Purpose: Medical artificial intelligence (AI) is rapidly being integrated into clinical practice and healthcare systems, raising concerns regarding safety, accountability, and governance. Despite its increasing importance, empirical comparative studies examining differences in perceptions of medical AI among key expert groups remain limited. This study aimed to compare and analyze perceptions of medical AI among medical and non-medical professionals and to systematically identify commonalities and differences across policy- and governance-relevant domains. Methods: Focus group interviews using open-ended questions were conducted with 30 experts (15 medical and 15 non-medical professionals) who had direct experience with medical AI. Data were analyzed using inductive thematic analysis combined with qualitative comparative analysis. Analytical rigor was strengthened through independent coding and consensus-based discussions. Results: Both groups recognized the potential of medical AI to bring meaningful changes to healthcare systems. However, medical professionals primarily evaluated medical AI in terms of clinical applicability, patient safety, explainability, and accountability. In contrast, non-medical professionals emphasized technological maturity, scalability, data infrastructure, standardization, and system-integration potential. Group-specific patterns also emerged regarding perceived limitations, autonomy, educational priorities, and classification frameworks, particularly in relation to clinical risk management versus system-level design and governance considerations. Conclusion: Differences in perceptions of medical AI are systematically associated with distinct interpretive frames shaped by professional roles and responsibility structures. Effective implementation and policy design for medical AI therefore require an integrated approach that accounts for these structural differences. This study provides empirical evidence and a conceptual foundation for future quantitative and mixed-methods research on medical AI governance.

Attributable fraction (AF) measures, including AF and population attributable fraction (PAF), quantify the potential reductions in disease burden if specific risk factors were eliminated. Although relative risk describes the strength of association, it does not directly address the clinically and policy-relevant question of how much disease is preventable. This article presents an integrated framework for interpreting AF and PAF across clinical and population contexts, focusing on applications to cancer prevention.Current concepts: AF, defined at the level of exposed individuals, helps explain causal contribution and the preventable proportion in clinical settings. PAF that is based on exposure prevalence among those with the disease (Pc) reflects the causal composition of disease among patients, whereas PAF based on exposure prevalence in the population (Pe) estimates potential impacts of population-level interventions. These measures are grounded in a counterfactual framework and require causal interpretation. This review presents key formulations, including Levin’s and Miettinen’s approaches, together with their underlying assumptions. By distinguishing target populations and question types—causation, prevention, and prioritization—AF and PAF provide complementary insights at the individual, patient group, and population levels.Discussion and conclusion: AF measures offer a unified framework linking causal inference with clinical decision-making and public health policy. AF supports patient-level counseling and intervention prioritization, whereas PAF informs population-level prevention and resource allocation. Appropriate interpretation requires careful consideration of causal assumptions, target populations, and the presence of multiple risk factors. Overall, AF and PAF are essential tools for translating epidemiologic evidence into actionable clinical and policy decisions.

Autonomic dysfunction is a common but frequently underrecognized feature of many neurological disorders. It may present as orthostatic hypotension (OH), supine hypertension, bladder and gastrointestinal dysfunction, sudomotor abnormalities, or sexual dysfunction, and it contributes substantially to morbidity and reduced quality of life. This review provides a clinically oriented overview of autonomic dysfunction across major neurological disorders, outlines a practical diagnostic framework, and summarizes current management principles for general physicians and neurologists.Current concepts: The spectrum of neurological diseases associated with autonomic involvement is broad, ranging from peripheral neuropathies—such as diabetic autonomic neuropathy, Guillain-Barré syndrome, and hereditary transthyretin amyloidosis—to central neurodegenerative disorders, including Parkinson disease, multiple system atrophy, dementia with Lewy bodies, and pure autonomic failure. Motor neuron disease and autoimmune autonomic ganglionopathy represent additional important categories. Clinical evaluation of autonomic dysfunction relies on careful history taking, bedside orthostatic blood pressure measurement, and standardized autonomic function tests, including the Valsalva maneuver, deep breathing, tilt-table testing, and sudomotor assessment. Distinguishing neurogenic from non-neurogenic causes of OH is critical because it determines both prognosis and management. Management requires a multifaceted approach that includes treatment of the underlying disease, nonpharmacologic interventions, and targeted pharmacotherapy for specific autonomic manifestations. The coexistence of OH and supine hypertension in patients with autonomic failure presents a particularly challenging therapeutic dilemma.Discussion and conclusion: Autonomic dysfunction spans diverse neurological diseases, impairing quality of life and survival. Systematic evaluation enables early detection, while multifaceted management—combining nonpharmacologic measures and pharmacotherapy—improves outcomes. Greater awareness will enhance diagnostic accuracy and care for affected patients.

