1.Intradialytic hypotension and worse outcomes in patients with acute kidney injury requiring intermittent hemodialysis
Yeong-Won PARK ; Donghwan YUN ; Yeojin YU ; Sang Hyun KIM ; Sehoon PARK ; Yong Chul KIM ; Dong Ki KIM ; Kook-Hwan OH ; Kwon Wook JOO ; Yon Su KIM ; Seong Geun KIM ; Seung Seok HAN
Kidney Research and Clinical Practice 2026;45(1):77-85
Background:
Intradialytic hypotension (IDH) is a critical complication related to worse outcomes in patients undergoing maintenance hemodialysis. Herein, we addressed the impact of IDH on mortality and other outcomes in patients with severe acute kidney injury (AKI) requiring intermittent hemodialysis.
Methods:
We retrospectively reviewed 1,009 patients who underwent intermittent hemodialysis due to severe AKI. IDH was defined as either dialysis discontinuation due to hemodynamic instability or a decrease in systolic blood pressure (BP) of ≥30 mmHg, with or without a nadir systolic BP of <90 mmHg during the first session. The primary outcome was all-cause mortality, and transfer to the intensive care unit (ICU) due to unstable status was additionally analyzed. Hazard ratios (HRs) of outcomes were calculated using a Cox regression model after adjusting for multiple variables. Risk factors for IDH were evaluated using a logistic regression model.
Results:
IDH occurred in 449 patients (44.5%) during the first hemodialysis session. Patients with IDH had a higher mortality rate than those without IDH (40% vs. 23%; HR, 1.30; 95% confidence interval [CI], 1.02–1.65). The rate of ICU transfer was higher in patients experiencing IDH than in those without IDH (17% vs. 11%; HR, 1.43; 95% CI, 1.02–2.02). Factors such as old age, high BP and pulse rate, active malignancy, cirrhosis, and hypoalbuminemia were associated with an increased risk of IDH episodes.
Conclusion
The occurrence of IDH is associated with worse outcomes in patients with AKI requiring intermittent hemodialysis. Therefore, careful monitoring and early intervention of IDH may be necessary in this patient subset.
2.Recurrence Dynamics of Pathological N2 Non–Small Cell Lung Cancer Based on IASLC Residual Tumor Descriptor
In Ha KIM ; Geun Dong LEE ; Sehoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):105-115
Purpose:
This study investigated the recurrence patterns and timing in patients with pathologic N2 (pN2) non-small cell lung cancer (NSCLC) according to the residual tumor (R) descriptor proposed by the International Association for the Study of Lung Cancer (IASLC).
Materials and Methods:
From 2004 to 2021, patients with pN2 NSCLC who underwent anatomical resection were analyzed according to the IASLC R criteria using medical records from a single center. Survival analysis was performed using Cox proportional hazards models. Recurrence patterns between complete (R0) and uncertain resections (R[un]) were compared.
Results:
In total, 1,373 patients were enrolled in this study: 576 (42.0%) in R0, 286 (20.8%) in R(un), and 511 (37.2%) in R1/R2 according to the IASLC R criteria. The most common reason for R(un) classification was positivity for the highest lymph node (88.8%). In multivariable analysis, the hazard ratios for recurrence in R(un) and R1/R2 compared to R0 were 1.18 (95% confidence interval [CI], 0.96–1.46) and 1.58 (1.31–1.90), respectively. The hazard rate curves displayed similar patterns among groups, peaking at approximately 12 months after surgery. There was a significant difference in distant recurrence patterns between R0 and R(un). Further analysis after stratification with the IASLC N2 descriptor showed significant differences in distant recurrence patterns between R0 and R(un) in patients pN2a1 and pN2a2 disease, but not in those with pN2b disease.
Conclusion
The IASLC R criteria has prognostic relevance in patients with pN2 NSCLC. R(un) is a highly heterogeneous group, and the involvement of the highest mediastinal lymph node can affect distant recurrence patterns.
