Objective: Objective of this study is to evaluate the association between high risk of depression and metabolic diseases such as hypertension, diabetes, and dyslipidemia in Korean cervical cancer patients. Methods: A total of 330 women with cervical cancer were included in this study, using data from the Korea National Health and Nutrition Examination Survey from 2010 to 2021. Participants were categorized into two groups—high risk of depression and non-depression—based on their answers to survey items related to depression. A multivariate logistic regression analysis was used to evaluate the influence of metabolic diseases on high risk of depression in patients with cervical cancer. Results: A total of 78 (23.64%) and 252 (76.36%) women were classified into the high risk of depression and non-depression groups, respectively. In multivariate logistic regression analysis adjusting for age, menopausal status, and smoking status, diabetes was associated with an odds ratio of 2.47 (95% confidence interval: 1.205, 5.071) for high risk of depression in cervical cancer patients. However, among the metabolic diseases, hypertension, and dyslipidemia were not associated with high risk of depression in patients with cervical cancer. Conclusion This study suggests that diabetes may be associated with a increased risk of high risk of depression in cervical cancer patients. Therefore, appropriate treatment of diabetes in cervical cancer patients may contribute to lowering the risk of depression in the future.

Background: Although an appropriate weight management strategy is essential for obese individuals, weight loss can have adverse effects on bone mineral density (BMD). We conducted a systematic review of randomized controlled trials to evaluate changes in BMD after the implementation of various weight loss strategies. Methods: The PubMed, Embase, Web of Science, and Cochrane Library databases were searched to find articles published from database inception until June 2023. Randomized controlled trials of various treatments for obese patients that reported changes in BMD were selected. The primary outcome was BMD of the whole body, lumbar spine, and total hip, measured using dual X-ray absorptiometry. Results: Eighteen randomized controlled trials involving 2,510 participants with obesity were included in the analysis. At follow-up examination, the BMD of the lumbar spine decreased significantly after metabolic surgery (mean difference [MD]= –0.40 g/cm2 ; 95% confidence interval [CI], –0.73 to –0.07; I2 = 0%); lifestyle and pharmacological interventions did not result in a significant decrease in BMD at any location. Metabolic surgery also produced the most substantial difference in weight, with an MD of –3.14 (95% CI, –3.82 to –2.47). Conclusion This meta-analysis is the first to examine the effects of all categories of anti-obesity strategies, including the use of anti-obesity medications, on BMD. Bariatric metabolic surgery can have adverse effects on BMD. Moreover, medications can be used as a treatment for weight loss without compromising bone quality.

Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Background: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize transplant benefits. Methods: This study retrospectively analyzed data from the Korean Network for Organ Sharing database, including 1,599 lung transplant candidates between September 2009 and December 2020. We developed the MaxBenefit LAS, combining a waitlist mortality model and a post-transplant survival model using elastic-net Cox regression, was assessed using area under the curve (AUC) values and Uno’s C-index. Its performance was compared to the US LAS in an independent cohort. Results: The waitlist mortality model showed strong predictive performance with AUC values of 0.834 and 0.818 in the training and validation cohorts, respectively. The post-transplant survival model also demonstrated good predictive ability (AUC: 0.708 and 0.685). The MaxBenefit LAS effectively stratified patients by risk, with higher scores correlating with increased waitlist mortality and decreased post-transplant mortality. The MaxBenefit LAS outperformed the conventional LAS in predicting waitlist death and identifying candidates with higher transplant benefits. Conclusion The MaxBenefit LAS offers a promising approach to optimizing lung allocation by balancing the urgency of candidates with their likelihood of survival post-transplant. This novel system has the potential to improve outcomes for lung transplant recipients and reduce waitlist mortality, providing a more equitable allocation of donor lungs.

Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings. Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals. Our analysis focused on laboratory tests that are frequently requested, excluding clinical microbiology and molecular tests. Codes from nationwide proficiency tests served as intermediary benchmarks for comparison. A research team, comprising clinical pathologists and terminology experts, utilized the LOINC manual to reach a consensus on determining the most suitable LOINC codes. Results: A total of 235 LOINC codes were designated as optimal codes for 162 frequent tests.Among these, 51 test items, including 34 urine tests, required multiple optimal LOINC codes, primarily due to unnoted properties such as whether the test was quantitative or qualitative, or differences in measurement units. We analyzed 962 LOINC codes linked to 162 tests across seven institutions, discovering that 792 (82.3%) of these codes were consistent. Inconsistencies were most common in the analyte component (38 inconsistencies, 33.3%), followed by the method (33 inconsistencies, 28.9%), and properties (13 inconsistencies, 11.4%). Conclusion This study reveals a significant inconsistency rate of over 15% in LOINC mappings utilized for research purposes in university hospitals, underlining the necessity for expert verification to enhance interoperability in real patient care.

