Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Purpose: Identifying and managing risk factors for lower urinary tract symptoms (LUTS) is crucial because it impacts the quality of life of elderly individuals. Lifestyle factors, including physical activity (PA), and their relationship with LUTS have not been well studied. This objective of this study was to investigate the association between PA and LUTS. Materials and Methods: A total of 7,296 men were included in this cross-sectional study. PA was quantified in metabolic equivalent (MET)-hours per week, and LUTS severity was assessed using the international prostate symptom score. Logistic regression was used to analyze the association between PA and LUTS, including voiding and storage symptoms. Results: The average age of the participants was 57.8 years, and the prevalence of LUTS was 41.3%. After adjusting for potential confounders, PA was inversely associated with the prevalence and severity of moderate-to-severe LUTS, showing a dose-response pattern (all p for trend <0.01). Compared to the minimal activity group, which engaged in <5 MET-hours per week of PA, the odds ratios for moderate to severe LUTS were 0.83 (95% confidence interval [CI]: 0.72–0.97) for men engaging in 15–30 MET-hours per week, 0.82 (95% CI: 0.71–0.95) for 30–60 MET-hours per week, and 0.72 (95% CI: 0.62–0.84) for ≥60 MET-hours per week. The possible protective effect of PA was still observed in the additional analysis for voiding and storage symptoms showing the same dose-response pattern (all p for trend <0.01). Conclusions A higher PA level was associated with a lower prevalence and severity of total, voiding, and storage LUTS in a dose-dependent manner in Korean men.

Background: Respiratory infections play a major role in acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study assessed the prevalence of bacterial and viral pathogens and their clinical impact on patients with AECOPD. Methods: This retrospective study included 1,186 patients diagnosed with AECOPD at 28 hospitals in South Korea between 2015 and 2018. We evaluated the identification rates of pathogens, basic patient characteristics, clinical features, and the factors associated with infections by potentially drug-resistant (PDR) pathogens using various microbiological tests. Results: Bacteria, viruses, and both were detected in 262 (22.1%), 265 (22.5%), and 129 (10.9%) of patients, respectively. The most common pathogens included Pseudomonas aeruginosa (17.8%), Mycoplasma pneumoniae (11.2%), Streptococcus pneumoniae (9.0%), influenza A virus (19.0%), rhinovirus (15.8%), and respiratory syncytial virus (6.4%). Notably, a history of pulmonary tuberculosis (odds ratio [OR], 1.66; p=0.046), bronchiectasis (OR, 1.99; p=0.032), and the use of a triple inhaler regimen within the past 6 months (OR, 2.04; p=0.005) were identified as significant factors associated with infection by PDR pathogens. Moreover, patients infected with PDR pathogens exhibited extended hospital stays (15.9 days vs. 12.4 days, p=0.018) and higher intensive care unit admission rates (15.9% vs. 9.5%, p=0.030). Conclusion This study demonstrates that a variety of pathogens are involved in episodes of AECOPD. Nevertheless, additional research is required to confirm their role in the onset and progression of AECOPD.

Background: Kelch-like ECH-associated protein 1 (KEAP1)–nuclear factor erythroid- 2-related factor 2 (NRF2) pathway is a major regulator protecting cells from oxidative and metabolic stress. Studies have revealed that this pathway is involved in mediating resistance to cytotoxic chemotherapy and immunotherapy; however, its implications in oncogene-addicted tumors are largely unknown. This study aimed to elucidate whether this pathway could be a potential therapeutic target for epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer. Methods: We measured the baseline expression of NRF2 using EGFR-mutant parental cells and acquired gefitinib resistant cells. We investigated whether NRF2 inhibition affected cell death in vitro and tumor growth in vivo using a xenograft mouse model, and compared the transcriptional changes before and after NRF2 inhibition. Results: Baseline NRF2 expression was enhanced in PC9 and PC9 with gefitinib resistance (PC9/GR) cells than in other cell lines, with a more prominent expression in PC9/ GR. The NRF2 inhibitor induced NRF2 downregulation and cell death in a dose-dependent manner. Cotreatment with an NRF2 inhibitor enhanced osimertinib-induced cell death in vitro, and potentiated tumor growth inhibition in a PC9/GR xenograft model. Finally, RNA sequencing revealed that NRF2 inhibition resulted in the altered expression of multiple genes involved in various signaling pathways. Conclusion We identified that NRF2 inhibition enhanced cell death and inhibited tumor growth in tyrosine kinase inhibitor (TKI)-resistant lung cancer with EGFR-mutation. Thus, NRF2 modulation may be a novel therapeutic strategy to overcome the resistance to EGFR-TKIs.

Purpose: Ultrasound-guided nerve hydrodissection has emerged as a potential non-surgical treatment for carpal tunnel syndrome (CTS). The objective of this research was to offer suggestions for optimizing injectables utilized in hydrodissection for the treatment of CTS through a systematic review and network meta-analysis. Materials and Methods: PubMed, MEDLINE, EMBASE, Cochrane, Scopus, and Web of Science were searched through April 25, 2024. Effect sizes were quantified using standard mean differences within a random-effects model. Effectiveness ranking for each treatment was expressed as the surface under the cumulative ranking curve (SUCRA). Results: Nine studies with 458 patients with CTS were included. According to SUCRA, 5% dextrose (DW) was the most effective option for the Boston Carpal Tunnel Questionnaire (BCTQ) function at 99.9, 89.8, and 88.8 at 4, 12, and 24 weeks, respectively; for BCTQ symptoms, 5% DW was the most effective option at 99.9 at 4 weeks and platelet-rich plasma at 95.7 and 93.9 at 12 and 24 weeks, respectively. In terms of both BCTQ symptoms and BCTQ function, the 5 cc injection was the most effective, with SUCRA values of 99.5 for both categories. However, the effectiveness of the electrodiagnostic assessment and ultrasound variables was dependent on the type and dose of medication. Conclusion Administration of 5% DW showed better results in terms of initial symptom relief and long-term functional recovery compared to other agents, while platelet-rich plasma showed greater long-term symptom improvement; an injection dose of 5 cc showed the greatest benefit. However, additional research is required to establish precise protocols based on disease severity.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.

