kyu PARK ; Il Seong NAM-GOONG ; Seongbin HONG ; Chul Woo AHN ; Ji Hee YU ; Jong Heon PARK ; Keun-Gyu PARK ; Chan Ho PARK ; Kyong Hye JOUNG ; Ohk-Hyun RYU ; Keun Yong PARK ; Eun-Gyoung HONG ; Bong-Soo CHA ; Kyu Chang WON ; Yoon-Sok CHUNG ; Sin Gon KIM
Endocrinology and Metabolism 2024;39(5):722-731
Background:
Atherogenic dyslipidemia, which is frequently associated with type 2 diabetes (T2D) and insulin resistance, contributes to the development of vascular complications. Statin therapy is the primary approach to dyslipidemia management in T2D, however, the role of non-statin therapy remains unclear. Ezetimibe reduces cholesterol burden by inhibiting intestinal cholesterol absorption. Fibrates lower triglyceride levels and increase high-density lipoprotein cholesterol (HDL-C) levels via peroxisome proliferator- activated receptor alpha agonism. Therefore, when combined, these drugs effectively lower non-HDL-C levels. Despite this, few clinical trials have specifically targeted non-HDL-C, and the efficacy of triple combination therapies, including statins, ezetimibe, and fibrates, has yet to be determined.
Methods:
This is a multicenter, prospective, randomized, open-label, active-comparator controlled trial involving 3,958 eligible participants with T2D, cardiovascular risk factors, and elevated non-HDL-C (≥100 mg/dL). Participants, already on moderate-intensity statins, will be randomly assigned to either Ezefeno (ezetimibe/fenofibrate) addition or statin dose-escalation. The primary end point is the development of a composite of major adverse cardiovascular and diabetic microvascular events over 48 months.
Conclusion
This trial aims to assess whether combining statins, ezetimibe, and fenofibrate is as effective as, or possibly superior to, statin monotherapy intensification in lowering cardiovascular and microvascular disease risk for patients with T2D. This could propose a novel therapeutic approach for managing dyslipidemia in T2D.
9.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
10.Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys
Tae-Yeon KIM ; Seong-Uk BAEK ; Myeong-Hun LIM ; Byungyoon YUN ; Domyung PAEK ; Kyung Ehi ZOH ; Kanwoo YOUN ; Yun Keun LEE ; Yangho KIM ; Jungwon KIM ; Eunsuk CHOI ; Mo-Yeol KANG ; YoonHo CHO ; Kyung-Eun LEE ; Juho SIM ; Juyeon OH ; Heejoo PARK ; Jian LEE ; Jong-Uk WON ; Yu-Min LEE ; Jin-Ha YOON
Annals of Occupational and Environmental Medicine 2024;36(1):e19-
Accurate occupation classification is essential in various fields, including policy development and epidemiological studies. This study aims to develop an occupation classification model based on DistilKoBERT. This study used data from the 5th and 6th Korean Working Conditions Surveys conducted in 2017 and 2020, respectively. A total of 99,665 survey participants, who were nationally representative of Korean workers, were included. We used natural language responses regarding their job responsibilities and occupational codes based on the Korean Standard Classification of Occupations (7th version, 3-digit codes). The dataset was randomly split into training and test datasets in a ratio of 7:3. The occupation classification model based on DistilKoBERT was fine-tuned using the training dataset, and the model was evaluated using the test dataset. The accuracy, precision, recall, and F1 score were calculated as evaluation metrics. The final model, which classified 28,996 survey participants in the test dataset into 142 occupational codes, exhibited an accuracy of 84.44%. For the evaluation metrics, the precision, recall, and F1 score of the model, calculated by weighting based on the sample size, were 0.83, 0.84, and 0.83, respectively. The model demonstrated high precision in the classification of service and sales workers yet exhibited low precision in the classification of managers. In addition, it displayed high precision in classifying occupations prominently represented in the training dataset. This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.

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