Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Background: Bulky or multiple lymph node (LN) metastases are associated with poor prognosis in cervical cancer, and the size or number of LN metastases is not yet reflected in the staging system and therapeutic strategy. Although the therapeutic effects of surgical resection of bulky LNs before standard treatment have been reported in several retrospective studies, wellplanned randomized clinical studies are lacking. Therefore, the aim of the Korean Gynecologic Oncology Group (KGOG) 1047/DEBULK trial is to investigate whether the debulking surgery of bulky or multiple LNs prior to concurrent chemoradiation therapy (CCRT) improves the survival rate of patients with cervical cancer IIICr diagnosed by imaging tests. Methods The KGOG 1047/DEBULK trial is a phase III, multicenter, randomized clinical trial involving patients with bulky or multiple LN metastases in cervical cancer IIICr. This study will include patients with a short-axis diameter of a pelvic or para-aortic LN ≥2 cm or ≥3 LNs with a short-axis diameter ≥1 cm and for whom CCRT is planned. The treatment arms will be randomly allocated in a 1:1 ratio to either receive CCRT (control arm) or undergo surgical debulking of bulky or multiple LNs before CCRT (experimental arm). CCRT consists of extended-field external beam radiotherapy/pelvic radiotherapy, brachytherapy and LN boost, and weekly chemotherapy with cisplatin (40 mg/m 2 ), 4–6 times administered intravenously.The primary endpoint will be 3-year progression-free survival rate. The secondary endpoints will be 3-year overall survival rate, treatment-related complications, and accuracy of radiological diagnosis of bulky or multiple LNs.

Objectives: Sepsis is a leading global cause of mortality, and predicting its outcomes is vital for improving patient care. This study explored the capabilities of ChatGPT, a state-of-the-art natural language processing model, in predicting in-hospital mortality for sepsis patients. Methods: This study utilized data from the Korean Sepsis Alliance (KSA) database, collected between 2019 and 2021, focusing on adult intensive care unit (ICU) patients and aiming to determine whether ChatGPT could predict all-cause mortality after ICU admission at 7 and 30 days. Structured prompts enabled ChatGPT to engage in in-context learning, with the number of patient examples varying from zero to six. The predictive capabilities of ChatGPT-3.5-turbo and ChatGPT-4 were then compared against a gradient boosting model (GBM) using various performance metrics. Results: From the KSA database, 4,786 patients formed the 7-day mortality prediction dataset, of whom 718 died, and 4,025 patients formed the 30-day dataset, with 1,368 deaths. Age and clinical markers (e.g., Sequential Organ Failure Assessment score and lactic acid levels) showed significant differences between survivors and non-survivors in both datasets. For 7-day mortality predictions, the area under the receiver operating characteristic curve (AUROC) was 0.70–0.83 for GPT-4, 0.51–0.70 for GPT-3.5, and 0.79 for GBM. The AUROC for 30-day mortality was 0.51–0.59 for GPT-4, 0.47–0.57 for GPT-3.5, and 0.76 for GBM. Zero-shot predictions using GPT-4 for mortality from ICU admission to day 30 showed AUROCs from the mid-0.60s to 0.75 for GPT-4 and mainly from 0.47 to 0.63 for GPT-3.5. Conclusions GPT-4 demonstrated potential in predicting short-term in-hospital mortality, although its performance varied across different evaluation metrics.

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.

Background: Prolonged length of hospital stay (LOS) is associated with an increased risk of hospital-acquired conditions and worse outcomes. We conducted a nationwide, multicenter, retrospective cohort study to determine whether prolonged hospitalization before developing sepsis has a negative impact on its prognosis. Methods: We analyzed data from 19 tertiary referral or university-affiliated hospitals between September 2019 and December 2020. Adult patients with confirmed sepsis during hospitalization were included. In-hospital mortality was the primary outcome. The patients were divided into two groups according to their LOS before the diagnosis of sepsis: early- (< 5 days) and late-onset groups (≥ 5 days). Conditional multivariable logistic regression for propensity score matched-pair analysis was employed to assess the association between lateonset sepsis and the primary outcome. Results: A total of 1,395 patients were included (median age, 68.0 years; women, 36.3%).The early- and late-onset sepsis groups comprised 668 (47.9%) and 727 (52.1%) patients.Propensity score-matched analysis showed an increased risk of in-hospital mortality in the late-onset group (adjusted odds ratio [aOR], 3.00; 95% confidence interval [CI], 1.69–5.34).The same trend was observed in the entire study population (aOR, 1.85; 95% CI, 1.37–2.50).When patients were divided into LOS quartile groups, an increasing trend of mortality risk was observed in the higher quartiles (Pfor trend < 0.001). Conclusion Extended LOS before developing sepsis is associated with higher in-hospital mortality. More careful management is required when sepsis occurs in patients hospitalized for ≥ 5 days.

