Objective: Using a nationally representative cohort of medical claims data in Korea, this study aimed to analyze the association between the use of various anti-rheumatic agents and the risk of acute myocardial infarction (AMI) in patients with rheumatoid arthritis (RA). Methods: This nested case-control study used the Korean Health Insurance Review and Assessment data of 35,133 patients newly diagnosed with RA between 2011 and 2020. Incident AMI patients were identified and matched at a 1:4 ratio with randomly selected controls. The usage of anti-rheumatic agents was measured from the date of RA diagnosis to the index date and stratified based on exposure time and duration. The risk of AMI associated with each anti-rheumatic agent was estimated using conditional logistic regression, adjusted for comorbidities and concomitant drug use. Results: Of the 35,133 patients with RA, 484 were diagnosed with AMI. In total, 484 AMI patients and 1,924 controls with newly diagnosed RA were included in the analysis. Current exposure and long-term exposure to glucocorticoids (adjusted odds ratio [aOR]: 2.301, 95% confidence interval [CI]: 1.741~3.041; aOR: 1.792, 95% CI: 1.378~2.330) and leflunomide (aOR: 1.525, 95% CI: 1.196~1.944; aOR: 1.740, 95% CI: 1.372~2.207) were associated with an increased risk of AMI. Conclusion The study demonstrates a significant association between the current and long-term use of glucocorticoids and leflunomide and an increased risk of AMI in patients with RA. These findings underscore the importance of careful consideration of cardiovascular risks when selecting anti-rheumatic agents for RA treatment.

Digital breast tomosynthesis (DBT) provides improved cancer detection and lower recall rates when compared with full-field digital mammography (DM) and has been widely adopted for breast cancer screening. However, adopting DBT presents new challenges such as an increased number of acquired images resulting in longer interpretation times. Artificial intelligence (AI) offers numerous opportunities to enhance the advantages of DBT and mitigate its shortcomings. Research in the DBT AI domain has grown significantly and AI algorithms play a key role in the screening and diagnostic phases of breast cancer detection and characterization. The application of AI may streamline the workflow and reduce the time required for radiologists to interpret images. In addition, AI can minimize radiation exposure and enhance lesion visibility in synthetic two-dimensional DM images. This review provides an overview of AI technology in DBT, its clinical applications, and future considerations.

After a year of exchange in Montreal, a South Korean academic physiatrist and his Canadian colleague have reflected on the strengths and weaknesses of their respective healthcare systems. They have focused more specifically on physiatrist-delivered pain medicine treatments. This article is written based on personal perspectives. It aims to present the differences between the systems in South Korea and Quebec, highlighting the issues arising from each system and providing perspectives on potential solutions.

Accurate measurement of the foot contact area is crucial for diagnosing pes planus (flatfoot) and pes cavus (high arch), which significantly affect pressure distribution across the plantar surface. This study aimed to develop a program using ChatGPT-4 to automate foot contact area measurements using a podoscope, thereby enhancing diagnostic precision. A 53-year-old female volunteer stood on a podoscope to capture images of her feet, which were processed to isolate the foot contours and measure the contact areas. A program developed utilizing ChatCPT-4 was designed to outline the feet, detect contact areas, and calculate their sizes and ratios. The results demonstrated clear visualization of foot contours with automated calculation of the contact area and its ratio to the total foot area. The entire foot area measured 1,091,381.00 pixels, with a contact area of 604,252.50 pixels. The ratio of the ground contact area to the entire foot area was calculated as 55.37%. This method, which employs advanced image-processing techniques powered by ChatGPT-4, demonstrates the potential for integrating artificial intelligence into clinical applications. This approach could improve diagnostic precision and patient outcomes through personalized treatment strategies.

