Journal of Yeungnam medical science最新文献

Spondylocarpotarsal synostosis syndrome (SCTS) is a rare genetic disorder characterized by vertebral fusion, short stature, and skeletal anomalies. SCTS is primarily associated with mutations in filamin B. However, in this report, we present a unique case of SCTS in a 28-year-old male who complained of neck and shoulder pain persisting for 1 year. His clinical presentation included radioulnar synostosis, cervical spine anomalies (scoliosis and agenesis of the posterior arch of C1), and a history of polydactyly. Genetic analysis revealed mutations in GMNN and DLL1. To the best of our knowledge, this is the first report on the association of SCTS with these genes.

Background: The self-management of low back pain (LBP) through patient information interventions offers significant benefits in terms of cost, reduced work absenteeism, and overall healthcare utilization. Using a large language model (LLM), such as ChatGPT (OpenAI) or Copilot (Microsoft), could potentially enhance these outcomes further. Thus, it is important to evaluate the LLMs ChatGPT and Copilot in providing medical advice for LBP and assessing the impact of clinical context on the quality of responses.

Methods: This was a qualitative comparative observational study. It was conducted within the Department of Physical Medicine and Rehabilitation, University of Montreal in Montreal, QC, Canada. ChatGPT and Copilot were used to answer 27 common questions related to LBP, with and without a specific clinical context. The responses were evaluated by physiatrists for validity, safety, and usefulness using a 4-point Likert scale (4, most favorable).

Results: Both ChatGPT and Copilot demonstrated good performance across all measures. Validity scores were 3.33 for ChatGPT and 3.18 for Copilot, safety scores were 3.19 for ChatGPT and 3.13 for Copilot, and usefulness scores were 3.60 for ChatGPT and 3.57 for Copilot. The inclusion of clinical context did not significantly change the results.

Conclusion: LLMs, such as ChatGPT and Copilot, can provide reliable medical advice on LBP, irrespective of the detailed clinical context, supporting their potential to aid in patient self-management.

Digital therapeutics (DTx) are emerging as a transformative innovation in healthcare offering evidence-based digital interventions for the treatment, management, and prevention of various diseases and disorders. In Korea, DTx have gained significant attention as potential solutions to the increasing burden of chronic diseases and mental health conditions. However, the Korean DTx market faces several challenges that hinder its widespread adoption and integration into the national healthcare system. This study provides a comprehensive analysis of the current state of the DTx market in Korea, identifies the key challenges impeding its growth, and proposes strategies for overcoming these obstacles. This study utilized a literature review and market analysis approach to examine the latest research, industry reports, and regulatory documents related to DTx. The analysis focused on three primary areas: (1) the current regulatory landscape, (2) technological advancements and challenges, and (3) economic and commercial factors influencing DTx adoption in Korea. A comparative analysis of global regulatory practices was also conducted to identify best practices. The findings revealed that while Korea has made significant strides in supporting DTx development, the market remains in its early stages. The key challenges include underdeveloped regulatory frameworks, issues with data quality and security, and a lack of established reimbursement pathways. We recommend developing tailored regulatory frameworks for DTx, enhancing policy support for small and medium-sized enterprises involved in DTx development, and increasing investments in technological infrastructure. By addressing these challenges, Korea could position itself as a leader in the global DTx market, delivering innovative and effective treatments to enhance patient care and outcomes.

The coronavirus disease 2019 (COVID-19) pandemic prompted the development of messenger RNA vaccines. Following extensive vaccination campaigns worldwide, several adverse reactions to these vaccines have been reported. This is a case series of unilateral lower extremity lymphedema after COVID-19 vaccination in two patients with a history of cervical cancer. An 82-year-old woman and a 68-year-old woman visited the outpatient clinic with unilateral leg edema after receiving a COVID-19 booster vaccine (BNT162b2; Pfizer-BioNTech) in the deltoid muscle. Both patients had a common history of cervical cancer treated with surgery, chemotherapy, and radiotherapy and were in complete remission. Gynecological evaluations, including laboratory and imaging studies, revealed no specific findings. Lymphoscintigraphy revealed delayed lymphatic drainage with diffuse dermal backflow in a unilateral lower extremity. This case series explores adverse reactions to COVID-19 vaccination in patients who are at high risk of developing lymphedema, providing novel data for similar clinical presentations.

