1.Hyperbaric Oxygen Therapy for the Treatment of Chronic Prostatitis/Chronic Pelvic Pain Syndrome: Case Report
Kwang Jin KIM ; Yoonsuk LEE ; Yong Sung CHA ; Tae Wook KANG ; Hyun Chul CHUNG ; Hong CHUNG ; Hyun KIM ; Jae Hung JUNG
Urogenital Tract Infection 2024;19(2):44-47
Hyperbaric oxygen therapy (HBOT) was conducted on two male patients with chronic prostatitis/chronic pelvic pain syndrome who were resistant to conventional medical therapies. Both patients underwent 20 sessions of 100% oxygen inhalation (2.0 atmosphere absolute for 90 min/day, five days/week for four weeks) in a hyperbaric chamber. The follow-up period was three months. Although the patients reported a slight improvement in the pain domain of the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) after HBOT, no changes were noted in the other domains of NIH-CPSI and International Prostate Symptom Score. No adverse events were encountered during or after HBOT.
2.Effect of Furosemide on Prevertebral Soft Tissue Swelling after Anterior Cervical Fusion: A Comparative Study with Dexamethasone
Ju-Sung JANG ; Young-Seok LEE ; Myeong Jin KO ; Seong Hyun WUI ; Kwang-Sup SONG ; Seung Won PARK
Asian Spine Journal 2024;18(1):66-72
Methods:
The symptomatic PSTS group received intravenous (IV) administration of dexamethasone or furosemide. The asymptomatic PSTS group did not receive any medication. Patients were divided into the control (no medication, n=31), Dexa (IV dexamethasone, n=25), and Furo (IV furosemide, n=28) groups. PSTS was checked daily with simple radiographs and medication-induced reductions in PSTS from its peak or after medication.
Results:
The peak time (postoperative days) of PSTS in the control (2.27±0.47, p<0.05) and Dexa (1.91±0.54, p<0.01) groups were significantly later than that in the Furo group (1.38±0.74). PSTS was significantly lower in the Furo group than in the Dexa group from postoperative days 4 to 7 (p<0.05). PSTS reduction after the peak was significantly greater in the Furo group than in the control (p<0.01) and Dexa (p<0.01) groups. After starting the medication therapy, the Furo group showed a significantly greater reduction in PSTS than the Dexa group (p<0.01). No difference was found in symptom improvement among the three groups.
Conclusions
If furosemide is used to reduce PSTS after ACF, it can effectively reduce symptoms.
3.Hyperbaric Oxygen Therapy for the Treatment of Chronic Prostatitis/Chronic Pelvic Pain Syndrome: Case Report
Kwang Jin KIM ; Yoonsuk LEE ; Yong Sung CHA ; Tae Wook KANG ; Hyun Chul CHUNG ; Hong CHUNG ; Hyun KIM ; Jae Hung JUNG
Urogenital Tract Infection 2024;19(2):44-47
Hyperbaric oxygen therapy (HBOT) was conducted on two male patients with chronic prostatitis/chronic pelvic pain syndrome who were resistant to conventional medical therapies. Both patients underwent 20 sessions of 100% oxygen inhalation (2.0 atmosphere absolute for 90 min/day, five days/week for four weeks) in a hyperbaric chamber. The follow-up period was three months. Although the patients reported a slight improvement in the pain domain of the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) after HBOT, no changes were noted in the other domains of NIH-CPSI and International Prostate Symptom Score. No adverse events were encountered during or after HBOT.
4.Clinical Trial Protocol for Porcine Islet Xenotransplantation in South Korea
Byung-Joon KIM ; Jun-Seop SHIN ; Byoung-Hoon MIN ; Jong-Min KIM ; Chung-Gyu PARK ; Hee-Jung KANG ; Eung Soo HWANG ; Won-Woo LEE ; Jung-Sik KIM ; Hyun Je KIM ; Iov KWON ; Jae Sung KIM ; Geun Soo KIM ; Joonho MOON ; Du Yeon SHIN ; Bumrae CHO ; Heung-Mo YANG ; Sung Joo KIM ; Kwang-Won KIM
Diabetes & Metabolism Journal 2024;48(6):1160-1168
Background:
Islet transplantation holds promise for treating selected type 1 diabetes mellitus patients, yet the scarcity of human donor organs impedes widespread adoption. Porcine islets, deemed a viable alternative, recently demonstrated successful longterm survival without zoonotic risks in a clinically relevant pig-to-non-human primate islet transplantation model. This success prompted the development of a clinical trial protocol for porcine islet xenotransplantation in humans.
Methods:
A single-center, open-label clinical trial initiated by the sponsor will assess the safety and efficacy of porcine islet transplantation for diabetes patients at Gachon Hospital. The protocol received approval from the Gachon Hospital Institutional Review Board (IRB) and the Korean Ministry of Food and Drug Safety (MFDS) under the Investigational New Drug (IND) process. Two diabetic patients, experiencing inadequate glycemic control despite intensive insulin treatment and frequent hypoglycemic unawareness, will be enrolled. Participants and their family members will engage in deliberation before xenotransplantation during the screening period. Each patient will receive islets isolated from designated pathogen-free pigs. Immunosuppressants and systemic infection prophylaxis will follow the program schedule. The primary endpoint is to confirm the safety of porcine islets in patients, and the secondary endpoint is to assess whether porcine islets can reduce insulin dose and the frequency of hypoglycemic unawareness.
