Purpose: Recently, deep learning techniques have been introduced for age estimation, with automated methods based on radiographic analysis demonstrating high accuracy. In this study, we applied convolutional neural network (CNN) techniques to the lower dentition area on orthopantomograms (OPGs) of children to develop an automated age estimation model and evaluate its accuracy for use in forensic dentistry. Methods: In this study, OPGs of 2,856 subjects aged 3-14 years were analyzed. The You Only Look Once (YOLO) V8 object detection technique was applied to extract the mandibular dentition area on OPGs, designating it as the region of interest (ROI). First, 200 radiographs were randomly selected, and were used to train a model for extracting the ROI. The trained model was then applied to the entire dataset. For the CNN image classification task, 80% of OPGs were allocated to the training set, while the remaining 20% were used as the test set. A transfer learning approach was employed using the ResNet50 and VGG19 backbone models, with an ensemble technique combining these models to improve performance. The mean absolute error (MAE) on the test set was used as the validation metric, and the model with the lowest MAE was selected. Results: In this study, the age estimation model developed using mandibular dentition region from OPGs achieved MAE and root mean squared error (RMSE) values of 0.501 and 0.742, respectively, on the test set, and MAE and RMSE values of 0.273 and 0.354, respectively, on the training set. Conclusions The automated age estimation model developed in this study demonstrated accuracy comparable to that of previous research and shows potential for applications in forensic investigations. Increasing the sample size and incorporating diverse deep learning techniques are expected to further enhance the accuracy of future age estimation models.

With advancements in both pharmacologic and non-pharmacologic treatments, significant changes have occurred in heart failure (HF) management. The previous Korean HF registries, namely the Korea Heart Failure Registry (KorHF-registry) and Korean Acute Heart Failure Registry (KorAHF-registry), no longer accurately reflect contemporary acute heart failure (AHF) patients. Our objective is to assess contemporary AHF patients through a nationwide registry encompassing various aspects, such as clinical characteristics, management approaches, hospital course, and long-term outcomes of individuals hospitalized for AHF in Korea. This prospective observational multicenter cohort study (KorHF III) is organized by the Korean Society of Heart Failure. We aim to prospectively enroll 7,000 or more patients hospitalized for AHF at 47 tertiary hospitals in Korea starting from March 2018. Eligible patients exhibit signs and symptoms of HF and demonstrate either lung congestion or objective evidence of structural or functional cardiac abnormalities in echocardiography, or isolated right-sided HF. Patients will be followed up for up to 5 years after enrollment in the registry to evaluate long-term clinical outcomes. KorHF III represents the nationwide AHF registry that will elucidate the clinical characteristics, management strategies, and outcomes of contemporary AHF patients in Korea.

Background: Atherogenic dyslipidemia, which is frequently associated with type 2 diabetes (T2D) and insulin resistance, contributes to the development of vascular complications. Statin therapy is the primary approach to dyslipidemia management in T2D, however, the role of non-statin therapy remains unclear. Ezetimibe reduces cholesterol burden by inhibiting intestinal cholesterol absorption. Fibrates lower triglyceride levels and increase high-density lipoprotein cholesterol (HDL-C) levels via peroxisome proliferator- activated receptor alpha agonism. Therefore, when combined, these drugs effectively lower non-HDL-C levels. Despite this, few clinical trials have specifically targeted non-HDL-C, and the efficacy of triple combination therapies, including statins, ezetimibe, and fibrates, has yet to be determined. Methods: This is a multicenter, prospective, randomized, open-label, active-comparator controlled trial involving 3,958 eligible participants with T2D, cardiovascular risk factors, and elevated non-HDL-C (≥100 mg/dL). Participants, already on moderate-intensity statins, will be randomly assigned to either Ezefeno (ezetimibe/fenofibrate) addition or statin dose-escalation. The primary end point is the development of a composite of major adverse cardiovascular and diabetic microvascular events over 48 months. Conclusion This trial aims to assess whether combining statins, ezetimibe, and fenofibrate is as effective as, or possibly superior to, statin monotherapy intensification in lowering cardiovascular and microvascular disease risk for patients with T2D. This could propose a novel therapeutic approach for managing dyslipidemia in T2D.

Nevus unius lateris (NUL) is a variant of an epidermal nevus that involves a widespread body surface, especially half of the body, and its onset usually occurs at birth or early life. An increased risk of basal cell carcinoma (BCC) in epidermal nevus has also been reported. However, the exact incidence remains unknown. A 67-year-old female patient visited our dermatology clinic with black nodules protruding over multiple verrucous brownish patches and plaques on the right side of the trunk. The patient had congenital NUL. Black nodules were observed to develop several months previously and gradually enlarged. The skin biopsy of one black nodule was consistent with BCC. Subsequently, Mohs micrographic surgery was performed for the BCC. To date, there have been few reports of BCC arising within the nevus unius lateri. Herein, we report a rare case of BCC considered to originate from a congenital NUL.