3.Differences in the Prognostic Impact between Single-Zone and Multi-Zone N2 Node Metastasis in Patients with Station-Based Multiple N2 Non–Small Cell Lung Cancer
Shia KIM ; Geun Dong LEE ; SeHoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):95-104
Purpose:
The International Association for the Study of Lung Cancer suggests further subdivision of pathologic N (pN) category in non–small-cell lung cancer (NSCLC) by incorporating the location and number of involved lymph node (LN) stations. We reclassified patients with the station-based N2b disease into single-zone and multi-zone N2b groups and compared survival outcomes between the groups.
Materials and Methods:
This retrospective study included patients with pN2 NSCLC who underwent lobectomy from 2006 to 2019. The N2 disease was subdivided into four categories: single-station N2 without N1 (N2a1), single-station N2 with N1 (N2a2), multiple-station N2 with single zone involvement (single-zone N2b), and multiple-station N2 with multiple zone involvement (multi-zone N2b). LN zones included in the subdivision of N2 disease were upper mediastinal, lower mediastinal, aortopulmonary, and subcarinal.
Results:
Among 996 eligible patients, 211 (21.2%), 394 (39.6%), and 391 (39.3%) were confirmed to have pN2a1, pN2a2, and pN2b disease, respectively. In multivariable analysis after adjustment for sex, age, pT category, and adjuvant chemotherapy, overall survival was significantly better with single-zone N2b disease (n=125, 12.6%) than with multi-zone N2b disease (n=266, 26.7%) (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.49 to 0.90; p=0.009) and was comparable to that of N2a2 disease (HR, 1.12; 95% CI, 0.83 to 1.49; p=0.46).
Conclusion
Prognosis of single-zone LN metastasis was better than that of multiple-zone LN metastasis in patients with N2b NSCLC. Along with the station-based N descriptors, zone-based descriptors might ensure optimal staging, enabling the most appropriate decision-making on adjuvant therapy for patients with pN2 NSCLC.
4.Recurrence Dynamics of Pathological N2 Non–Small Cell Lung Cancer Based on IASLC Residual Tumor Descriptor
In Ha KIM ; Geun Dong LEE ; Sehoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):105-115
Purpose:
This study investigated the recurrence patterns and timing in patients with pathologic N2 (pN2) non-small cell lung cancer (NSCLC) according to the residual tumor (R) descriptor proposed by the International Association for the Study of Lung Cancer (IASLC).
Materials and Methods:
From 2004 to 2021, patients with pN2 NSCLC who underwent anatomical resection were analyzed according to the IASLC R criteria using medical records from a single center. Survival analysis was performed using Cox proportional hazards models. Recurrence patterns between complete (R0) and uncertain resections (R[un]) were compared.
Results:
In total, 1,373 patients were enrolled in this study: 576 (42.0%) in R0, 286 (20.8%) in R(un), and 511 (37.2%) in R1/R2 according to the IASLC R criteria. The most common reason for R(un) classification was positivity for the highest lymph node (88.8%). In multivariable analysis, the hazard ratios for recurrence in R(un) and R1/R2 compared to R0 were 1.18 (95% confidence interval [CI], 0.96–1.46) and 1.58 (1.31–1.90), respectively. The hazard rate curves displayed similar patterns among groups, peaking at approximately 12 months after surgery. There was a significant difference in distant recurrence patterns between R0 and R(un). Further analysis after stratification with the IASLC N2 descriptor showed significant differences in distant recurrence patterns between R0 and R(un) in patients pN2a1 and pN2a2 disease, but not in those with pN2b disease.
Conclusion
The IASLC R criteria has prognostic relevance in patients with pN2 NSCLC. R(un) is a highly heterogeneous group, and the involvement of the highest mediastinal lymph node can affect distant recurrence patterns.
5.Differences in the Prognostic Impact between Single-Zone and Multi-Zone N2 Node Metastasis in Patients with Station-Based Multiple N2 Non–Small Cell Lung Cancer
Shia KIM ; Geun Dong LEE ; SeHoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):95-104
Purpose:
The International Association for the Study of Lung Cancer suggests further subdivision of pathologic N (pN) category in non–small-cell lung cancer (NSCLC) by incorporating the location and number of involved lymph node (LN) stations. We reclassified patients with the station-based N2b disease into single-zone and multi-zone N2b groups and compared survival outcomes between the groups.
