https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/372 2026-07-03T22:21:31Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212314 Title: Critical illness-related corticosteroid insufficiency after acute brain hemorrhage surgery: a prospective cohort study with a randomized trial of hydrocortisone : HYdrocortisone theraPy in nEurocRitical illness; HYPER study Authors: Kim, Moinay; Jung, Hyunchul; Kim, Seung Bin; Jeon, Hanwool; Chung, Yeongu; Shim, Youngbo; Kwon, Sae Min; Kim, Jae Hyun; Chung, Jaewoo; Choi, Kyu-Sun; Lee, Heui Seung; Byun, Joonho; Lee, Si Un; Park, Wonhyoung; Park, Jung Cheol; Ahn, Jae Sung; Lee, Seungjoo Abstract: Background Critical illness-related corticosteroid insufficiency (CIRCI) is a potentially underrecognized complication in postoperative patients with acute brain hemorrhage. Its incidence, associated risk factors, and the therapeutic role of corticosteroids in this population remain unclear. Method This multicenter study combined a prospective observational cohort with a single-blinded randomized controlled trial. Adult patients aged 18-80 years who underwent neurological surgery for acute brain hemorrhage within 48 h of admission at tertiary care hospitals were eligible for inclusion. Acute brain hemorrhage was confirmed by computed tomography or magnetic resonance imaging and included both traumatic (e.g., epidural or subdural hematoma) and non-traumatic etiologies (e.g., aneurysmal subarachnoid hemorrhage). Among 497 screened patients, 255 eligible postoperative patients underwent adrenal function testing using a high-dose corticotropin stimulation test (HDST) on postoperative day (POD) 2 or 3. Patients diagnosed with CIRCI (n = 64, 25.1%) were randomized in a 1:1 ratio to receive intravenous hydrocortisone or placebo. The primary outcome was neurological improvement at 30 days assessed using the modified Rankin Scale (mRS). Results CIRCI was diagnosed in 25.1% of patients. Independent predictors of CIRCI included traumatic subdural hematoma, epidural hematoma, mechanical ventilation, and fresh frozen plasma transfusion. While hydrocortisone did not significantly improve the primary outcome of 30-day neurological function, it significantly reduced mechanical ventilation duration (median [IQR], 5 [3-7] vs. 10 [6-16] days; p = 0.032) and ICU length of stay (5 [2-13] vs. 13 [3-18] days; p = 0.038). No increase in serious adverse events was observed. Conclusion CIRCI is common in postoperative patients with acute brain hemorrhage and is associated with specific clinical risk factors. Although targeted hydrocortisone therapy did not significantly improve functional outcomes at 30 days, it yielded significant improvements in short-term ICU parameters. These findings warrant further adequately powered studies to evaluate the role of corticosteroid therapy in patients with acute brain hemorrhage diagnosed with CIRCI. Clinical trial registration This study was registered with the Clinical Research Information Service (CRIS), a primary registry of the WHO International Clinical Trials Registry Platform, under the identifier KCT0004425. The trial was prospectively registered on 5 November 2019. 2026-12-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212886 Title: Machine Learning Prediction of Prevertebral Soft Tissue Swelling after Single-Level Anterior Cervical Surgery : A Proof-of-Concept Study Authors: Hwang, Joon Hyun; Kang, Sang Mook; Ha, Byeong Jin; Won, Yu Deok; Han, Myung-Hoon; Cheong, Jin Hwan; Ko, Shin-Woong; Il Ryu, Je Abstract: Objective : Prevertebral soft tissue swelling (PSTS) is a significant complication of anterior cervical spine surgery (ACSS) that causes dysphagia, dysphonia, and possibly life-threatening airway obstruction. This study aims to develop and internally validate an interpretable machine learning model to predict significant PSTS after single-level ACSS using a small, single-center dataset. Methods : We retrospectively analyzed data from 62 patients who underwent single-level ACSS in our center, from January 2014 to December 2022. Postoperative swelling over 7.0 mm (above 75th percentile) was defined as significant PSTS. We developed an elastic net regularized logistic regression model over 1000 iterations with nested 5-fold cross validation for hyperparameter tuning and bootstrap validation. The model's interpretability was assessed using SHapley Additive exPlanations (SHAP) approach, and its clinical utility by decision curve analysis. Results : A total of 16 (25.8%) out of 62 patients developed significant PSTS. Our model achieved a bootstrap-validated area under the ROC curve value of 0.84 (95% confidence interval, 0.73-0.92) with good calibration (Hosmer-Lemeshow p=0.42). According to our results, important predictors of PSTS included 1) low preoperative serum albumin (SHAP importance, 0.42), 2) upper level surgery above C5 (0.38), and 3) male sex (0.31). Decision curve analysis demonstrated net benefit across probability thresholds of 15-45%. Conclusion : Our machine learning model effectively predicted risk of significant PSTS following single-level ACSS despite small sample size. Such findings offer new opportunities for risk stratification and prevention strategies. This study is a proof of concept for artificial intelligence (AI)-based risk stratification strategy; further external validation could improve its relevance in the clinical setting. 