Purpose: In the present study, we determined the prevalence of obstructive meibomian gland dysfunction (MGD), hyposecretory MGD, grossly normal MG, and hypersecretory MGD in patients with dry eye syndrome using lipid layer thickness (LLT) and MG dropout. Methods: Eighty-eight patients with dry eye syndrome were included in the study. Patients were categorized into four groups according to the LLT and weighted total meiboscore. The proportion of patients in each group was calculated. The age, sex, Ocular Surface Disease Index, LLT, Schirmer, tear film breakup time, cornea stain, weighted total meiboscore, expressibility, and quality of meibum were compared between the four groups. Results: Fifteen eyes (17.0%) had obstructive MGD, two eyes (2.3%) had hyposecretory MGD, 40 eyes (45.5%) had grossly normal MG, and 17 eyes (19.3%) had hypersecretory MGD. The obstructive MGD group was younger than the grossly normal MG group. In obstructive MGD, the ratio of men to women was higher than that of the other groups. However, Ocular Surface Disease Index, Schirmer, tear film breakup time, and corneal stain did not show statistically significant differences between the four groups. The meibum expressibility of the hyposecretoy MGD group was worse than those of the other groups. The meibum expressibility of the hyposecretoy MGD group was poor than those of the obstructive and hypersecretory MGD group. Conclusions This categorization was expected to help determine the best treatment method for dry eye syndrome, according to the MG status.

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a pivotal enzyme in the Toll-like receptor (TLR)/MYD88 dependent signaling pathway, which is highly activated in rheumatoid arthritis tissues and activated B cell-like diffuse large B-cell lymphoma (ABC-DLBCL). Inflammatory responses followed by IRAK4 activation promote B-cell proliferation and aggressiveness of lymphoma. Moreover, proviral integration site for Moloney murine leukemia virus 1 (PIM1) functions as an anti-apoptotic kinase in propagation of ABC-DLBCL with ibrutinib resistance. We developed a dual IRAK4/PIM1 inhibitor KIC-0101 that potently suppresses the NF-κB pathway and proinflammatory cytokine induction in vitro and in vivo. In rheumatoid arthritis mouse models, treatment with KIC-0101 significantly ameliorated cartilage damage and inflammation. KIC-0101 inhibited the nuclear translocation of NF-κB and activation of JAK/STAT pathway in ABC-DLBCLs. In addition, KIC-0101 exhibited an anti-tumor effect on ibrutinib-resistant cells by synergistic dual suppression of TLR/MYD88-mediated NF-κB pathway and PIM1 kinase. Our results suggest that KIC-0101 is a promising drug candidate for autoimmune diseases and ibrutinib-resistant B-cell lymphomas.

Background: Administration of adequate antibiotics is crucial for better outcomes in sepsis. Because no uniform tool can accurately assess the risk of multidrug-resistant (MDR) pathogens, a local antibiogram is necessary. We aimed to describe the antibiogram of MDR bacteria based on locations of sepsis onset in South Korea. Methods: We performed a prospective observational study of adult patients diagnosed with sepsis according to Sepsis-3 from 19 institutions (13 tertiary referral and 6 universityaffiliated general hospitals) in South Korea. Patients were divided into four groups based on the respective location of sepsis onset: community, nursing home, long-term-care hospital, and hospital. Along with the antibiogram, risk factors of MDR bacteria and drug-bug match of empirical antibiotics were analyzed. Results: MDR bacteria were detected in 1,596 (22.7%) of 7,024 patients with gram-negative predominance. MDR gram-negative bacteria were more commonly detected in long-termcare hospital- (30.4%) and nursing home-acquired (26.3%) sepsis, whereas MDR grampositive bacteria were more prevalent in hospital-acquired (10.9%) sepsis. Such findings were consistent regardless of the location and tier of hospitals throughout South Korea. Patients with long-term-care hospital-acquired sepsis had the highest risk of MDR pathogen, which was even higher than those with hospital-acquired sepsis (adjusted odds ratio, 1.42; 95% confidence interval, 1.15–1.75) after adjustment of risk factors. The drug-bug match was lowest in patients with long-term-care hospital-acquired sepsis (66.8%). Conclusion Gram-negative MDR bacteria were more common in nursing home- and long-term-care hospital-acquired sepsis, whereas gram-positive MDR bacteria were more common in hospital-acquired settings in South Korea. Patients with long-term-care hospitalacquired sepsis had the highest the risk of MDR bacteria but lowest drug-bug match of initial antibiotics. We suggest that initial antibiotics be carefully selected according to the onset location in each patient.

Background: CycloZ, a combination of cyclo-His-Pro and zinc, has anti-diabetic activity. However, its exact mode of action remains to be elucidated. Methods: KK-Ay mice, a type 2 diabetes mellitus (T2DM) model, were administered CycloZ either as a preventive intervention, or as a therapy. Glycemic control was evaluated using the oral glucose tolerance test (OGTT), and glycosylated hemoglobin (HbA1c) levels. Liver and visceral adipose tissues (VATs) were used for histological evaluation, gene expression analysis, and protein expression analysis. Results: CycloZ administration improved glycemic control in KK-Ay mice in both prophylactic and therapeutic studies. Lysine acetylation of peroxisome proliferator-activated receptor gamma coactivator 1-alpha, liver kinase B1, and nuclear factor-κB p65 was decreased in the liver and VATs in CycloZ-treated mice. In addition, CycloZ treatment improved mitochondrial function, lipid oxidation, and inflammation in the liver and VATs of mice. CycloZ treatment also increased the level of β-nicotinamide adenine dinucleotide (NAD+), which affected the activity of deacetylases, such as sirtuin 1 (Sirt1). Conclusion Our findings suggest that the beneficial effects of CycloZ on diabetes and obesity occur through increased NAD+ synthesis, which modulates Sirt1 deacetylase activity in the liver and VATs. Given that the mode of action of an NAD+ booster or Sirt1 deacetylase activator is different from that of traditional T2DM drugs, CycloZ would be considered a novel therapeutic option for the treatment of T2DM.