Background: Epidermal growth factor receptor (EGFR) gene mutation testing is crucial for the administration of tyrosine kinase inhibitors to treat non–small cell lung cancer. In addition to traditional tissue-based tests, liquid biopsies using plasma are increasingly utilized, particularly for detecting T790M mutations. This study compared tissue- and plasma-based EGFR testing methods. Methods: A total of 248 patients were tested for EGFR mutations using tissue and plasma samples from 2018 to 2023 at Pusan National University Yangsan Hospital. Tissue tests were performed using PANAmutyper, and plasma tests were performed using the Cobas EGFR Mutation Test v2. Results: All 248 patients underwent tissue-based EGFR testing, and 245 (98.8%) showed positive results. Of the 408 plasma tests, 237 (58.1%) were positive. For the T790M mutation, tissue biopsies were performed 87 times in 69 patients, and 30 positive cases (38.6%) were detected. Plasma testing for the T790M mutation was conducted 333 times in 207 patients, yielding 62 positive results (18.6%). Of these, 57 (27.5%) were confirmed to have the mutation via plasma testing. Combined tissue and plasma tests for the T790M mutation were positive in nine patients (13.4%), while 17 (25.4%) were positive in tissue only and 12 (17.9%) in plasma only. This mutation was not detected in 28 patients (43.3%). Conclusions Although the tissue- and plasma-based tests showed a sensitivity of 37.3% and 32.8%, respectively, combined testing increased the detection rate to 56.7%. Thus, neither test demonstrated superiority, rather, they were complementary.

Objectives: This study was performed to evaluate the utilization patterns of acid suppressants following the withdrawal of ranitidine in Korea. Methods: Health Insurance Review & Assessment Service (HIRA) data from January 2016 to May 2023 were utilized to assess the usage of histamine H2 receptor antagonists (H2RAs) and proton pump inhibitors (PPIs) for acid-related diseases. Drug utilization was calculated for each agent based on the defined daily dose (DDD). To evaluate changes in utilization following the ranitidine recall, an interrupted time series analysis was conducted using segmented linear regression and an autoregressive integrated moving average model. Results: Before the withdrawal of ranitidine, the DDD per 100 000 inhabitants per day was increasing by 6.9 (95% confidence interval [CI], 4.7 to 9.0) for H2RAs and by 19.3 (95% CI, 16.9 to 21.8) for PPIs each month. After the recall, H2RA utilization immediately declined by -1041.7 (95% CI, -1115.8 to -967.7), followed by a monthly increase of 6.6 (95% CI, 3.7 to 9.6) above the previous trend. PPI utilization temporarily surged by 235.2 (95% CI, 149.1 to 321.3), then displayed a monthly increase of 4.1 (95% CI, 0.7 to 7.6) on top of the pre-recall trend. Among PPIs, esomeprazole and rabeprazole demonstrated notable increases, representing the most commonly used acid suppressants in 2023. Conclusions PPI usage rose prominently following the withdrawal of ranitidine from the market. Considering the potential adverse effects of PPIs, further research is necessary to evaluate the public health implications of shifts in the utilization of acid suppressants.

Background and Objectives: Inconsistencies in nasal nitric oxide (nNO) values, due to anatomical variations and comorbidities, challenge the accurate assessment of upper airway inflammation severity. We hypothesized that changes in nNO levels following treatment for chronic rhinitis would be consistent and provide relative value. This study aimed to evaluate the correlation between changes in nNO levels and symptomatic improvements following treatment for chronic rhinitis. Methods: This prospective observational study included 46 participants diagnosed with chronic rhinitis between December 2021 and November 2023. nNO measurements, evaluations of four nasal and two ocular symptoms, and quality of life questionnaires were conducted at baseline and after one month of treatment. Baseline laboratory tests included serum total immunoglobulin E levels, blood eosinophil percentages, and skin prick tests. Results: The Total Nasal Symptom Score (TNSS), TNSS with ocular symptoms (TNSS eye), and Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ) scores significantly decreased following treatment (all p<0.001). nNO levels also decreased significantly after treatment (p=0.036). Moreover, changes in nNO were significantly correlated with changes in TNSS, TNSS eye, and RQLQ scores (p=0.047, r=0.294; p=0.021, r=0.340; and p=0.004, r=0.419, respectively). Conclusion In patients with chronic rhinitis, changes in TNSS, TNSS eye, and RQLQ scores were correlated with changes in nNO levels after treatment. nNO may serve as a potential objective evaluation tool for chronic rhinitis, particularly in patients who have difficulty reporting symptoms.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: Since the World Health Organization’s pandemic declaration in March 2020, Korea has witnessed shifts in lifestyle behaviors, impacting habits tied to socioeconomic status and contributing to metabolic syndrome (MetS). To investigate this issue, the current study aimed to investigate changes in MetS prevalence, particularly based on income levels before and after the coronavirus disease 2019 (COVID-19) pandemic. Methods: This study used data from the 8th Korea National Health and Nutrition Examination Survey (2019–2020). A total of 6,840 individuals aged 30–65 years were included in this study. Household income was divided into high (≥75th percentile), middle (25–75th percentile), and low (≤25th percentile). A multivariable logistic regression analysis was performed to explore the interaction between this association before and after the COVID-19 pandemic. Results: A statistically significant difference was found in the prevalence of MetS before and after the COVID-19 pandemic (26.7% to 30.2%, P=0.001). These changes differed based on income levels. The increase in the prevalence of MetS was statistically significant in the low- and high-income groups but not in the middle-income group (low: 8.0%p increase [P=0.039], middle: 1.0%p increase [P=0.522], high: 6.4%p increase [P<0.001]). The interaction between household income and the COVID-19 pandemic on MetS was statistically significant (P for interaction=0.032). Conclusion This study revealed that P for interaction between household income, MetS, and the period before and after the COVID-19 pandemic was significant. Changes in physical activity and eating habits during the COVID-19 pandemic may have contributed to these differences.