Purpose: This study compared the clinical utility and safety of the muscle-sparing anterolateral supine (ALS) approach using a skin-crease bikini incision with the conventional direct lateral (DL) approach in terms of the short-term patient reported outcome measurement (PROM) and the postoperative complication rates. Materials and Methods: Between March 2023 and February 2024, patients who underwent primary total hip arthroplasty at a single institution were reviewed retrospectively. Ninety patients were identified in the ALS group, and 264 were identified in the DL group. After 1:1 matching for age, sex, and body mass index, 87 patients in each group were analyzed. The primary outcomes were the PROM, including the modified Harris Hip Score (mHHS), Oxford Hip Score (OHS), and Hip Disability and Osteoarthritis Outcome Score (HOOS), evaluated preoperatively and at six weeks, three months, six months, and one year postoperatively. The secondary outcomes included postoperative complications such as transient sensory changes, permanent nerve injury, dislocation, superficial and deep infections, intraoperative fracture, and iliopsoas tendinitis. Results: All three PROM (mHHS, OHS, and HOOS) showed statistically and clinically superior results in the ALS group compared to the DL group within the first six months postoperatively. No significant differences in the incidence of any recorded complications were observed between the two groups. Conclusion At three and six months postoperatively, the ALS approach with a bikini incision showed superior PROM compared to the DL, suggesting better early functional recovery and patient satisfaction. Although the PROM differences diminished at one year, the early postoperative advantage highlights the clinical benefits of the muscle-sparing ALS approach.

Rotator cuff tears are a common musculoskeletal disorder that significantly impairs shoulder function, especially in the elderly. Traditionally, mechanical wear and age-related degeneration have been considered the leading causes. Recent studies, however, emphasize that systemic metabolic disorders, such as diabetes mellitus, obesity, and dyslipidemia, play a crucial role in the development and healing of rotator cuff disease. This narrative review comprehensively examines the biological mechanisms and clinical outcomes associated with these metabolic comorbidities in rotator cuff degeneration and surgical repair failure. Based on relevant clinical and experimental studies, this study analyzed how each metabolic disease contributes to tendon injury and impaired regeneration. Diabetes mellitus induces chronic inflammation, inhibits collagen synthesis, and impairs microvascular perfusion, hindering tendon healing. Obesity increases the mechanical load on the shoulder and promotes systemic inflammation, exacerbating fatty infiltration of muscles and delaying tissue repair. Dyslipidemia accelerates tendon degeneration through the accumulation of fat, oxidative stress, and fatty infiltration of the rotator cuff muscles. These systemic factors are associated with higher re-tear rates, delayed functional recovery, and poorer surgical outcomes. As the prevalence of metabolic syndrome increases, precise assessment and perioperative management of these metabolic disorders are essential to improve patient outcomes and develop personalized treatment strategies for rotator cuff tears.

Rotator cuff (RC) injuries cause degenerative changes, including muscle atrophy and fatty infiltration, which remain key pathophysiological factors limiting functional recovery and increasing the risk of re-tears even after surgical repair. In particular, these changes tend to progress to fibrofatty replacement over time, highlighting the limitations of surgery-focused treatments alone. Recent research has addressed this by increasingly focusing on biological therapeutic strategies that directly target the degenerative pathology of the RC muscle. This review article examines the current trends in preclinical and clinical research on three main biological approaches: stem cell-based tissue regeneration, modulation of pathological signaling pathways, and metabolic reprogramming strategies that restore the pathological metabolic environment. Building upon these pathophysiological foundations, this review aims to develop recent biological treatment strategies and explore their potential clinical applications.