Materials and Methods:
This retrospective study included patients with pN2 NSCLC who underwent lobectomy from 2006 to 2019. The N2 disease was subdivided into four categories: single-station N2 without N1 (N2a1), single-station N2 with N1 (N2a2), multiple-station N2 with single zone involvement (single-zone N2b), and multiple-station N2 with multiple zone involvement (multi-zone N2b). LN zones included in the subdivision of N2 disease were upper mediastinal, lower mediastinal, aortopulmonary, and subcarinal.
Results:
Among 996 eligible patients, 211 (21.2%), 394 (39.6%), and 391 (39.3%) were confirmed to have pN2a1, pN2a2, and pN2b disease, respectively. In multivariable analysis after adjustment for sex, age, pT category, and adjuvant chemotherapy, overall survival was significantly better with single-zone N2b disease (n=125, 12.6%) than with multi-zone N2b disease (n=266, 26.7%) (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.49 to 0.90; p=0.009) and was comparable to that of N2a2 disease (HR, 1.12; 95% CI, 0.83 to 1.49; p=0.46).
Conclusion
Prognosis of single-zone LN metastasis was better than that of multiple-zone LN metastasis in patients with N2b NSCLC. Along with the station-based N descriptors, zone-based descriptors might ensure optimal staging, enabling the most appropriate decision-making on adjuvant therapy for patients with pN2 NSCLC.
6.Recurrence Dynamics of Pathological N2 Non–Small Cell Lung Cancer Based on IASLC Residual Tumor Descriptor
In Ha KIM ; Geun Dong LEE ; Sehoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):105-115
Purpose:
This study investigated the recurrence patterns and timing in patients with pathologic N2 (pN2) non-small cell lung cancer (NSCLC) according to the residual tumor (R) descriptor proposed by the International Association for the Study of Lung Cancer (IASLC).
Materials and Methods:
From 2004 to 2021, patients with pN2 NSCLC who underwent anatomical resection were analyzed according to the IASLC R criteria using medical records from a single center. Survival analysis was performed using Cox proportional hazards models. Recurrence patterns between complete (R0) and uncertain resections (R[un]) were compared.
Results:
In total, 1,373 patients were enrolled in this study: 576 (42.0%) in R0, 286 (20.8%) in R(un), and 511 (37.2%) in R1/R2 according to the IASLC R criteria. The most common reason for R(un) classification was positivity for the highest lymph node (88.8%). In multivariable analysis, the hazard ratios for recurrence in R(un) and R1/R2 compared to R0 were 1.18 (95% confidence interval [CI], 0.96–1.46) and 1.58 (1.31–1.90), respectively. The hazard rate curves displayed similar patterns among groups, peaking at approximately 12 months after surgery. There was a significant difference in distant recurrence patterns between R0 and R(un). Further analysis after stratification with the IASLC N2 descriptor showed significant differences in distant recurrence patterns between R0 and R(un) in patients pN2a1 and pN2a2 disease, but not in those with pN2b disease.
Conclusion
The IASLC R criteria has prognostic relevance in patients with pN2 NSCLC. R(un) is a highly heterogeneous group, and the involvement of the highest mediastinal lymph node can affect distant recurrence patterns.
7.Differences in the Prognostic Impact between Single-Zone and Multi-Zone N2 Node Metastasis in Patients with Station-Based Multiple N2 Non–Small Cell Lung Cancer
Shia KIM ; Geun Dong LEE ; SeHoon CHOI ; Hyeong Ryul KIM ; Yong-Hee KIM ; Dong Kwan KIM ; Seung-Il PARK ; Jae Kwang YUN
Cancer Research and Treatment 2025;57(1):95-104
Purpose:
The International Association for the Study of Lung Cancer suggests further subdivision of pathologic N (pN) category in non–small-cell lung cancer (NSCLC) by incorporating the location and number of involved lymph node (LN) stations. We reclassified patients with the station-based N2b disease into single-zone and multi-zone N2b groups and compared survival outcomes between the groups.