The initial molecular cytogenetic characteristics of blasts plays a significant role in determining the treatment course of B-cell acute lymphoblastic leukemia (B-ALL).B-ALL with intrachromosomal amplification of chromosome 21 (iAMP21) has been well known to have unfavorable prognosis. Also, there are previously recognized germline mutations that increase the risk of ALL, such as trisomy 21, Down syndrome. This case report is about a 16-year-old girl who presented with lymphadenitis, purpura, and fever followed by initial lab of elevated white blood cell with blasts.She had some notable facial features, but no typical Down syndrome related one.Bone marrow biopsy and fluorescence in situ hybridization finalized the diagnosis as B-ALL with iAMP21, high-risk group. The minimal residual disease-negative complete remission was achieved after the induction chemotherapy with Korean multicenter high-risk protocol. However, abnormal karyotype was sustained in bone marrow. Microarrays with her buccal swab raised the possibility that the abnormal karyotype was not from the leukemic blasts but rather from the germline. Although she underwent scheduled chemotherapy uneventfully as slow early responder type, thrombocytopenia and abnormal karyotype persisted, leading to the diagnosis of acute myeloid leukemia. Additional chemotherapy and peripheral blood stem cell transplantation was performed which resulted in engraftment. This case highlights the discovery of a constitutional genetic aberration, which played like a silent yet critical background factor for B-ALL with iAMP21. As the number of reported cases are limited, the role of germline chromosome 21 mutation as the indicator for prognosis of B-ALL should be studied further.

Background: Sarcopenia, a multifactorial disorder involving metabolic disturbance, suggests potential for metabolite biomarkers. Carnitine (CN), essential for skeletal muscle energy metabolism, may be a candidate biomarker. We investigated whether CN metabolites are biomarkers for sarcopenia. Methods: Associations between the CN metabolites identified from an animal model of sarcopenia and muscle cells and sarcopenia status were evaluated in men from an age-matched discovery (72 cases, 72 controls) and a validation (21 cases, 47 controls) cohort. Results: An association between CN metabolites and sarcopenia showed in mouse and cell studies. In the discovery cohort, plasma C5-CN levels were lower in sarcopenic men (P=0.005). C5-CN levels in men tended to be associated with handgrip strength (HGS) (P=0.098) and were significantly associated with skeletal muscle mass (P=0.003). Each standard deviation increase in C5-CN levels reduced the odds of low muscle mass (odd ratio, 0.61; 95% confidence interval [CI], 0.42 to 0.89). The area under the receiver operating characteristic curve (AUROC) of CN score using a regression equation of C5-CN levels, for sarcopenia was 0.635 (95% CI, 0.544 to 0.726). In the discovery cohort, addition of CN score to HGS significantly improved AUROC from 0.646 (95% CI, 0.575 to 0.717; HGS only) to 0.727 (95% CI, 0.643 to 0.810; P=0.006; HGS+CN score). The improvement was confirmed in the validation cohort (AUROC=0.563; 95% CI, 0.470 to 0.656 for HGS; and AUROC=0.712; 95% CI, 0.569 to 0.855 for HGS+CN score; P=0.027). Conclusion C5-CN, indicative of low muscle mass, is a potential circulating biomarker for sarcopenia in men. Further studies are required to confirm these results and explore sarcopenia-related metabolomic changes.

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.

Objective: To test the performance of an artificial intelligence-based computer-aided diagnosis (AI-CAD) designed for fullfield digital mammography (FFDM) when applied to synthetic mammography (SM). Materials and Methods: We analyzed 501 women (mean age, 57 ± 11 years) who underwent preoperative mammography and breast cancer surgery. This cohort consisted of 1002 breasts, comprising 517 with cancer and 485 without. All patients underwent digital breast tomosynthesis (DBT) and FFDM during the preoperative workup. The SM is routinely reconstructed using DBT. Commercial AI-CAD (Lunit Insight MMG, version 1.1.7.2) was retrospectively applied to SM and FFDM to calculate the abnormality scores for each breast. The median abnormality scores were compared for the 517 breasts with cancer using the Wilcoxon signed-rank test. Calibration curves of abnormality scores were evaluated. The discrimination performance was analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 10% preset threshold. Sensitivity and specificity were further analyzed according to the mammographic and pathological characteristics.The results of SM and FFDM were compared. Results: AI-CAD demonstrated a significantly lower median abnormality score (71% vs. 96%, P < 0.001) and poorer calibration performance for SM than for FFDM. SM exhibited lower sensitivity (76.2% vs. 82.8%, P < 0.001), higher specificity (95.5% vs.91.8%, P < 0.001), and comparable AUC (0.86 vs. 0.87, P = 0.127) than FFDM. SM showed lower sensitivity than FFDM in asymptomatic breasts, dense breasts, ductal carcinoma in situ, T1, N0, and hormone receptor-positive/human epidermal growth factor receptor 2-negative cancers but showed higher specificity in non-cancerous dense breasts. Conclusion AI-CAD showed lower abnormality scores and reduced calibration performance for SM than for FFDM.Furthermore, the 10% preset threshold resulted in different discrimination performances for the SM. Given these limitations, off-label application of the current AI-CAD to SM should be avoided.