Anterior cruciate ligament (ACL) injuries are common sports-related knee injuries, with surgical treatment being widely accepted as the standard approach. An ACL reconstruction aims to restore the knee function, prevent secondary meniscal tears, and cartilage damage caused by instability. Acute isolated ACL injuries account for approximately 3%–10% of all ACL injuries, making them relatively uncommon.Various treatment methods, ranging from conservative management to ACL reconstruction, have been used, but surgical treatment is often preferred, particularly in young and active individuals. Conservative treatment allows patients to return to their previous activities, and studies have shown that its outcomes in terms of patient assessment and osteoarthritis incidence are comparable to those of surgical treatment. Nevertheless, it has some drawbacks, including a higher risk of secondary meniscal tears and mild static knee instability compared to surgery. Therefore, selecting suitable patients for conservative treatment is crucial for achieving satisfactory results. Various selection criteria have been proposed. Recent reports suggest that even young, highly active patients can return to their pre-injury activity levels if they are carefully selected for conservative treatment. With the appropriate indications and functional rehabilitation tailored to the patient’s expectations, conservative treatment can be considered a viable standard option for managing acute isolated ACL injuries. This review summarizes the clinical outcomes of conservative treatment for such injuries, focusing on appropriate indications and rehabilitation strategies based on the literature.

Metaverse-based mental health interventions have recently emerged as an extension of telepsychiatry, digital therapeutics (DTx), and virtual reality (VR)–based treatments for children and adolescents. The coronavirus disease 2019 pandemic accelerated the adoption of remote psychological assessment and intervention, raising critical questions regarding their clinical validity, developmental appropriateness, and long-term applicability in youth populations. Accumulating evidence has demonstrated that remote assessments and internet-based interventions can achieve clinical outcomes comparable to face-to-face approaches in selected domains, particularly anxiety, depression, and social communication difficulties. In parallel, immersive technologies such as VR and metaverse-based platforms have been applied to exposure-based interventions, social skills training, and emotion regulation in controlled and repeatable environments. This narrative review examined 48 empirical and review studies on telepsychiatry, internet-based cognitive behavioral therapy, DTx, VR, and metaverse-based interventions for children and adolescents. Neurobiological mechanisms relevant to fear extinction, executive function, emotion regulation, and social cognition were critically reviewed. In addition, real-world implementation experiences from a hospital-based Wee Center in Korea were integrated to evaluate feasibility within school-linked mental health services. The findings suggested that metaverse-based counseling should not be conceptualized as a stand-alone replacement for face-to-face treatment, but rather as a complementary, hybrid platform linking remote screening, structured digital intervention, and in-person clinical care. While current evidence supported feasibility and conditional clinical utility, further longitudinal, controlled, and cost-effectiveness studies were required to establish its role in pediatric mental health.

Ketamine is commonly used in the emergency department for procedural sedation. It is the most commonly chosen sedative drug in children because of its rapid onset, short half-life, little respiratory depression, and can be administered intravenously and intramuscularly. Common side effects include hallucination, visual disturbance, dizziness, nausea, and vomiting. Recently, it has also been used as an anticonvulsant for refractory status epilepticus. The authors encountered a case of generalized tonic-clonic seizure in a four-year-old boy after an intramuscular injection of ketamine for procedural sedation. This case is reported to share the author’s experience with medical professionals who use ketamine and raise awareness.

Objective: The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare systems worldwide, leading to increased mortality rates across various conditions. This study assessed the impact of COVID-19 on excess in-hospital mortality among emergency department patients and examined variations by community income levels, thereby highlighting socioeconomic disparities. Methods: This retrospective cross-sectional study used data from the National Emergency Department Information System in Korea. Cancer patients who visited emergency departments between January 27 and December 31 in 2019 (pre-COVID) and 2020 (during COVID) were included. The primary outcome was in-hospital mortality. The main exposure was the COVID-19 outbreak, with county per capita income tax serving as the interaction variable. The risk-adjusted in-hospital mortality rates were calculated. A multilevel linear regression model with an interaction term was used to estimate the difference-in-difference between the periods based on county income tax. Results: A total of 206,400 cancer patients were included 110,879 pre-COVID and 95,521 during COVID with an unadjusted in-hospital mortality rate of 1.0%. The risk-adjusted mortality rate was significantly higher during COVID than pre-COVID (1.2% vs. 0.9%, P<0.01). Using the highest socioeconomic status group (Q1) as the reference, the excess inhospital mortality odds during COVID were higher in Q3 (adjusted odds ratio [aOR], 1.32; 95% confidence interval [CI], 1.17-1.54) and Q4 (aOR, 1.43; 95% CI, 1.15-1.77). Conclusion The COVID-19 pandemic exacerbated in-hospital mortality disparities among cancer patients, imposing a greater burden on lower socioeconomic groups. These findings highlight the importance of implementing equitable healthcare strategies to protect vulnerable populations during health emergencies.