1.Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery
Insun PARK ; Jae Hyon PARK ; Young Hyun KOO ; Chang-Hoon KOO ; Bon-Wook KOO ; Jin-Hee KIM ; Ah-Young OH
Yonsei Medical Journal 2025;66(3):160-171
Purpose:
To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.
Materials and Methods:
Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers.
Results:
A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001).
Conclusion
ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.
2.Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery
Insun PARK ; Jae Hyon PARK ; Young Hyun KOO ; Chang-Hoon KOO ; Bon-Wook KOO ; Jin-Hee KIM ; Ah-Young OH
Yonsei Medical Journal 2025;66(3):160-171
Purpose:
To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.
Materials and Methods:
Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers.
Results:
A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001).
Conclusion
ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.
3.Sex Differences in Procedural Characteristics and Clinical Outcomes Among Patients Undergoing Bifurcation PCI
Hyun Jin AHN ; Francesco BRUNO ; Jeehoon KANG ; Doyeon HWANG ; Han-Mo YANG ; Jung-Kyu HAN ; Leonardo De LUCA ; Ovidio de FILIPPO ; Alessio MATTESINI ; Kyung Woo PARK ; Alessandra TRUFFA ; Wojciech WANHA ; Young Bin SONG ; Sebastiano GILI ; Woo Jung CHUN ; Gerard HELFT ; Seung-Ho HUR ; Bernardo CORTESE ; Seung Hwan HAN ; Javier ESCANED ; Alaide CHIEFFO ; Ki Hong CHOI ; Guglielmo GALLONE ; Joon-Hyung DOH ; Gaetano De FERRARI ; Soon-Jun HONG ; Giorgio QUADRI ; Chang-Wook NAM ; Hyeon-Cheol GWON ; Hyo-Soo KIM ; Fabrizio D’ASCENZO ; Bon-Kwon KOO
Korean Circulation Journal 2025;55(1):5-16
Background and Objectives:
The risk profiles, procedural characteristics, and clinical outcomes for women undergoing bifurcation percutaneous coronary intervention (PCI) are not well defined compared to those in men.
Methods:
COronary BIfurcation Stenting III (COBIS III) is a multicenter, real-world registry of 2,648 patients with bifurcation lesions treated with second-generation drug-eluting stents.We compared the angiographic and procedural characteristics and clinical outcomes based on sex. The primary outcome was 5-year target lesion failure (TLF), a composite of cardiac death, myocardial infarction, and target lesion revascularization.
Results:
Women (n=635, 24%) were older, had hypertension and diabetes more often, and had smaller main vessel and side branch reference diameters than men. The pre- and post-PCI angiographic percentage diameter stenoses of the main vessel and side branch were comparable between women and men. There were no differences in procedural characteristics between the sexes. Women and men had a similar risk of TLF (6.3% vs. 7.1%, p=0.63) as well as its individual components and sex was not an independent predictor of TLF. This finding was consistent in the left main and 2 stenting subgroups.
Conclusions
In patients undergoing bifurcation PCI, sex was not an independent predictor of adverse outcome.
4.Outcomes of Deferring Percutaneous Coronary Intervention Without Physiologic Assessment for Intermediate Coronary Lesions
Jihoon KIM ; Seong-Hoon LIM ; Joo-Yong HAHN ; Jin-Ok JEONG ; Yong Hwan PARK ; Woo Jung CHUN ; Ju Hyeon OH ; Dae Kyoung CHO ; Yu Jeong CHOI ; Eul-Soon IM ; Kyung-Heon WON ; Sung Yun LEE ; Sang-Wook KIM ; Ki Hong CHOI ; Joo Myung LEE ; Taek Kyu PARK ; Jeong Hoon YANG ; Young Bin SONG ; Seung-Hyuk CHOI ; Hyeon-Cheol GWON
Korean Circulation Journal 2025;55(3):185-195
Background and Objectives:
Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment.
Methods:
A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years.
Results:
The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization.
Conclusions
For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.
