Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Objective: The Scales for Outcomes in Parkinson’s Disease–Cognition (SCOPA-Cog) was developed to assess cognition in patients with Parkinson’s disease (PD). In this study, we aimed to evaluate the validity and reliability of the Korean version of the SCOPACog (K-SCOPA-Cog). Methods: We enrolled 129 PD patients with movement disorders from 31 clinics in South Korea. The original version of the SCOPA-Cog was translated into Korean using the translation-retranslation method. The test–retest method with an intraclass correlation coefficient (ICC) and Cronbach’s alpha coefficient were used to assess reliability. Spearman’s rank correlation analysis with the Montreal Cognitive Assessment-Korean version (MOCA-K) and the Korean Mini-Mental State Examination (K-MMSE) were used to assess concurrent validity. Results: The Cronbach’s alpha coefficient was 0.797, and the ICC was 0.887. Spearman’s rank correlation analysis revealed a significant correlation with the K-MMSE and MOCA-K scores (r = 0.546 and r = 0.683, respectively). Conclusion Our results demonstrate that the K-SCOPA-Cog has good reliability and validity.

Mannitol, derived from mannose sugar, is crucial in treating patients with elevated intracranial pressure (ICP). Its dehydrating properties at the cellular and tissue levels increase plasma osmotic pressure, which is studied for its potential to reduce ICP through osmotic diuresis. While clinical guidelines support mannitol use in these cases, the best approach for its application continues to be debated. Important aspects needing further investigation include: 1) bolus administration versus continuous infusion, 2) ICP-based dosing versus scheduled bolus, 3) identifying the optimal infusion rate, 4) determining the appropriate dosage, 5) establishing fluid replacement plans for urinary loss, and 6) selecting monitoring techniques and thresholds to assess effectiveness and ensure safety.Due to the lack of adequate high-quality prospective research data, a comprehensive review of recent studies and clinical trials is crucial. This assessment aims to bridge the knowledge gap, improve understanding of effective mannitol use in elevated ICP patients, and provide insights for future research. In conclusion, this review aspires to contribute to the ongoing discourse on mannitol application. By integrating the latest findings, this review will offer valuable insights into the function of mannitol in decreasing ICP, thereby informing better therapeutic approaches and enhancing patient outcomes.

Objective: : Chronic subdural hematoma (CSDH) is a common neurosurgical disease and generally treated with burr-hole surgery alone. Tranexamic acid (TXA) is an antifibrinolytic agent that potentially reduces recurrence rates and the residual hematoma volume. However, the role of postoperative TXA medication remains unclear to date. This study aimed to verify the effectiveness of adjunctive TXA in the view of early hematoma resolution. Methods: : Between January 2018 and September 2021, patients with CSDH who underwent burr-hole trephination in a single tertiary institute were reviewed. The study population was divided into three groups, TXA, non-TXA, and antithrombotics (AT) groups, according to the medical history of cardio-cerebrovascular disease and TXA administration. The primary endpoint was CSDH recurrence, defined as re-appearance or re-accumulation of CSDH requiring neurosurgical interventions. The secondary outcome was CSDH resolution, defined as complete or near-complete resorption of the CSDH. The CSDH resolution time and serial changes of hematoma thickness were also investigated. Results: : A total of 240 patients was included in the analysis consisting of 185 male and 55 female, with a median age of 74 years. During the median imaging follow-up period of 75 days, 222 patients were reached to the primary or secondary endpoint. TXA was administered as an adjunctive therapy in 41 patients (TXA group, 16.9%) while 114 patients were included in the non-TXA group (47.9%) and 85 were in the AT group. The recurrence rate was the lowest in the TXA group (2.4%), followed by non-TXA (7.0%) and AT (8.2%) groups. However, there was no statistical significance due to the small number of patients with recurrence. CSDH resolution was achieved in 206 patients, and the median estimated time to resolution was significantly faster in the TXA group (p<0.001). Adjunctive TXA administration was a significant positive factor for achieving CSDH resolution (p<0.001). The hematoma thickness was comparable among the three groups at the initial time and after surgery. However, CSDH thickness in the TXA group decreased abruptly in a month and showed a significant difference from that in the other groups (p<0.001). There was no TXA-related adverse event. Conclusion : The adjunctive use of TXA after CSDH surgery significantly facilitated the resorption of residual CSDH and resulted in the early CSDH resolution. Adjunctive TXA may be an effective treatment option to reduce recurrence by enhancing CSDH resolution in the selective patients.

Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R2 and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R2 value was 0.27 and in set II, LightGBM was the best model with the highest R2 value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R2 value of 0.56 and the lowest MSE of 174.07. Conclusion The LightGBM model showed the best performance in predicting postoperative lung function.

