This study aimed to investigate changes in candidemia incidence, species distribution, antifungal susceptibility, initial antifungal use, and mortality trends in Korea before and during the COVID-19 pandemic. A retrospective analysis was conducted on candidemia cases from two tertiary care hospitals in Korea between 2017 and 2022. Data were compared between the pre-pandemic (2017-2019) and pandemic (2020-2022) periods. Statistical methods included incidence rate ratios (IRRs) and multivariate Cox regression to assess 30-day mortality risk factors. A total of 470 candidemia cases were identified, with 48.7% occurring pre-pandemic and 51.3% during the pandemic. While the overall incidence of candidemia remained similar across the two periods (IRR 1.15;p=0.13), the incidence in intensive care units (ICUs) significantly increased during the pandemic (IRR 1.50; p<0.01). The distribution of Candida species did not differ significantly between the two periods. Fluconazole non-susceptibility in C. albicans markedly decreased (10.0% vs. 0.9%, p<0.01), whereas C. glabrata exhibited a significant rise in caspofungin non-susceptibility during the pandemic (0% vs. 22.4%, p<0.01).Echinocandin use increased (21.8% vs. 34.4%; p<0.01), while fluconazole use declined (48.0% vs. 32.8%; p<0.01). Although the 30-day mortality rate was higher during the pandemic (60.2% vs. 57.2%), the difference was not statistically significant (p=0.57).The findings highlight the need for region-specific surveillance and tailored management strategies to improve candidemia outcomes, especially during healthcare disruptions like the COVID-19 pandemic.

Axial spondyloarthritis (axSpA) is a chronic inflammatory disorder affecting the sacroiliac joints and axial spine. Along with pharmacotherapy, non-pharmacological interventions for axSpA are crucial and constitute the cornerstone of treatment. Here, we review the evidence for non-pharmacological treatment of axSpA as a basis for the 2023 Korean treatment recommendations for patients with axSpA. The effectiveness of the core non-pharmacological approaches, such as education, smoking cessation, and exercise, has been reaffirmed. High-quality research on surgical treatment is limited. However, total hip replacement is advised in patients with ongoing pain or disability and visible structural damage to the hip on imaging. Urgent spinal intervention should be considered in cases of acute spinal pain with neurological deficiency or concurrent unstable fractures. Evidence for complementary therapies, including spas and acupuncture, remains insufficient.

Purpose: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

This guideline outlines the use of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the diagnosis and management of infectious and inflammatory diseases. It provides detailed recommendations for healthcare providers on patient preparation, imaging procedures, and the interpretation of results. Adapted from international standards and tailored to local clinical practices, the guideline emphasizes safety, quality control, and effective use of the technology in various conditions, including spinal infections, diabetic foot, osteomyelitis, vasculitis, and cardiac inflammation. The aim is to assist nuclear medicine professionals in delivering accurate diagnoses and improving patient outcomes while allowing flexibility to adapt to individual patient needs, technological advancements, and evolving medical knowledge. This document is a comprehensive resource for enhancing the quality and safety of 18F-fluoro-2-deoxyglucose positron emission tomography / computed tomography for the evaluation of infectious and inflammatory diseases.Preamble The Korean Society of Nuclear Medicine (KSNM) was established in 1961 to promote the clinical and technological advancement of nuclear medicine in South Korea, with members that include nuclear medicine physicians and associated scientists. The KSNM regularly formulates and revises procedural guidelines for nuclear medicine examinations to enhance the field and improve the quality of patient care. These guidelines are designed to support healthcare professionals in providing appropriate medical care to patients. However, they are not immutable rules or mandatory requirements for conducting examinations.Therefore, KSNM states that these guidelines should not be used in legal actions challenging a healthcare professional’s medical decisions. The ultimate judgment regarding specific procedures or appropriate measures should be made by nuclear medicine physicians, considering the unique circumstances of each case. Deviation from these guidelines does not imply substandard medical practice. Rather, reasonable judgments differing from the guidelines can be made based on the patient’s condition, available resources, and advancements in knowledge or technology. Due to the diversity and complexity of patients, it is often challenging to predict the most appropriate diagnostic and accurate therapeutic responses. Thus, adherence to these guidelines does not always guarantee an exact diagnosis or successful outcomes.The purpose of this guideline is to assist healthcare providers in making reasonable decisions and conducting effective and safe examinations based on current medical knowledge, available resources, and patient needs when performing 18F-fluoro-2-deoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT) examinations for infectious/ inflammatory diseases.

Objective: To analyze the microbiological and clinical characteristics of vulvovaginitis in girls, distinguishing between the premenarcheal and postmenarcheal groups in a tertiary center in South Korea. Methods: This retrospective cohort study included 195 patients under 20 years of age diagnosed with vulvovaginitis at a tertiary hospital between 2014 and 2023. The patients were categorized into premenarcheal (n=95) and postmenarcheal (n=100) groups. Data on initial symptoms, microbial cultures, and treatment methods were analyzed. Results: The most common initial symptom was vaginal discharge, reported in 63.1% of cases. Culture results showed a 51.3% positivity rate for any microorganism, with a prevalence of gram-negative rods (32.8%) and gram-positive cocci (14.4%). The most frequently isolated microorganisms were Escherichia coli (17.9%), Candida albicans (7.7%), and Enterococcus faecalis (6.7%). Gram-negative rods were more common in the premenarcheal group (37.1% vs. 25.0%; p=0.01). No significant differences were observed in the prevalence of gram-positive cocci and Candida species between the two groups (16.8% vs. 12.0%, p=0.22; 6.3% vs. 13.0%, p=0.09; respectively). The susceptibilities of grampositive microorganisms to penicillin, oxacillin, clindamycin, vancomycin, and tetracycline were 58.8%, 58.3%, 94.7%, 100.0%, and 73.7%, respectively. The susceptibilities of gram-negative microorganisms to amoxicillin/clavulanic acid, ciprofloxacin, ceftriaxone, and nitrofurantoin were 89.3%, 85.3%, 76.0%, and 100.0%, respectively. Conclusion This study identified differences in the microbial profiles associated with vulvovaginitis between premenarcheal and postmenarcheal girls. Age-specific and history-based clinical approaches tailored to menarcheal status are warranted to improve the management and outcomes of pediatric and adolescent vulvovaginitis.

