1.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
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
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.Effectiveness of intravenous thrombolysis in patients with large-vessel occlusion receiving endovascular treatment in South Korea
Min KIM ; Ji Sung LEE ; Seong-Joon LEE ; So Young PARK ; Jungyun SEO ; Ji Man HONG ; Hee-Kwon PARK ; Jae-Kwan CHA ; Jeffrey L. SAVER ; Jin Soo LEE
Acute and Critical Care 2025;40(2):282-292
Background:
The effectiveness of intravenous tissue plasminogen activator (IV tPA) in patients with large-vessel occlusion (LVO) receiving endovascular treatment (EVT) for acute ischemic stroke (AIS) has been questioned. We investigated IV tPA effectiveness in real-world AIS patients, including those with intracranial LVO receiving EVT.
Methods:
We identified patients with AIS who presented to hospital with National Institutes of Health Stroke Scale ≥4 within 8 hours of symptom onset from the institutional stroke registry. The association of IV tPA use with effectiveness and safety outcomes was analyzed in overall enrolled AIS patients; LVO patients; and patients treated with EVT. The effect of IV tPA was assessed using multiple logistic regression.
Results:
Among the 654 patients meeting study entry criteria, 238 (36.4%) received IV tPA and 416 (63.6%) did not. Multiple logistic regression analysis and shift analysis revealed IV tPA was associated with improved outcomes in overall enrolled AIS population, LVO, and EVT-treated subgroups. Among EVT-treated patients, IV tPA was associated with higher likelihood of ambulatory or better outcome (modified Rankin Scale 0–3) with odds ratio of 1.95 (P=0.03).
Conclusions
In this real-world study, IV tPA use was associated with improved outcomes for patients with AIS, including among LVO patients treated and not treated with EVT, in the contemporary mechanical thrombectomy era.
8.Risk of Lymphedema After Sentinel Node Biopsy in Patients With Breast Cancer
Jinyoung BYEON ; Eunhye KANG ; Ji-Jung JUNG ; Jong-Ho CHEUN ; Kwan Sik SEO ; Hong-Kyu KIM ; Han-Byoel LEE ; Wonshik HAN ; Hyeong-Gon MOON
Journal of Breast Cancer 2024;27(5):323-333
Purpose:
Although numerous studies have identified potential risk factors for ipsilateral lymphedema development in patients with breast cancer following axillary node dissection, the risk factors for lymphedema in patients undergoing sentinel node biopsy without axillary dissection remain unclear. In this study, we aimed to determine the real-world incidence and risk factors for lymphedema in such patients.
Methods:
We conducted a single-center, retrospective review of medical records of patients with breast cancer who underwent sentinel node biopsy alone. The development cohort (5,051 patients, January 2017–December 2020) was analyzed to identify predictors of lymphedema, and a predictive model was subsequently created. A validation cohort (1,627 patients, January 2014–December 2016) was used to validate the model.
Results:
In the development cohort, 49 patients (0.9%) developed lymphedema over a median follow-up of 56 months, with most cases occurring within the first three years post-operation.Multivariate analysis revealed that a body mass index (BMI) of 30 kg/m2 or above, radiation therapy (RTx), chemotherapy, and more than three harvested lymph nodes significantly predicted lymphedema. The predictive model showed an area under the curve of 0.824 for systemic chemotherapy, with the number of harvested lymph nodes being the most significant factor. Patients were stratified into four risk groups, showing lymphedema incidences of 3.3% in the highest-risk group and 0.1% in the lowest-risk group. In the validation cohort, the incidences were 1.7% and 0.2% for the highest and lowest risk groups, respectively.
Conclusion
The lymphedema prediction model identifies RTx, chemotherapy, BMI ≥ 30 kg/m2 , and more than three harvested lymph nodes as significant risk factors. Although the overall incidence is low, the risk is notably influenced by the extent of lymph node removal and systemic therapies. The model’s high negative predictive value supports its application in designing tailored lymphedema surveillance programs for early intervention.