Background and Objectives: Several real-world studies have been done in patients with nonvalvular atrial fibrillation (NVAF); however, information on its safety profile in patients with renal impairment is limited. XARENAL, a real-world study, aimed to prospectively investigate the safety profile of rivaroxaban in patients with NVAF with renal impairment (creatinine clearance [CrCl], 15–49 mL/min). Methods: XARENAL is an observational single-arm cohort study in renal impairment NVAF patients. Patients were followed up approximately every 3 months for 1 year or until 30 days following early discontinuation. The primary endpoint was major bleeding events. All adverse events, symptomatic thromboembolic events, treatment duration, and renal function change from baseline were the secondary endpoints. Results: XARENAL included 888 patients from 29 study sites. Overall, 713 (80.3%) had moderate renal impairment (CrCl, 30–49 mL/min), and 175 (19.7%) had severe renal impairment (CrCl, 15–29 mL/min) with a mean estimated glomerular filtration rate (eGFR) of 45.2±13.0 mL/min/1.73 m 2 . The mean risk scores were 3.3±1.4 and 1.7±0.9 for CHA 2 DS 2 -VASc score and HAS-BLED score, respectively. An incidence proportion of 5.6% (6.2 events per 100 patient-years) developed major bleeding; however, fatal bleeding occurred in 0.5% (0.5 events per 100 patient-years). The mean change in the eGFR was 2.22±26.47 mL/min/1.73 m 2 per year. Conclusions XARENAL observed no meaningful differences in major bleeding events from other previous findings as well as renal function changes in rivaroxaban-treated NVAF patients with renal impairment, which is considered to be acceptable in clinical practice.

Background and Objectives: The aim of this study was to confirm the effect of intralesional triamcinolone acetonide injections (TRIAM) to treat granulomatous tissue surrounding the tracheostomy stoma.Subjects and Method We reviewed and documented the medical charts of 20 patients who were administered with TRIAM to treat granulomatous tissue surrounding the tracheostomy stoma from January 2018 to June 2019 were. The surface area of the granulomatous tissue was measured using Image J. The differences between the area of the granulomatous tissue after conventional treatment and after TRIAM on the same patient were compared. Results: A total of 20 patients consisting of 12 males and 8 females were included, with the patients’ average age being 60.0±14.3 years. The initial surface area of granulation tissue was 1.266±0.449 cm2, and 1.243±0.432 cm2 after conventional treatment, showing no statistically significant difference in the tissue area (p=0.143). The pre-injection surface area of granulation tissue was 1.243±0.432 cm2, and the area on the 7th day after the third injection was 0.477±0.217 cm2, showing a significant difference (p<0.001). Conclusion Compared to the conventional treatment, the surface area of granulomatous tissue surrounding the tracheostomy stoma significantly decreased after being treating with TRIAM. This finding suggests the effectiveness of TRIAM as a treatment of granulomatous tissue surrounding the tracheostomy stoma without complications such as bleeding.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

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.

Background/Aims: Krebs von den Lungen-6 (KL-6) is associated with prognosis in patients with COVID-19. However, there is limited data on the correlation between the prognosis of COVID-19 and varying KL-6 levels at different time points. We investigated the optimal cutoff values of the initial and peak serum KL-6 levels to predict mortality and evaluated their correlation with mortality. Methods: This retrospective cohort study collected data on serially collected serum KL-6 levels in patients hospitalized with COVID-19 between October 2020 and January 2022 at a single tertiary hospital in South Korea. The area under the receiver operating characteristic curve and Youden index were used to determine the cutoff points for the initial and peak KL-6 levels that best predicted 30-day mortality. The association between the initial and peak KL-6 values was assessed by univariate and multivariate logistic regression models. Results: A total of 349 patients were included in this study. The mean initial and peak KL-6 levels were significantly higher in the non-survivor group than in the survivor group. The initial and peak KL-6 values that best predicted 30-day mortality were 491.85 U/mL and 660.05 U/mL, respectively. An initial KL-6 level greater than 491.85 U/mL and a peak KL-6 level greater than 660.05 U/mL were significantly associated with 30-day mortality. Conclusions The initial and peak levels of KL-6 were significantly associated with 30-day mortality in hospitalized patients with COVID-19. These findings suggest that serially monitoring blood KL-6 levels could be a valuable prognostic indicator for COVID-19.