Conclusion
A clinical trial protocol adhering to global consensus guidelines for porcine islet xenotransplantation is presented, facilitating streamlined implementation of comparable human trials worldwide.
5.Development of a Deep Learning-Based Predictive Model for Improvement after Holmium Laser Enucleation of the Prostate According to Detrusor Contractility
Jong Hoon LEE ; Jung Hyun KIM ; Myung Jin CHUNG ; Kyu-Sung LEE ; Kwang Jin KO
International Neurourology Journal 2024;28(Suppl 2):S82-89
Purpose:
Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery.
Methods:
We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning.
Results:
A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models.
Conclusions
The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.
6.Asia-Pacific consensus on long-term and sequential therapy for osteoporosis
Ta-Wei TAI ; Hsuan-Yu CHEN ; Chien-An SHIH ; Chun-Feng HUANG ; Eugene MCCLOSKEY ; Joon-Kiong LEE ; Swan Sim YEAP ; Ching-Lung CHEUNG ; Natthinee CHARATCHAROENWITTHAYA ; Unnop JAISAMRARN ; Vilai KUPTNIRATSAIKUL ; Rong-Sen YANG ; Sung-Yen LIN ; Akira TAGUCHI ; Satoshi MORI ; Julie LI-YU ; Seng Bin ANG ; Ding-Cheng CHAN ; Wai Sin CHAN ; Hou NG ; Jung-Fu CHEN ; Shih-Te TU ; Hai-Hua CHUANG ; Yin-Fan CHANG ; Fang-Ping CHEN ; Keh-Sung TSAI ; Peter R. EBELING ; Fernando MARIN ; Francisco Javier Nistal RODRÍGUEZ ; Huipeng SHI ; Kyu Ri HWANG ; Kwang-Kyoun KIM ; Yoon-Sok CHUNG ; Ian R. REID ; Manju CHANDRAN ; Serge FERRARI ; E Michael LEWIECKI ; Fen Lee HEW ; Lan T. HO-PHAM ; Tuan Van NGUYEN ; Van Hy NGUYEN ; Sarath LEKAMWASAM ; Dipendra PANDEY ; Sanjay BHADADA ; Chung-Hwan CHEN ; Jawl-Shan HWANG ; Chih-Hsing WU
Osteoporosis and Sarcopenia 2024;10(1):3-10
Objectives:
This study aimed to present the Asia-Pacific consensus on long-term and sequential therapy for osteoporosis, offering evidence-based recommendations for the effective management of this chronic condition.The primary focus is on achieving optimal fracture prevention through a comprehensive, individualized approach.
Methods:
A panel of experts convened to develop consensus statements by synthesizing the current literature and leveraging clinical expertise. The review encompassed long-term anti-osteoporosis medication goals, first-line treatments for individuals at very high fracture risk, and the strategic integration of anabolic and anti resorptive agents in sequential therapy approaches.
Results:
The panelists reached a consensus on 12 statements. Key recommendations included advocating for anabolic agents as the first-line treatment for individuals at very high fracture risk and transitioning to anti resorptive agents following the completion of anabolic therapy. Anabolic therapy remains an option for in dividuals experiencing new fractures or persistent high fracture risk despite antiresorptive treatment. In cases of inadequate response, the consensus recommended considering a switch to more potent medications. The consensus also addressed the management of medication-related complications, proposing alternatives instead of discontinuation of treatment.
Conclusions
This consensus provides a comprehensive, cost-effective strategy for fracture prevention with an emphasis on shared decision-making and the incorporation of country-specific case management systems, such as fracture liaison services. It serves as a valuable guide for healthcare professionals in the Asia-Pacific region, contributing to the ongoing evolution of osteoporosis management.
7.Hyperbaric Oxygen Therapy for the Treatment of Chronic Prostatitis/Chronic Pelvic Pain Syndrome: Case Report
Kwang Jin KIM ; Yoonsuk LEE ; Yong Sung CHA ; Tae Wook KANG ; Hyun Chul CHUNG ; Hong CHUNG ; Hyun KIM ; Jae Hung JUNG
Urogenital Tract Infection 2024;19(2):44-47
Hyperbaric oxygen therapy (HBOT) was conducted on two male patients with chronic prostatitis/chronic pelvic pain syndrome who were resistant to conventional medical therapies. Both patients underwent 20 sessions of 100% oxygen inhalation (2.0 atmosphere absolute for 90 min/day, five days/week for four weeks) in a hyperbaric chamber. The follow-up period was three months. Although the patients reported a slight improvement in the pain domain of the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) after HBOT, no changes were noted in the other domains of NIH-CPSI and International Prostate Symptom Score. No adverse events were encountered during or after HBOT.