Background: The prognosis of end-of-life patients is challenging, and clinicians have attempted to predict survival more accurately. High serum creatinine (sCr) levels are associated with lower survival rates in patients with various cancers; however, low sCr levels are commonly expected in patients with terminal cancer because of muscle wasting and malnutrition. Therefore, we investigated the prevalence of low and high sCr levels and their association with survival duration in patients with terminal cancer in a palliative care unit. Methods: We analyzed the medical records of 280 patients admitted to a palliative care unit. Patients were divided into low (<0.5 mg/dL), normal (0.5–1.2 mg/dL), and high (>1.2 mg/dL) sCr groups. Kaplan-Meier survival curves using sCr levels were plotted and compared using the log-rank test. Using stepwise selection, a multivariable Cox proportional hazards model was used to identify the significant prognostic factors. Results: The median survival durations in the high-, low-, and normal-sCr groups were 9.57 days, 22.26 days, and 27.51 days, respectively. Multivariable Cox proportional hazard model identified that males (hazard ratio [HR], 1.81; 95% confidence interval [CI], 1.16–2.85), poor performance status (HR, 3.43; 95% CI, 1.12–10.54), total parenteral nutrition use (HR, 1.84; 95% CI, 1.09–3.1), high sCr (HR, 2.74; 95% CI, 1.52–4.94), and low sCr (HR, 1.22; 95% CI, 1.07–1.43) were significantly associated with a shorter survival time. Conclusion Low and high serum creatinine levels were significantly associated with poor survival in patients with cancer at the end-of-life stage. Therefore, readily available and simple biomarkers may help plan advanced care in palliative care settings.

Purpose: With the accelerated adoption of artificial intelligence (AI) in medicine, the integration of AI education into medical school curricula is gaining significant attention. This study aimed to gather the perceptions of faculty members and students regarding the integration of AI education into medical curricula in the Korean context. Methods: Faculty members and medical students’ perspectives on integrating AI into medical curricula were assessed through thematic analysis of free-written responses from 157 faculty members and 125 students in a national online survey on medical AI competencies in South Korea. Results: Three key themes emerged: content, which prioritizes basic knowledge and its practical applications, with an emphasis on ethical and legal responsibilities; curricular design, which advocates for a spiral curriculum tailored to learners' needs; and concerns, which highlight balancing AI integration with the principal goals of medical education while critically evaluating ongoing advancements. Conclusion Our study adds valuable insights into the content and methods to prioritize AI education. Given the rapid evolution of medical learners and AI technologies, continuous and timely needs assessment for AI curriculum development is crucial to maintain relevance and effectiveness.

Objectives: Assessing medical disputes requires both medical and legal expertise, presenting challenges for patients seeking clarity regarding potential malpractice claims. This study aimed to develop and evaluate a chatbot based on a chain-of-thought pipeline using a large language model (LLM) for providing medical dispute counseling and compare its performance with responses from human experts. Methods: Retrospective counseling cases (n = 279) were collected from the Korea Medical Dispute Mediation and Arbitration Agency’s website, from which 50 cases were randomly selected as a validation dataset. The Claude 3.5 Sonnet model processed each counseling request through a five-step chain-of-thought pipeline. Thirty-eight experts evaluated the chatbot’s responses against the original human expert responses, rating them across four dimensions on a 5-point Likert scale. Statistical analyses were conducted using Wilcoxon signed-rank tests. Results: The chatbot significantly outperformed human experts in quality of information (p < 0.001), understanding and reasoning (p < 0.001), and overall satisfaction (p < 0.001). It also demonstrated a stronger tendency to produce opinion-driven content (p < 0.001). Despite generally high scores, evaluators noted specific instances where the chatbot encountered difficulties. Conclusions A chain-of-thought–based LLM chatbot shows promise for enhancing the quality of medical dispute counseling, outperforming human experts across key evaluation metrics. Future research should address inaccuracies resulting from legal and contextual variability, investigate patient acceptance, and further refine the chatbot’s performance in domain-specific applications.