5.Poor Prognosis of Pneumococcal Co-Infection in Hospitalized Patients with COVID-19: A Propensity Score-Matched Analysis
Soyoon HWANG ; Eunkyung NAM ; Shin-Woo KIM ; Hyun-Ha CHANG ; Yoonjung KIM ; Sohyun BAE ; Nan Young LEE ; Yu Kyung KIM ; Ji Sun KIM ; Han Wook PARK ; Joon Gyu BAE ; Juhwan JEONG ; Ki Tae KWON
Infection and Chemotherapy 2025;57(1):172-178
The impact of Streptococcus pneumoniae coinfection on coronavirus disease 2019 (COVID-19) prognosis remains uncertain. We conducted a retrospective analysis of patients hospitalized with COVID-19 who underwent a pneumococcal urinary antigen (PUA) test to assess its clinical utility. Results showed that PUA-positive patients required more oxygen support, high-flow nasal cannula, and dexamethasone compared to PUA-negative patients.Furthermore, the significantly higher incidence of a National Early Warning Score ≥5 in the PUA-positive group (P<0.001) suggests that a positive PUA test is associated with a severe disease course. However, no significant difference in mortality was observed between the two groups, and antibiotics were used in almost all patients (96.2%). While the PUA test may help guide antibiotic use in COVID-19 patients, its interpretation should be approached with caution.
6.Study Protocol of Expanded Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro-EXP)
Jae Hoon MOON ; Eun Kyung LEE ; Wonjae CHA ; Young Jun CHAI ; Sun Wook CHO ; June Young CHOI ; Sung Yong CHOI ; A Jung CHU ; Eun-Jae CHUNG ; Yul HWANGBO ; Woo-Jin JEONG ; Yuh-Seog JUNG ; Kyungsik KIM ; Min Joo KIM ; Su-jin KIM ; Woochul KIM ; Yoo Hyung KIM ; Chang Yoon LEE ; Ji Ye LEE ; Kyu Eun LEE ; Young Ki LEE ; Hunjong LIM ; Do Joon PARK ; Sue K. PARK ; Chang Hwan RYU ; Junsun RYU ; Jungirl SEOK ; Young Shin SONG ; Ka Hee YI ; Hyeong Won YU ; Eleanor WHITE ; Katerina MASTROCOSTAS ; Roderick J. CLIFTON-BLIGH ; Anthony GLOVER ; Matti L. GILD ; Ji-hoon KIM ; Young Joo PARK
Endocrinology and Metabolism 2025;40(2):236-246
Background:
Active surveillance (AS) has emerged as a viable management strategy for low-risk papillary thyroid microcarcinoma (PTMC), following pioneering trials at Kuma Hospital and the Cancer Institute Hospital in Japan. Numerous prospective cohort studies have since validated AS as a management option for low-risk PTMC, leading to its inclusion in thyroid cancer guidelines across various countries. From 2016 to 2020, the Multicenter Prospective Cohort Study of Active Surveillance on Papillary Thyroid Microcarcinoma (MAeSTro) enrolled 1,177 patients, providing comprehensive data on PTMC progression, sonographic predictors of progression, quality of life, surgical outcomes, and cost-effectiveness when comparing AS to immediate surgery. The second phase of MAeSTro (MAeSTro-EXP) expands AS to low-risk papillary thyroid carcinoma (PTC) tumors larger than 1 cm, driven by the hypothesis that overall risk assessment outweighs absolute tumor size in surgical decision-making.
Methods:
This protocol aims to address whether limiting AS to tumors smaller than 1 cm may result in unnecessary surgeries for low-risk PTCs detected during their rapid initial growth phase. By expanding the AS criteria to include tumors up to 1.5 cm, while simultaneously refining and standardizing the criteria for risk assessment and disease progression, we aim to minimize overtreatment and maintain rigorous monitoring to improve patient outcomes.
Conclusion
This study will contribute to optimizing AS guidelines and enhance our understanding of the natural course and appropriate management of low-risk PTCs. Additionally, MAeSTro-EXP involves a multinational collaboration between South Korea and Australia. This cross-country study aims to identify cultural and racial differences in the management of low-risk PTC, thereby enriching the global understanding of AS practices and their applicability across diverse populations.