8.Development of a Deep Learning-Based Predictive Model for Improvement after Holmium Laser Enucleation of the Prostate According to Detrusor Contractility
Jong Hoon LEE ; Jung Hyun KIM ; Myung Jin CHUNG ; Kyu-Sung LEE ; Kwang Jin KO
International Neurourology Journal 2024;28(Suppl 2):S82-89
Purpose:
Predicting improvements in voiding symptoms following deobstructive surgery for male lower urinary tract symptoms/benign prostatic hyperplasia (LUTS/BPH) is challenging when detrusor contractility is impaired. This study aimed to develop an artificial intelligence model that predicts symptom improvement after holmium laser enucleation of the prostate (HoLEP), focusing on changes in maximum flow rate (MFR) and voiding efficiency (VE) 1-month postsurgery.
Methods:
We reviewed 1,933 patients who underwent HoLEP at Samsung Medical Center from July 2008 to January 2024. The study employed a deep neural network (DNN) for multiclass classification to predict changes in MFR and VE, each divided into 3 categories. For comparison, additional machine learning (ML) models such as extreme gradient boosting, random forest classification, and support vector machine were utilized. To address class imbalance, we applied the least squares method and multitask learning.
Results:
A total of 1,142 patients with complete data were included in the study, with 992 allocated for model training and 150 for external validation. In predicting MFR, the DNN achieved a microaverage area under the receiver operating characteristic curve (AUC) of 0.884±0.006, sensitivity of 0.783±0.020, and specificity of 0.891±0.010. For VE prediction, the microaverage AUC was 0.817±0.007, with sensitivity and specificity values of 0.660±0.014 and 0.830±0.007, respectively. These results indicate that the DNN's predictive performance was superior to that of other ML models.
Conclusions
The DNN model provides detailed and accurate predictions for recovery after HoLEP, providing valuable insights for clinicians managing patients with LUTS/BPH.
9.Clinical Trial Protocol for Porcine Islet Xenotransplantation in South Korea
Byung-Joon KIM ; Jun-Seop SHIN ; Byoung-Hoon MIN ; Jong-Min KIM ; Chung-Gyu PARK ; Hee-Jung KANG ; Eung Soo HWANG ; Won-Woo LEE ; Jung-Sik KIM ; Hyun Je KIM ; Iov KWON ; Jae Sung KIM ; Geun Soo KIM ; Joonho MOON ; Du Yeon SHIN ; Bumrae CHO ; Heung-Mo YANG ; Sung Joo KIM ; Kwang-Won KIM
Diabetes & Metabolism Journal 2024;48(6):1160-1168
Background:
Islet transplantation holds promise for treating selected type 1 diabetes mellitus patients, yet the scarcity of human donor organs impedes widespread adoption. Porcine islets, deemed a viable alternative, recently demonstrated successful longterm survival without zoonotic risks in a clinically relevant pig-to-non-human primate islet transplantation model. This success prompted the development of a clinical trial protocol for porcine islet xenotransplantation in humans.
Methods:
A single-center, open-label clinical trial initiated by the sponsor will assess the safety and efficacy of porcine islet transplantation for diabetes patients at Gachon Hospital. The protocol received approval from the Gachon Hospital Institutional Review Board (IRB) and the Korean Ministry of Food and Drug Safety (MFDS) under the Investigational New Drug (IND) process. Two diabetic patients, experiencing inadequate glycemic control despite intensive insulin treatment and frequent hypoglycemic unawareness, will be enrolled. Participants and their family members will engage in deliberation before xenotransplantation during the screening period. Each patient will receive islets isolated from designated pathogen-free pigs. Immunosuppressants and systemic infection prophylaxis will follow the program schedule. The primary endpoint is to confirm the safety of porcine islets in patients, and the secondary endpoint is to assess whether porcine islets can reduce insulin dose and the frequency of hypoglycemic unawareness.
Conclusion
A clinical trial protocol adhering to global consensus guidelines for porcine islet xenotransplantation is presented, facilitating streamlined implementation of comparable human trials worldwide.
10.Hyperbaric Oxygen Therapy for the Treatment of Chronic Prostatitis/Chronic Pelvic Pain Syndrome: Case Report
Kwang Jin KIM ; Yoonsuk LEE ; Yong Sung CHA ; Tae Wook KANG ; Hyun Chul CHUNG ; Hong CHUNG ; Hyun KIM ; Jae Hung JUNG
Urogenital Tract Infection 2024;19(2):44-47
Hyperbaric oxygen therapy (HBOT) was conducted on two male patients with chronic prostatitis/chronic pelvic pain syndrome who were resistant to conventional medical therapies. Both patients underwent 20 sessions of 100% oxygen inhalation (2.0 atmosphere absolute for 90 min/day, five days/week for four weeks) in a hyperbaric chamber. The follow-up period was three months. Although the patients reported a slight improvement in the pain domain of the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI) after HBOT, no changes were noted in the other domains of NIH-CPSI and International Prostate Symptom Score. No adverse events were encountered during or after HBOT.

Result Analysis
Print
Save
E-mail