The coronavirus disease 2019 pandemic has underscored the limitations of traditional diagnostic methods, particularly in ensuring the safety of healthcare workers and patients during infectious outbreaks. Smartphone-based digital stethoscopes enhanced with artificial intelligence (AI) have emerged as potential tools for addressing these challenges by enabling remote, efficient, and accessible auscultation. Despite advancements, most existing systems depend on additional hardware and external processing, increasing costs and complicating deployment. This review examines the feasibility and limitations of smartphone-based digital stethoscopes powered by AI, focusing on their ability to perform real-time analyses of audible and inaudible sound frequencies. We also explore the regulatory barriers, data storage challenges, and diagnostic accuracy issues that must be addressed to facilitate broader adoption. The implementation of these devices in veterinary medicine is discussed as a practical step toward refining their applications. With targeted improvements and careful consideration of existing limitations, smartphone-based AI stethoscopes could enhance diagnostic capabilities in human and animal healthcare settings.

Artificial intelligence (AI) has shown promise for revolutionizing healthcare. This narrative review focuses on the evolving discussion of the utility of AI and clinical informatics in critical care and acute care medicine, specifically focusing on digital twin (DT) technology. The improved computational power and iterative validation of these intelligent tools have enhanced medical education, in silico research, and clinical decision support in critical care settings. Integrating DTs into critical care opens vast opportunities, but simultaneously poses complex challenges, from data safety and privacy concerns to potentially increasing healthcare disparities. In medicine, DTs can significantly improve the efficiency of critical care systems. Stakeholder investment is essential for successful implementation and integration of these technologies.

Background: Chronic periodontitis is associated with various systemic inflammatory diseases; however, research on its association with chronic kidney disease (CKD) is relatively limited. Because both conditions share common risk factors, systemic inflammation plays a key role in the progression of these diseases. Galectin-3 (Gal-3) is a proinflammatory cytokine that plays an important role in chronic inflammatory diseases and is a potential biomarker. This study aimed to measure salivary Gal-3 levels in patients with periodontitis and CKD to better understand their association and evaluate Gal-3 as a diagnostic biomarker for these conditions.

Methods: Seventy-five patients were categorized into three groups: Group I, patients with CKD and periodontitis (n=25); Group II, patients with chronic periodontitis who were systemically healthy (n=25); and Group III, patients with CKD without chronic periodontitis (n=25). Demographic characteristics and periodontal and renal parameters were recorded for each patient. Saliva samples were collected to evaluate Gal-3 levels using an enzyme-linked immunosorbent assay.

Results: Patients with chronic periodontitis and CKD and those with chronic periodontitis alone (Groups I and II, respectively) showed significantly higher salivary Gal-3 levels than patients with CKD alone (Group III) (p<0.001). Bivariate correlation analysis indicated a strong relationship between clinical parameters and Gal-3 levels across all three groups.

Conclusion: Salivary Gal-3 level is a valuable early diagnostic marker of chronic periodontitis and CKD.

Background: The aim of this study was to examine various patient factors affecting first programmed embryo transfer (ET) outcomes under the freeze-all policy at a single tertiary university infertility center.

Methods: This retrospective observational study reviewed the medical records of 243 couples who underwent their first ET using blastocysts collected under the freeze-all antagonist-controlled ovarian stimulation (COS) protocol from 2015 to 2023. Patients were grouped into pregnant and nonpregnant groups, and their data, including demographics, COS and ET outcomes, and embryo storage duration, were analyzed.

Results: Patient body mass index, cause of infertility, follicle-to-oocyte index, distribution of blastocyst grades, number of transferred embryos, and embryo storage duration were not significantly different between the groups. In a simple comparative analysis, patients with successful clinical pregnancy tended to have significantly lower female and male age (33.83±3.67 and 35.32±4.54 years vs. 37.07±4.15 and 39.33±5.60 years, respectively), higher anti-Müllerian hormone levels (6.27±5.32 ng/mL vs. 4.14±3.82 ng/mL) and antral follicle counts (14.20±8.26 vs. 10.04±5.75), and higher numbers of retrieved oocytes and metaphase II oocytes (13.74±6.92 and 9.64±6.19 vs. 11.21±6.04 and 7.53±5.56, respectively). Multivariate logistic regression analysis of these variables revealed that only male age was a significant factor for successful clinical pregnancy (odds ratio, 4.768; 95% confidence interval, 1.252-18.162; p=0.022).

Conclusion: During the first programmed ET using blastocysts collected under the freeze-all antagonist COS protocol, male age and correspondingly the quality of gametes for fertilization were crucial for successful pregnancy, having more importance than calculated female ovarian reserve and embryo storage duration.