Materials and Methods:
This retrospective study included patients with pN2 NSCLC who underwent lobectomy from 2006 to 2019. The N2 disease was subdivided into four categories: single-station N2 without N1 (N2a1), single-station N2 with N1 (N2a2), multiple-station N2 with single zone involvement (single-zone N2b), and multiple-station N2 with multiple zone involvement (multi-zone N2b). LN zones included in the subdivision of N2 disease were upper mediastinal, lower mediastinal, aortopulmonary, and subcarinal.
Results:
Among 996 eligible patients, 211 (21.2%), 394 (39.6%), and 391 (39.3%) were confirmed to have pN2a1, pN2a2, and pN2b disease, respectively. In multivariable analysis after adjustment for sex, age, pT category, and adjuvant chemotherapy, overall survival was significantly better with single-zone N2b disease (n=125, 12.6%) than with multi-zone N2b disease (n=266, 26.7%) (hazard ratio [HR], 0.67; 95% confidence interval [CI], 0.49 to 0.90; p=0.009) and was comparable to that of N2a2 disease (HR, 1.12; 95% CI, 0.83 to 1.49; p=0.46).
Conclusion
Prognosis of single-zone LN metastasis was better than that of multiple-zone LN metastasis in patients with N2b NSCLC. Along with the station-based N descriptors, zone-based descriptors might ensure optimal staging, enabling the most appropriate decision-making on adjuvant therapy for patients with pN2 NSCLC.
8.Associations of metabolic variabilities and cardiovascular outcomes according to estimated glomerular filtration rate in chronic kidney disease: a nationwide observational cohort study
Jeong Min CHO ; Kyungdo HAN ; Kwon Wook JOO ; Soojin LEE ; Yaerim KIM ; Semin CHO ; Hyuk HUH ; Seong Geun KIM ; Minsang KIM ; Eunjeong KANG ; Dong Ki KIM ; Sehoon PARK
Kidney Research and Clinical Practice 2025;44(2):265-276
The impact of baseline estimated glomerular filtration rate (eGFR) on the risk of adverse outcomes according to metabolic parameter variabilities in chronic kidney disease has rarely been investigated. Methods: We conducted a retrospective nationwide cohort study using the National Health Insurance System data in Korea from 2007 to 2013 to identify individuals with three or more health screenings. The metabolic components variability was defined as intraindividual variability between measurements using the variability independent of the mean. The metabolic variability score was defined as the total number of high-variability metabolic components. Multivariable-adjusted Cox regression analysis was conducted to evaluate the risks of all-cause mortality, myocardial infarction, and ischemic stroke. Results: During a mean follow-up of 6.0 ± 0.7 years, 223,531 deaths, 107,140 myocardial infarctions, and 116,182 ischemic strokes were identified in 9,971,562 patients. Low eGFR categories and higher metabolic variability scores were associated with a higher risk of adverse outcomes. The degree of association between metabolic variability and adverse outcomes was significantly larger in those with low eGFR categories than in those with preserved eGFR (p for interaction < 0.001). Representatively, those with high metabolic variability in the eGFR of <15 mL/min/1.73 m2 group showed a prominently higher risk for all-cause mortality (adjusted hazard ratio [aHR], 5.28; 95% confidence interval [CI], 4.02–6.94) when the degree was compared to the findings in those with preserved (eGFR of ≥60 mL/min/1.73 m2) kidney function (aHR, 2.55; 95% CI, 2.41–2.69). Conclusion: The degree of adverse association between metabolic variability and poor prognosis is accentuated in patients with impaired kidney function.