Purpose: Claudin 18.2 (CLDN18.2) has emerged as a promising therapeutic target for CLDN18.2-expressing gastric cancer (GC). We sought to examine the heterogeneity of CLDN18.2 expression between primary GC (PGC) and metastatic GC (MGC) using various scoring methods. Materials and Methods: We retrospectively analyzed data from 102 patients with pathologically confirmed paired primary and metastatic gastric or gastroesophageal junction adenocarcinomas. CLDN18.2 expression was evaluated through immunohistochemistry on formalin-fixed paraffin-embedded tissue samples. We assessed CLDN18.2 positivity using multiple scoring approaches, including the immunoreactivity score, H-score, and the percentage of tumor cells showing moderate-to-strong staining intensity. We analyzed the concordance rates between PGC and MGC and the association of CLDN18.2 positivity with clinicopathological features. Results: CLDN18.2 positivity varied from 25% to 65% depending on the scoring method, with PGC consistently showing higher expression levels than MGC. Intratumoral heterogeneity was noted in 25.5% of PGCs and 19.6% of MGCs. Intertumoral heterogeneity, manifesting as discordance in CLDN18.2 positivity between PGC and MGC, was observed in about 20% of cases, with moderate agreement across scoring methods (κ=0.47 to 0.60).In PGC, higher CLDN18.2 positivity correlated with synchronous metastasis, presence of peritoneal metastasis, poorly differentiated grade, and biopsy specimens. In MGC, positivity was associated with synchronous metastasis, presence of peritoneal metastasis, and metastatic peritoneal tissues. Conclusions CLDN18.2 expression demonstrates significant heterogeneity between PGC and MGC, with a 20% discordance rate. Comprehensive tissue sampling and reassessment of CLDN18.2 status are crucial, especially before initiating CLDN18.2-targeted therapies.

Purpose: While colonoscopy is the standard surveillance tool for stage I colorectal cancer according to National Comprehensive Cancer Network guidelines, its effectiveness in detecting recurrence is debated. This study evaluates recurrence risk factors and patterns in stage I colorectal cancer to inform comprehensive surveillance strategies. Materials and Methods: A retrospective analysis of 2,248 stage I colorectal cancer patients who underwent radical surgery at Samsung Medical Center (2007-2018) was conducted. Exclusions were based on familial history, prior recurrences, preoperative treatments, and inadequate data. Surveillance included colonoscopy, laboratory tests, and computed tomography (CT) scans. Results: Stage I colorectal cancer patients showed favorable 5-year disease-free survival (98.3% colon, 94.6% rectum). Among a total of 1,467 colon cancer patients, 26 (1.76%) experienced recurrence. Of the 781 rectal cancer patients, 47 (6.02%) experienced recurrence. Elevated preoperative carcinoembryonic antigen levels and perineural invasion were significant recurrence risk factors in colon cancer, while tumor budding was significant in rectal cancer. Distant metastasis was the main recurrence pattern in colon cancer (92.3%), while rectal cancer showed predominantly local recurrence (50%). Colonoscopy alone detected recurrences in a small fraction of cases (3.7% in colon, 14.9% in rectum). Conclusion Although recurrence in stage I colorectal cancer is rare, relying solely on colonoscopy for surveillance may miss distant metastases or locoregional recurrence outside the colorectum. For high-risk patients, we recommend considering regular CT scans alongside colonoscopy. This targeted approach may enable earlier recurrence detection and improve outcomes in this subset while avoiding unnecessary scans for the low-risk majority.

Purpose: While colonoscopy is the standard surveillance tool for stage I colorectal cancer according to National Comprehensive Cancer Network guidelines, its effectiveness in detecting recurrence is debated. This study evaluates recurrence risk factors and patterns in stage I colorectal cancer to inform comprehensive surveillance strategies. Materials and Methods: A retrospective analysis of 2,248 stage I colorectal cancer patients who underwent radical surgery at Samsung Medical Center (2007-2018) was conducted. Exclusions were based on familial history, prior recurrences, preoperative treatments, and inadequate data. Surveillance included colonoscopy, laboratory tests, and computed tomography (CT) scans. Results: Stage I colorectal cancer patients showed favorable 5-year disease-free survival (98.3% colon, 94.6% rectum). Among a total of 1,467 colon cancer patients, 26 (1.76%) experienced recurrence. Of the 781 rectal cancer patients, 47 (6.02%) experienced recurrence. Elevated preoperative carcinoembryonic antigen levels and perineural invasion were significant recurrence risk factors in colon cancer, while tumor budding was significant in rectal cancer. Distant metastasis was the main recurrence pattern in colon cancer (92.3%), while rectal cancer showed predominantly local recurrence (50%). Colonoscopy alone detected recurrences in a small fraction of cases (3.7% in colon, 14.9% in rectum). Conclusion Although recurrence in stage I colorectal cancer is rare, relying solely on colonoscopy for surveillance may miss distant metastases or locoregional recurrence outside the colorectum. For high-risk patients, we recommend considering regular CT scans alongside colonoscopy. This targeted approach may enable earlier recurrence detection and improve outcomes in this subset while avoiding unnecessary scans for the low-risk majority.