2026-05-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213328 Title: Prediction of Posterior Communicating Artery Aneurysm Rupture Risk: A Multivariate Analysis of Aneurysm and Surrounding Arterial Morphological Factors Authors: Nahm, Minu; Ko, Shin-Woong; Yi, Hyeong-Joong; Chun, Hyeong-Joon; Na, Min-Kyun; Lee, Young-Jun; Kim, KyuNam; Lee, Sang Hyung; Ryu, Jaiyoung; Song, Simon; Han, Kunhee; Choi, Kyu-Sun Abstract: Background/Objectives: Recent studies have increasingly focused on the morphological characteristics of surrounding arteries as rupture predictors, particularly because these vessel configurations remain stable before and after aneurysm rupture, providing a reliable anatomical substrate for risk assessment. This study aimed to identify independent predictors of rupture by evaluating both aneurysmal and internal carotid artery (ICA) morphological characteristics. Methods: We retrospectively analyzed imaging data from 64 patients with posterior communicating artery (PcomA) aneurysms who underwent treatment at a single tertiary center between 2018 and 2022, including 25 ruptured aneurysms (39.1%). Only treated aneurysms were included to ensure the availability of high-quality pre-treatment digital subtraction angiography (DSA) suitable for three-dimensional (3D) reconstruction and centerline-based analysis. Seventeen aneurysm morphological parameters and thirteen ICA-related parameters were measured. Because time-to-event data were not available, logistic regression analysis was performed with rupture status as the outcome variable. Receiver operating characteristic (ROC) curve analyses were conducted to evaluate discriminative performance. Results: Multivariate logistic regression revealed that three ICA-associated factors—the tortuosity of the communicating ICA segment (Tcco), the ICA cross-sectional area at the PcomA origin (Pcs), and the angle between the ICA and PcomA (θ2)—were independently associated with rupture. Among aneurysm-related factors, Maximum 3D Diameter remained significantly related to rupture risk. ROC analyses demonstrated that Maximum 3D Diameter had the highest discriminative value (AUC 0.779; cut-off 7.805 mm), followed by Pcs, Tcco, and θ2. Conclusions: Both aneurysm morphology and the anatomical configuration of surrounding arteries significantly contribute to rupture risk in PcomA aneurysms. Incorporating parent-vessel morphological features into rupture-risk assessment may enhance patient-specific decision-making. 2026-05-01T00:00:00Z https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212780 Title: Multi-Omics and Machine Learning Analyses Reveal PIK3CG, PRKCD, and TRIM22 as Potential Markers of Poor Prognosis and Immune Activation in Glioblastoma Authors: Han, Myung-Hoon; Noh, Yung-Kyun; Kim, Hyunkee; Kim, Kyu Shik; Kim, Dong-Hoon; Jung, Un Suk; Lee, Kyung Suk; Kwon, Mi Jung; Chae, Seoung Wan; Min, Kyueng-Whan Abstract: Background: Glioblastoma (GBM) is one of the most aggressive brain tumors with a poor prognosis despite current treatment modalities. This study aimed to identify genes whose high expression is paradoxically associated with both poor survival and enhanced immune activity, as potential targets for combination chemotherapeutic and immunotherapeutic strategies. Methods: Transcriptomic data from patients with central nervous system World Health Organization (WHO) grade IV gliomas (based on the 2016 WHO classification) were analyzed, using datasets from The Cancer Genome Atlas (525 cases), the Chinese Glioma Genome Atlas (250 cases), and the Genotype-Tissue Expression (1,152 normal samples). We initially screened 12,041 genes, prioritizing those showing a paradoxical association with prognosis and immune activation. Key genes were selected through rank statistics, machine-learning-based survival modeling, and pathway network analysis. Further subgroup validation was performed using only isocitrate dehydrogenase (IDH)-wildtype GBM cases, in line with the 2021 WHO classification. Results: Among the 12,041 candidate genes analyzed, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma (PIK3CG), protein kinase C delta type (PRKCD), and tripartite motif-containing protein 22 (TRIM22) were identified as key biomarkers whose elevated expression was significantly associated with poorer overall and disease-specific survival in IDH-wildtype GBM. These genes also correlated with enhanced immune activity, including increased tumor-infiltrating lymphocytes and elevated expression of programmed death-ligand 1. Pathway network analysis revealed indirect associations with critical immune markers such as CD8A and CD4, suggesting potential immunomodulatory functions. Additionally, differential gene expression and disease ontology analyses demonstrated their relevance across various cancer types. Drug sensitivity profiling using the Genomics of Drug Sensitivity in Cancer database identified AGI-6780, linsitinib, and Nutlin-3a as potential therapeutic agents targeting these genes. Conclusion: This study identifies PIK3CG, PRKCD, and TRIM22 as potential biomarkers and therapeutic targets in IDH-wildtype GBM. Their paradoxical association with poor survival and immune activation may inform personalized treatment strategies that combine conventional chemotherapy with immune-based therapies. While our findings are robust across both mixed and IDH-wildtype-focused cohorts, further mechanistic validation is warranted. 2026-04-01T00:00:00Z