7.Artificial Intelligence Models May Aid in Predicting Lymph Node Metastasis in Patients with T1 Colorectal Cancer
Ji Eun BAEK ; Hahn YI ; Seung Wook HONG ; Subin SONG ; Ji Young LEE ; Sung Wook HWANG ; Sang Hyoung PARK ; Dong-Hoon YANG ; Byong Duk YE ; Seung-Jae MYUNG ; Suk-Kyun YANG ; Namkug KIM ; Jeong-Sik BYEON
Gut and Liver 2025;19(1):69-76
Background/Aims:
Inaccurate prediction of lymph node metastasis (LNM) may lead to unnecessary surgery following endoscopic resection of T1 colorectal cancer (CRC). We aimed to validate the usefulness of artificial intelligence (AI) models for predicting LNM in patients with T1 CRC.
Methods:
We analyzed the clinical data, laboratory results, pathological reports, and endoscopic findings of patients who underwent radical surgery for T1 CRC. We developed AI models to predict LNM using four algorithms: regularized logistic regression classifier (RLRC), random forest classifier (RFC), CatBoost classifier (CBC), and the voting classifier (VC). Four histological factors and four endoscopic findings were included to develop AI models. Areas under the receiver operating characteristics curves (AUROCs) were measured to distinguish AI model performance in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines.
Results:
Among 1,386 patients with T1 CRC, 173 patients (12.5%) had LNM. The AUROC values of the RLRC, RFC, CBC, and VC models for LNM prediction were significantly higher (0.673, 0.640, 0.679, and 0.677, respectively) than the 0.525 suggested in accordance with the Japanese Society for Cancer of the Colon and Rectum guidelines (vs RLRC, p<0.001; vs RFC, p=0.001; vs CBC, p<0.001; vs VC, p<0.001). The AUROC value was similar between T1 colon versus T1 rectal cancers (0.718 vs 0.615, p=0.700). The AUROC value was also similar between the initial endoscopic resection and initial surgery groups (0.581 vs 0.746, p=0.845).
Conclusions
AI models trained on the basis of endoscopic findings and pathological features performed well in predicting LNM in patients with T1 CRC regardless of tumor location and initial treatment method.
8.Effect of Helicobacter pylori Eradication on Metabolic Parameters and Body Composition including Skeletal Muscle Mass: A Matched Case-Control Study
Suh Eun BAE ; Kee Don CHOI ; Jaewon CHOE ; Min Jung LEE ; Seonok KIM ; Ji Young CHOI ; Hana PARK ; Jaeil KIM ; Hye Won PARK ; Hye-Sook CHANG ; Hee Kyong NA ; Ji Yong AHN ; Kee Wook JUNG ; Jeong Hoon LEE ; Do Hoon KIM ; Ho June SONG ; Gin Hyug LEE ; Hwoon-Yong JUNG
Gut and Liver 2025;19(3):346-354
Background/Aims:
Findings on the impact of Helicobacter pylori eradication on metabolic parameters are inconsistent. This study aimed to evaluate the effects of H. pylori eradication on metabolic parameters and body composition, including body fat mass and skeletal muscle mass.
Methods:
We retrospectively reviewed the data of asymptomatic patients who underwent health screenings, including bioelectrical impedance analysis, before and after H. pylori eradication between 2005 and 2021. After matching individuals based on key factors, we compared lipid profiles, metabolic parameters, and body composition between 823 patients from the eradicated group and 823 patients from the non-eradicated groups.
Results:
Blood pressure, erythrocyte sedimentation rate, and glycated hemoglobin values were significantly lower in the eradicated group than in the non-eradicated group. However, changes in body mass index (BMI), body fat mass, appendicular skeletal muscle mass (ASM), waist circumference, and lipid profiles were not significantly different between the two groups. In a subgroup analysis of individuals aged >45 years, blood pressure, erythrocyte sedimentation rate, and glycated hemoglobin changes were significantly lower in the eradicated group than in the noneradicated group. BMI values were significantly higher in the eradicated group than in the noneradicated group; however, no significant differences were observed between the two groups regarding changes in body weight, body fat mass, ASM, or waist circumference. Total cholesterol and low-density lipoprotein cholesterol levels were significantly lower in the eradicated group than in non-eradicated group.
Conclusions
H. pylori eradication significantly reduced blood pressure, glucose levels, and systemic inflammation and improved lipid profiles in patients aged >45 years. BMI, body fat mass, ASM, and waist circumference did not significantly differ between patients in the eradicated group and those in the non-eradicated group.