9.Impact of albuminuria on early-onset type 2 diabetes mellitus: a nationwide population-based study
Soojin LEE ; Semin CHO ; Geum Nae NAM ; Jeongmin CHO ; Seong Geun KIM ; Minsang KIM ; Hyuk HUH ; Eunjeong KANG ; Sehoon PARK ; Jin Hyuk PAEK ; Woo Yeong PARK ; Kyubok JIN ; Seungyeup HAN ; Kwon Wook JOO ; Kyungdo HAN ; Dong Ki KIM ; Yaerim KIM
Kidney Research and Clinical Practice 2025;44(6):941-949
Early-onset diabetes mellitus has a significant lifetime burden and is associated with higher morbidity and mortality. Since insulin resistance is one of the mechanisms of podocyte injury, we aimed to evaluate the effect of albuminuria on newly developed early-onset type 2 diabetes mellitus (T2DM). Methods: We screened 6,891,399 subjects aged ≥20 and <40 years without a history of prediabetes or diabetes from the Korean National Health Insurance Service database between 2009 and 2012. A multivariate Cox proportional hazard model was used to identify the impact of albuminuria on early-onset T2DM. Results: Among a total of 5,383,779 subjects, 62,148 subjects (1.2%) developed early-onset diabetes over 7.3 ± 1.2 years. Albuminuria was significantly associated with early-onset T2DM (adjusted hazard ratio [aHR], 1.62; 95% confidence interval [CI], 1.55–1.70) after adjustment for age, sex, anthropometric data, physical exercise status, serum glucose, and total cholesterol. The risk of early-onset T2DM increased more in subjects with more components of metabolic syndrome (MetS). Among each component of MetS, hypertriglyceridemia was prominently associated with early-onset T2DM (aHR, 2.02; 95% CI, 1.81–2.25) in subjects with albuminuria. Conclusion: Dipstick albuminuria was significantly associated with early-onset T2DM in young adult populations. Close monitoring of albuminuria is warranted for disease risk modification, especially in subjects with MetS.
10.Conventional machine learning-based prediction models did not outperform the International IgA Nephropathy Prediction Tool
Sehoon PARK ; Yisak KIM ; Chung Hee BAEK ; Hyunjeong CHO ; Ji In PARK ; Eun Sil KOH ; Jung Pyo LEE ; Sun-Hee PARK ; Hyung Woo KIM ; Seung Hyeok HAN ; Ho Jun CHIN ; Dong Ki KIM ; Kyung Chul MOON ; Young-Gon KIM ; Hajeong LEE
Kidney Research and Clinical Practice 2025;44(5):802-813
Immunoglobulin A nephropathy (IgAN) is a major cause of end-stage kidney disease (ESKD). The International IgA Nephropathy Prediction Tool (IIgAN-PT) predicts IgAN prognosis, but improvement in the prediction performance using machine learning (ML)-based methods is needed. Methods: We analyzed 4,425 biopsy-confirmed patients with IgAN and ≥6 months of follow-up from nine tertiary university hospitals in Korea. The study population was divided into development and validation cohorts. Using the collected 87 clinicodemographic and pathological variables, ML-based prediction models for ESKD or estimated glomerular filtration rate decline (50% reduction or <15 mL/min/1.73 m2 ) were constructed: 1) the conventional CatBoost model, 2) the optimized CatBoost model with Cox proportional hazards, 3) the deep Cox proportional hazards model, and 4) the deep Cox mixture model. The area under the curve (AUC) and calibration plots were used to investigate the discriminative and calibration performance of the models, which were then compared with those of the IIgAN-PT full model. Results: The full model showed excellent performance (AUC [95% confidence interval] for 5-year outcome, 0.896 [0.853–0.940]), with acceptable calibration results. The ML-based models showed good performance in predicting adverse kidney outcomes and revealed acceptable discrimination performance in the external validation (AUC [95% confidence interval] for the 5-year outcome: 1) 0.829 [0.791–0.866]; 2) 0.847 [0.804–0.890]; 3) 0.823 [0.784–0.862]; and 4) 0.832 [0.794–0.870]), although the models showed underestimation in calibration analysis of the external validation cohort. With the validation data, the overall performance of the IIgAN-PT was non-inferior to that of the ML-based model. Conclusions: Our ML-based models showed good performance in predicting adverse kidney outcomes in patients with IgAN but they did not outperform the IIgAN-PT.

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