9.Risk of Lymphedema After Sentinel Node Biopsy in Patients With Breast Cancer
Jinyoung BYEON ; Eunhye KANG ; Ji-Jung JUNG ; Jong-Ho CHEUN ; Kwan Sik SEO ; Hong-Kyu KIM ; Han-Byoel LEE ; Wonshik HAN ; Hyeong-Gon MOON
Journal of Breast Cancer 2024;27(5):323-333
Purpose:
Although numerous studies have identified potential risk factors for ipsilateral lymphedema development in patients with breast cancer following axillary node dissection, the risk factors for lymphedema in patients undergoing sentinel node biopsy without axillary dissection remain unclear. In this study, we aimed to determine the real-world incidence and risk factors for lymphedema in such patients.
Methods:
We conducted a single-center, retrospective review of medical records of patients with breast cancer who underwent sentinel node biopsy alone. The development cohort (5,051 patients, January 2017–December 2020) was analyzed to identify predictors of lymphedema, and a predictive model was subsequently created. A validation cohort (1,627 patients, January 2014–December 2016) was used to validate the model.
Results:
In the development cohort, 49 patients (0.9%) developed lymphedema over a median follow-up of 56 months, with most cases occurring within the first three years post-operation.Multivariate analysis revealed that a body mass index (BMI) of 30 kg/m2 or above, radiation therapy (RTx), chemotherapy, and more than three harvested lymph nodes significantly predicted lymphedema. The predictive model showed an area under the curve of 0.824 for systemic chemotherapy, with the number of harvested lymph nodes being the most significant factor. Patients were stratified into four risk groups, showing lymphedema incidences of 3.3% in the highest-risk group and 0.1% in the lowest-risk group. In the validation cohort, the incidences were 1.7% and 0.2% for the highest and lowest risk groups, respectively.
Conclusion
The lymphedema prediction model identifies RTx, chemotherapy, BMI ≥ 30 kg/m2 , and more than three harvested lymph nodes as significant risk factors. Although the overall incidence is low, the risk is notably influenced by the extent of lymph node removal and systemic therapies. The model’s high negative predictive value supports its application in designing tailored lymphedema surveillance programs for early intervention.
10.Risk of Lymphedema After Sentinel Node Biopsy in Patients With Breast Cancer
Jinyoung BYEON ; Eunhye KANG ; Ji-Jung JUNG ; Jong-Ho CHEUN ; Kwan Sik SEO ; Hong-Kyu KIM ; Han-Byoel LEE ; Wonshik HAN ; Hyeong-Gon MOON
Journal of Breast Cancer 2024;27(5):323-333
Purpose:
Although numerous studies have identified potential risk factors for ipsilateral lymphedema development in patients with breast cancer following axillary node dissection, the risk factors for lymphedema in patients undergoing sentinel node biopsy without axillary dissection remain unclear. In this study, we aimed to determine the real-world incidence and risk factors for lymphedema in such patients.
Methods:
We conducted a single-center, retrospective review of medical records of patients with breast cancer who underwent sentinel node biopsy alone. The development cohort (5,051 patients, January 2017–December 2020) was analyzed to identify predictors of lymphedema, and a predictive model was subsequently created. A validation cohort (1,627 patients, January 2014–December 2016) was used to validate the model.
Results:
In the development cohort, 49 patients (0.9%) developed lymphedema over a median follow-up of 56 months, with most cases occurring within the first three years post-operation.Multivariate analysis revealed that a body mass index (BMI) of 30 kg/m2 or above, radiation therapy (RTx), chemotherapy, and more than three harvested lymph nodes significantly predicted lymphedema. The predictive model showed an area under the curve of 0.824 for systemic chemotherapy, with the number of harvested lymph nodes being the most significant factor. Patients were stratified into four risk groups, showing lymphedema incidences of 3.3% in the highest-risk group and 0.1% in the lowest-risk group. In the validation cohort, the incidences were 1.7% and 0.2% for the highest and lowest risk groups, respectively.
Conclusion
The lymphedema prediction model identifies RTx, chemotherapy, BMI ≥ 30 kg/m2 , and more than three harvested lymph nodes as significant risk factors. Although the overall incidence is low, the risk is notably influenced by the extent of lymph node removal and systemic therapies. The model’s high negative predictive value supports its application in designing tailored lymphedema surveillance programs for early intervention.

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