9.Feasibility of a Machine Learning Classifier for Predicting Post-Induction Hypotension in Non-Cardiac Surgery
Insun PARK ; Jae Hyon PARK ; Young Hyun KOO ; Chang-Hoon KOO ; Bon-Wook KOO ; Jin-Hee KIM ; Ah-Young OH
Yonsei Medical Journal 2025;66(3):160-171
Purpose:
To develop a machine learning (ML) classifier for predicting post-induction hypotension (PIH) in non-cardiac surgeries.
Materials and Methods:
Preoperative data and early vital signs were obtained from 3669 cases in the VitalDB database, an opensource registry. PIH was defined as sustained mean arterial pressure (MAP) <65 mm Hg within 20 minutes since induction or from induction to incision. Six different ML algorithms were used to create binary classifiers to predict PIH. The primary outcome was the area under the receiver operating characteristic curve (AUROC) of ML classifiers.
Results:
A total of 2321 (63.3%) cases exhibited PIH. Among ML classifiers, the random forest regressor and extremely gradient boosting regressor showed the highest AUROC, both recording a value of 0.772. Excluding these models, the light gradient boosting machine regressor showed the second highest AUROC [0.769; 95% confidence interval (CI), 0.767–0.771], followed by the gradient boosting regressor (0.768; 95% CI, 0.763–0.772), AdaBoost regressor (0.752; 95% CI, 0.743–0.761), and automatic relevance determination regression (0.685; 95% CI, 0.669–0.701). The top three important features were mean diastolic blood pressure (DBP), minimum MAP, and minimum DBP from anesthetic induction to tracheal intubation, and these features were lower in cases with PIH (all p<0.001).
Conclusion
ML classifiers exhibited moderate performance in predicting PIH, and have the potential for real-time prediction.
10.Sex Differences in Procedural Characteristics and Clinical Outcomes Among Patients Undergoing Bifurcation PCI
Hyun Jin AHN ; Francesco BRUNO ; Jeehoon KANG ; Doyeon HWANG ; Han-Mo YANG ; Jung-Kyu HAN ; Leonardo De LUCA ; Ovidio de FILIPPO ; Alessio MATTESINI ; Kyung Woo PARK ; Alessandra TRUFFA ; Wojciech WANHA ; Young Bin SONG ; Sebastiano GILI ; Woo Jung CHUN ; Gerard HELFT ; Seung-Ho HUR ; Bernardo CORTESE ; Seung Hwan HAN ; Javier ESCANED ; Alaide CHIEFFO ; Ki Hong CHOI ; Guglielmo GALLONE ; Joon-Hyung DOH ; Gaetano De FERRARI ; Soon-Jun HONG ; Giorgio QUADRI ; Chang-Wook NAM ; Hyeon-Cheol GWON ; Hyo-Soo KIM ; Fabrizio D’ASCENZO ; Bon-Kwon KOO
Korean Circulation Journal 2025;55(1):5-16
Background and Objectives:
The risk profiles, procedural characteristics, and clinical outcomes for women undergoing bifurcation percutaneous coronary intervention (PCI) are not well defined compared to those in men.
Methods:
COronary BIfurcation Stenting III (COBIS III) is a multicenter, real-world registry of 2,648 patients with bifurcation lesions treated with second-generation drug-eluting stents.We compared the angiographic and procedural characteristics and clinical outcomes based on sex. The primary outcome was 5-year target lesion failure (TLF), a composite of cardiac death, myocardial infarction, and target lesion revascularization.
Results:
Women (n=635, 24%) were older, had hypertension and diabetes more often, and had smaller main vessel and side branch reference diameters than men. The pre- and post-PCI angiographic percentage diameter stenoses of the main vessel and side branch were comparable between women and men. There were no differences in procedural characteristics between the sexes. Women and men had a similar risk of TLF (6.3% vs. 7.1%, p=0.63) as well as its individual components and sex was not an independent predictor of TLF. This finding was consistent in the left main and 2 stenting subgroups.
Conclusions
In patients undergoing bifurcation PCI, sex was not an independent predictor of adverse outcome.

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