Burning mouth syndrome remains a frequent source of diagnostic delay, repeated consultations, and fragmented care because it has long been treated as a “diagnosis of exclusion.” Recent updates in orofacial pain classification and research diagnostic frameworks support a practical shift: from an exclusionary label toward a structured diagnostic algorithm and staged, phenotype-guided management. This narrative, algorithm-focused clinical review aims to summarize clinically actionable evidence and to propose a “minimum sufficient workup” that prioritizes safety, efficiency, and patient-centered communication.We first outline pragmatic diagnostic criteria and key symptom patterns, then integrate current concepts of mixed mechanisms—peripheral neuropathic features, centralociplastic amplification, and psychosocial modulators—that account for symptom fluctuation and discordance between symptom severity and objective findings. The core of this review is a one-page stepwise algorithm: (1) confirm chronicity and absence of visible mucosal disease, (2) screen for red flags requiring urgent evaluation, (3) address common local contributors (e.g., candidiasis, irritants, contact allergy, xerostomia), (4) perform a targeted systemic/medication/deficiency panel, and (5) phenotype patients to guide staged treatment choices and follow-up. Finally, we provide a practical management framework emphasizing education, trigger control, and individualized combinations of topical, systemic, and behavioral interventions with predefined reassessment intervals. Future priorities include phenotype-stratified randomized trials and implementation outcomes that quantify reductions in diagnostic delay, misdiagnosis, and unnecessary testing.

In forensic medicine, age estimation commonly involves assessing age-related changes in teeth and skeletal structures. Vertebral morphological alterations, such as osteophyte formation, serve as age indicators. Recent studies using deep-learning techniques, such as neural networks, for age estimation from radiographic images have been conducted, reporting significantly higher accuracy than previous studies. This study aimed to estimate age using neural network-based deep-learning techniques applied to computed tomography (CT) cross-sectional images of the spine and evaluate its feasibility. Postmortem CT scans of 214 cadavers with varying decomposition levels were used. Coronal and sagittal cross-sectional images penetrating the center of each vertebral body were extracted for the 11th and 12th thoracic vertebrae and the first to fifth lumbar vertebrae. Using these images, along with the chronological ages of deceased individuals, an age estimation model was developed through regression analysis in PyTorch, employing a convolutional neural networks architecture with five-fold cross-validation. The model achieved a mean absolute error of 5.385 years, root mean squared error of 7.029 years, and coefficient of determination of 0.793. Although the sample size was relatively small, the results suggested the potential applicability of vertebral imagingbased age estimation in the Korean population. Further research using a larger dataset may improve the accuracy and reliability of the model.

Tuberculosis survivors often face long-term physical, psychological, and social challenges that extend beyond microbiological cure. Post-tuberculosis complications include pulmonary damage, cardiovascular and neurological sequelae, as well as significant impacts on overall wellbeing and livelihoods. Despite increasing awareness, most care continues to focus primarily on lung disease, overlooking the multisystem and social needs of survivors. A holistic, people-centered framework that integrates medical, rehabilitative, and community-based strategies is essential for restoring health and facilitating societal participation among tuberculosis survivors.

Background and Objectives: Clinical characteristics and outcomes in acute heart failure (AHF) vary by phenotype. We assessed phenotype-specific features, treatment patterns, and outcomes in a nationwide Korean cohort. Methods: The Korean Heart Failure III registry prospectively enrolled 7,351 AHF admissions at 47 hospitals. Among 6,777 patients with available left ventricular ejection fraction (EF), phenotypes were defined as heart failure with reduced EF (HFrEF, ≤40%), mildly reduced EF (HFmrEF,41–49%), or preserved EF (HFpEF, ≥50%). The primary endpoint was a 12-month composite of all-cause death or heart transplantation, evaluated from index admission and, among hospital survivors, from discharge. We used inverse probability weighting (multinomial generalized boosted models with stabilized, trimmed weights) and weighted Cox proportional-hazards models to estimate hazard ratios (HRs). Results: Phenotype distribution was 58.9% HFrEF, 13.6% HFmrEF, and 27.5% HFpEF. Crude 12-month composite rates from index admission were 13.4% (HFrEF), 12.7% (HFmrEF), and 16.8% (HFpEF). After weighting, from index admission, HFmrEF (HR, 0.892; 95% confidence interval [CI], 0.731–1.088) and HFpEF (HR, 1.101; 95% CI, 0.939–1.291) did not differ from HFrEF; from discharge, HFpEF had modestly higher risk (HR, 1.207; 95% CI, 1.008–1.445) whereas HFmrEF did not (HR, 1.039; 95% CI, 0.844–1.279). Hyponatremia and chronic kidney disease were consistent adverse markers, while angiotensin-converting enzyme inhibitor/ angiotensin II receptor blocker use at discharge was protective. Conclusions Across the EF spectrum, phenotypes showed distinct profiles and risk. Postdischarge risk was modestly higher in HFpEF, supporting phenotype-tailored care and systematic discharge optimization in Korean patients with AHF.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