Axial spondyloarthritis (axSpA) is a chronic inflammatory disorder affecting the sacroiliac joints and axial spine. Along with pharmacotherapy, non-pharmacological interventions for axSpA are crucial and constitute the cornerstone of treatment. Here, we review the evidence for non-pharmacological treatment of axSpA as a basis for the 2023 Korean treatment recommendations for patients with axSpA. The effectiveness of the core non-pharmacological approaches, such as education, smoking cessation, and exercise, has been reaffirmed. High-quality research on surgical treatment is limited. However, total hip replacement is advised in patients with ongoing pain or disability and visible structural damage to the hip on imaging. Urgent spinal intervention should be considered in cases of acute spinal pain with neurological deficiency or concurrent unstable fractures. Evidence for complementary therapies, including spas and acupuncture, remains insufficient.

Purpose: The study investigated whether incorporating magnetic resonance imaging (MRI) alongside ultrasonography (US) in the preoperative evaluation is associated with differing survival outcomes between male and female breast cancer patients in a matched analysis. Additionally, clinicopathological prognostic factors were analyzed. Methods: Between January 2005 and December 2020, 93 male and 28,191 female patients who underwent breast surgery were screened. Exact matching analysis was conducted for age, pathologic T and N stages, and molecular subtypes. The clinicopathological characteristics and preoperative imaging methods of the matched cohorts were reviewed. Disease-free survival (DFS) and overall survival (OS) were assessed using Kaplan-Meier analysis, and Cox proportional hazards regression analysis was used to identify prognostic factors. Results: A total of 328 breast cancer patients (61 men and 267 women) were included in the matched analysis. Male patients had worse DFS (10-year DFS, 70.6% vs. 89.2%; P=0.001) and OS (10-year OS, 64.4% vs. 96.3%; P<0.001) than female patients. The pathologic index cancer size (hazard ratio [HR], 2.013; 95% confidence interval [CI], 1.063 to 3.810; P=0.032) was associated with worse DFS, whereas there were no significant factors associated with OS. Adding MRI to US for preoperative evaluation was not associated with DFS (HR, 1.117; 95% CI, 0.223 to 5.583; P=0.893) or OS (HR, 1.529; 95% CI, 0.300 to 7.781; P=0.609) in male patients. Conclusion Adding breast MRI to US in the preoperative evaluation was not associated with survival outcomes in male breast cancer patients, and the pathologic index cancer size was associated with worse DFS.

Purpose: Early identification of patients at risk for acute respiratory failure (ARF) could help clinicians devise preventive strategies. Analyzing biosignals with artificial intelligence (AI) can uncover hidden information and variability within time series. We aimed to develop and validate AI models to predict ARF within 72 h after emergency department admission, primarily using highresolution biosignals collected within 4 h of arrival. Materials and Methods: Our AI model, built on convolutional recurrent neural networks, combines biosignal feature extraction and sequence modeling. The model was developed and internally validated with data from 5284 admissions [1085 (20.5%) positive for ARF], and externally validated using data from 144 admissions [7 (4.9%) positive for ARF] from another institution. We defined ARF as the application of advanced respiratory support devices. Results: Our AI model performed well in predicting ARF, achieving area under the receiver operating characteristic curve (AUROC) of 0.840 and 0.743 in internal and external validations, respectively. It outperformed the Modified Early Warning Score (MEWS) and XGBoost models built only with clinical variables. High predictive ability for mortality was observed, with AUROC up to 0.809. A 10% increase in AI prediction scores was associated with 1.44-fold and 1.42-fold increases in ARF risk and mortality risk, respectively, even after adjusting for MEWS and demographic variables. Conclusion Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.

Purpose: This study aimed to evaluate the impact of declining surgical residency program enrollment on patient care and outcomes in colorectal cancer surgeries. Methods: This retrospective observational study included 676 patients (410 males; median age: 69 years) who underwent colorectal cancer surgery at Pusan National University Hospital between January 2018 and June 2024. Patients were divided into Group A (before December 31, 2023; with residents) and Group B (after January 1, 2024; without residents). All surgeries were performed by a single attending surgeon. Results: Preoperative variables were comparable between groups. Group A had more emergency and open surgeries, and a higher proportion of advanced-stage cancers. Overall complication rates were similar, but Group B had a longer hospital stay (9.72 days vs. 11.95 days). Specific complications such as anastomotic leakage and surgical site infections differed significantly. The overall number of surgical procedures declined markedly in 2024 compared to 2018 (77.1% vs. 49.9%). Conclusion The absence of residents did not increase overall complication rates but was associated with longer hospital stays and shifts in clinical practice. Greater reliance on attending surgeons contributed to more defensive decision-making and conservative patient management. Addressing these issues requires systemic reforms, including multidisciplinary collaboration and legal protections to improve surgical care.