Purpose: The incidence and prognostic implications of atrial fibrillation (AF) in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI) are controversial, especially for Korean patients. Furthermore, the pattern of antithrombotic therapy for these patients is unknown. The present study sought to identify the impact of AF on Korean patients undergoing TAVI and demonstrate the status of antithrombotic therapy for these patients. Materials and Methods: A total of 660 patients who underwent TAVI for severe AS were recruited from the nationwide K-TAVI registry in Korea. The enrolled patients were stratified into sinus rhythm (SR) and AF groups. The primary endpoint was all-cause death at 1-year. Results: AF was recorded in 135 patients [pre-existing AF 108 (16.4%) and new-onset AF 27 (4.1%)]. The rate of all-cause death at 1 year was significantly higher in patients with AF than in those with SR [16.2% vs. 6.4%, adjusted hazard ratio (HR): 2.207, 95% confidence interval (CI): 1.182–4.120, p=0.013], regardless of the onset timing of AF. The rate of new pacemaker insertion at 1 year was also significantly higher in patients with AF than in those with SR (14.0% vs. 5.5%, adjusted HR: 3.137, 95%CI: 1.621–6.071, p=0.001).Among AF patients, substantial number of patients received the combination of multiple antithrombotic agents (77.8%), and the most common combination was that of aspirin and clopidogrel (38.1%). Conclusion AF was an independent predictor of 1-year mortality and new pacemaker insertion in Korean patients undergoing TAVI.

Background: Anterior choroidal artery (AchA) aneurysms are usually small in diameter because of the size of the involved artery and are often wide-necked. Coil embolization of AchA aneurysm is thus challenging because of serious risks, such as thromboembolic occlusion of artery and perforation of aneurysm dome. Therefore, aneurysmal neck clipping remains widely performed despite a recent increase in the use of coil embolization for aneurysm treatment. We report the treatment results of AchA aneurysms mostly (92.3%) treated with coil embolization at our institute. Methods: The database and medical records of patients who underwent coil embolization for AchA aneurysms were retrospectively analyzed. The clinical and imaging results and procedure-related complications were investigated after coil embolization performed between January 2006 and March 2022 at our institute. Results: In total, 96 AchA aneurysms comprising 65 unruptured and 31 ruptured aneurysms, including only 1 ruptured aneurysm (1.0%) re-embolized at postoperative day 192 because of coil compaction, were evaluated. After the initial coil embolization, complete occlusion was attained in 41, residual neck in 45, and residual aneurysm in 10 patients. Follow-up radiological studies after 6–174 months were performed for 80 aneurysms. Complete occlusion was noted in 57 patients, residual neck in 22, and residual aneurysm in 1. The dysarthria experienced by one (1.0%) patient was the only symptomatic procedure-related complication. After coil embolization, neither delayed new rupture nor re-rupture was observed. Conclusions The results of this study demonstrate that coil embolization is a safe and effective treatment option for patients with AchA aneurysms.

Background/Aims: While switching strategies of P2Y12 receptor inhibitors (RIs) have sometimes been used in acute myocardial infarction (AMI) patients, the current status of in-hospital P2Y12RI switching remains unknown. Methods: Overall, 8,476 AMI patients who underwent successful revascularization from Korea Acute Myocardial Infarction Registry-National Institute of Health (KAMIR-NIH) were divided according to in-hospital P2Y12RI strategies, and net adverse cardiovascular events (NACEs), defined as a composite of cardiac death, non-fatal myocardial infarction (MI), stroke, or thrombolysis in myocardial infarction (TIMI) major bleeding during hospitalization were compared. Results: Patients with in-hospital P2Y12RI switching accounted for 16.5%, of which 867 patients were switched from clopidogrel to potent P2Y12RI (C-P) and 532 patients from potent P2Y12RI to clopidogrel (P-C). There were no differences in NACEs among the unchanged clopidogrel, the unchanged potent P2Y12RIs, and the P2Y12RI switching groups. However, compared to the unchanged clopidogrel group, the C-P group had a higher incidence of non-fatal MI, and the P-C group had a higher incidence of TIMI major bleeding. In clinical events of in-hospital P2Y12RI switching, 90.9% of non-fatal MI occurred during pre-switching clopidogrel administration, 60.7% of TIMI major bleeding was related to pre-switching P2Y12RIs, and 71.4% of TIMI major bleeding was related to potent P2Y12RIs. Only 21.6% of the P2Y12RI switching group switched to P2Y12RIs after a loading dose (LD); however, there were no differences in clinical events between patients with and without LD. Conclusions In-hospital P2Y12RI switching occurred occasionally, but had relatively similar clinical outcomes compared to unchanged P2Y12RIs in Korean AMI patients. Non-fatal MI and bleeding appeared to be mainly related to pre-switching P2Y12RIs.

Background: As the number of large-scale studies involving multiple organizations producing data has steadily increased, an integrated system for a common interoperable format is needed. In response to the coronavirus disease 2019 (COVID-19) pandemic, a number of global efforts are underway to develop vaccines and therapeutics. We are therefore observing an explosion in the proliferation of COVID-19 data, and interoperability is highly requested in multiple institutions participating simultaneously in COVID-19 pandemic research. Results: In this study, a laboratory information management system (LIMS) approach has been adopted to systemically manage various COVID-19 non-clinical trial data, including mortality, clinical signs, body weight, body temperature, organ weights, viral titer (viral replication and viral RNA), and multiorgan histopathology, from multiple institutions based on a web interface. The main aim of the implemented system is to integrate, standardize, and organize data collected from laboratories in multiple institutes for COVID-19 non-clinical efficacy testings. Six animal biosafety level 3 institutions proved the feasibility of our system. Substantial benefits were shown by maximizing collaborative high-quality non-clinical research. Conclusions This LIMS platform can be used for future outbreaks, leading to accelerated medical product development through the systematic management of extensive data from non-clinical animal studies.