Purpose: Temporomandibular disorder (TMD) is a multifactorial condition influenced by biological, psychological, and social factors. Some patients perceive dental treatment as the cause of their TMD, which may impact symptom perception and treatment response.This study aims to compare the psychosocial and clinical characteristics of patients who attribute their TMD onset to prior dental treatment (DT group) with those who do not (NT group). Methods: A total of 250 patients diagnosed with TMD at Pusan National University Dental Hospital between January and October 2024 were included. Patients were classified into the DT group (n=92) if they attributed their symptoms to previous dental procedures, while the remaining NT group (n=158) consisted of patients with other primary complaints. Patients were additionally categorized into Generation X (1965-1980), Generation Y (1981-1999), and Generation Z (2000-2012). Clinical assessments were conducted following the Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), and psychosocial factors were evaluated using the Oral Behaviors Checklist (OBC), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-15 (PHQ-15). Results: The DT group had a significantly higher mean age (54.16±16.87 years) compared to the NT group (39.71±19.12 years, p<0.001). Psychological distress scores (PHQ-9, GAD-7, and PHQ-15) were significantly higher in the DT group, particularly among Generation X patients (p<0.05). Muscle-related pain was more prevalent in the DT group (75%) than in the NT group. Interestingly, OBC scores were higher in the NT group (p<0.05). Conclusions Patients who attributed their TMD onset to dental treatment reported higher psychological distress and a greater prevalence of muscle-related pain, underscoring the need for a biopsychosocial approach to TMD management. Clinicians should consider the impact of patient perception on TMD symptoms and integrate psychological assessment and counseling to enhance treatment efficacy and patient adherence.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.

Purpose: Emphysematous pyelonephritis (EPN) is a life-threatening disease requiring immediate treatment. This multicenter retrospective cohort study aimed to analyze the mortality rate and risk factors associated with EPN. Materials and Methods: Between January 2011 and February 2021, 217 patients diagnosed with EPN via computed tomography who visited 14 teaching hospitals were retrospectively analyzed. Clinical data, including age, sex, comorbidities, Huang and Tseng classification, hydronephrosis, acute kidney injury, blood and urine tests, surgical interventions, percutaneous drainage, and conservative treatments, were compared between the survival and death groups. Risk factors for mortality due to EPN were analyzed using univariate and multivariate methods. Results: The mean age of survivors and deceased patients was 67.8 and 69.0 years, respectively (p=0.136). The sex distribution (male/female) was 48/146 and 8/15, respectively (p=0.298). Of the 217 patients, 23 died, resulting in a mortality rate of 10.6%. In univariate analysis, the Huang and Tseng classification (p=0.004), platelet count (p=0.005), and acute kidney injury (p=0.007) were significantly associated with mortality from EPN. In multivariate analysis, only the Huang and Tseng classification (p=0.029) was identified as a risk factor. Mortality rates according to the Huang and Tseng classification were as follows: class I (5.88%), class II (7.50%), class IIIa (14.28%), class IIIb (25.00%), and class IV (23.07%). Conclusions EPN is associated with a high mortality rate. Among various clinical factors, the Huang and Tseng classification was the most significant indicator for predicting mortality.

Background: The development of frailty at hospital discharge affects the clinical outcomes in severe coronavirus disease 2019 (COVID-19) survivors who had no frailty before hospitalization. We aimed to describe the prevalence of new frailty using the clinical frailty scale (CFS) and evaluate its associated factors in patients with severe COVID-19 without pre-existing frailty before hospitalization. Methods: We performed a secondary analysis of clinical data from a nationwide retrospective cohort collected from 22 hospitals between January 1, 2020 and August 31, 2021. The patients were at least 19 years old and survived until discharge after admission to the intensive care unit (ICU) because of severe COVID-19. Development of new frailty was defined as a CFS score ≥5 at hospital discharge. Results: Among 669 severe COVID-19 survivors without pre-existing frailty admitted to the ICU, the mean age was 65.2±12.8 years, 62.5% were male, and 50.2% received mechanical ventilation (MV). The mean CFS score at admission was 2.4±0.9, and new frailty developed in 27.8% (186/483). In multivariate analysis, older age, cardiovascular disease, CFS score of 3–4 before hospitalization, increased C-reactive protein level, longer duration of corticosteroid treatment, and use of MV and extracorporeal membrane oxygenation were identified as factors associated with new-onset frailty. Conclusion Our study suggests that new frailty is not uncommon and is associated with diverse factors in survivors of severe COVID-19 without pre-existing frailty.