The circadian rhythm for mood (CRM) is a digital therapeutic, which aims to prevent mood episode and improve clinical course in patients with major mood disorders. Developed on the circadian rhythm hypothesis of mood disorder, CRM predicts the impending risk of mood episode with its built-in algorithm, utilizing wearable devices data and daily self-reports, and provides personalized feedback. In a pilot study of the CRM, the users experienced less frequent and shorter duration of mood episodes than the non-users. To investigate the efficacy of the upgraded CRM, a double-blind, randomized, sham-controlled, parallel-group trial is designed. Patients aged between 19 and 70, diagnosed with bipolar I disorder, bipolar II disorder, or major depressive disorder, in a euthymic state for more than two months, can participate. During this 12-month trial, participants are assessed for episode recurrence every three months, and the efficacy of the CRM as a potential digital therapeutic is evaluated. Trial registration: ClinicalTrials.gov Identifier: NCT05400785.

In children and adolescents, dental age estimation is performed with the development of the teeth. Various statistical analysis methods have been used to determine the relationship between age and dental maturity and develop an accurate method of age calculation. This study attempted to apply a neural network model for the statistical analysis of dental age estimation in children and evaluated its applicability. This study used 1196 panoramic radiographs of patients aged 3–16 years, and 996 and 200 were randomly classified into training and test sets, respectively. The dental maturity of the mandibular left teeth was evaluated using Demirjian's method, the neural network model using the backpropagation algorithm was derived using training sets, and the errors were evaluated using 100 radiographs of each male and female as test sets. In addition, multiple linear regression analysis was conducted on the same training set, and the error was calculated by applying it to the test set and comparing it with the error of the neural network model. In the neural network model, the mean absolute error (MAE) and root mean squared error (RMSE) were 0.589 and 0.783 in male subjects and 0.529 and 0.760 in female subjects, respectively. In the multiple linear regression model, the MAE and RMSE were 0.600 and 0.748 in male subjects and 0.566 and 0.789 in female subjects, respectively. When applying the neural network model to the statistical analysis of the dental developmental stage, the results were as accurate as those of conventional statistical analysis methods. This study’s approach is expected to be useful for estimating the ages of children.

Given that tooth loss is a degenerative change, the number of residual teeth may be used to specify a particular age range as a marker for age estimation. This study examined changes in the number of teeth with age using a nationwide oral survey database and derived the age distribution of the Korean population according to the number of teeth. Data on the number of teeth and age were extracted from the oral examination data of the Korean National Health and Nutrition Examination Survey (KNHANES) from 2016 to 2018. Statistical analyses of a complex sample survey were performed using weighted values. The distribution range of the number of teeth by age was broad. The proportion of young people decreased progressively as the number of remaining teeth decreased. In contrast, the proportion of those from the older age group decreased slightly as the number of teeth increased. The number of teeth was subdivided into groups of four, age was categorized into 5-year intervals, and the distribution of age groups by the number of teeth was analyzed. We attempted to determine the age group threshold at approximately 95th percentile for age. In summary, we found that if there were ≤4, 5-12, and 13-20 residual teeth, the estimated age was ≥60, ≥55, and ≥50 years, respectively, with an approximately 95% probability. When many teeth are lost and it is difficult to apply conventional dental age estimation methods, our method may assist in narrowing the age range, although it is not an accurate age determination method.

Background and Objectives: We analyzed surgical outcomes, perioperative complications, and mortality in head and neck squamous cell carcinoma (HNSCC) in patients who underwent curative surgery following neoadjuvant immunotherapy.Subjects and Method The records of 36 HNSCC patients who underwent curative surgery with neoadjuvant immunotherapy and 69 HNSCC patients who received neoadjuvant chemotherapy were analyzed. Results: The average operation time was 315 minutes, and the average bleeding volume was 167 cc. The average length of hospital stay was 21 days. When evaluating surgical margin status, we found 24 patients (66.6%) who exhibited a negative margin. We found no case where surgery was impossible due to progression of the lesion during neoadjuvant immunotherapy. Compared to the neoadjuvant chemotherapy group, neoadjuvant immunotherapy group showed acceptable perioperative safety and complication profile. The postoperative complication rate was 19.4% in the neoadjuvant immunotherapy group and 13.0% in the neoadjuvant chemotherapy group (p=0.386). There were no serious complications during the recovery period after surgery or instances of death due to complications. Conclusion In HNSCC patients, there was no increase in the incidence of complications or mortality related to curative surgery after neoadjuvant immunotherapy.

Background/Aims: Despite proper use of pharmaceuticals, adverse drug reactions (ADRs) can lead to problems related to patient safety. We analyzed the characteristics of ADRs, particularly serious adverse events (SAEs), in a single tertiary medical institution. Methods: Spontaneous ADR report data collected from 2010 to 2019 in Seoul National University Hospital were assessed. Causality was evaluated according to the World Health Organization-Uppsala Monitoring Centre criteria. Age, sex, onset, severity, seriousness, and system organ class (SOC) of ADRs and SAEs were analyzed. Results: During the study period, a total of 49,955 individual case safety reports were assessed as possible, probable, or certain. Although the number of gastrointestinal ADR reports was high (25.9%), severe cases were uncommon (2.6%). By contrast, the number of hematologic disorders was low (6.6%) but 39.2% of them were severe. Among ADRs, 10.2% were assessed as SAEs, the proportion of which was high at extreme ages and in males. Body as a whole-general disorders were the most frequently reported SOC for SAEs, followed by skin and appendage disorders. Antineoplastic agents and antibiotics were the most common causative agents of SAEs and ADRs. Anaphylactic reaction was the most frequent SAE (6.5%). Conclusions The proportion of SAE differs according to SOC and drug. Attention should be paid to SAEs in children and older adults because the rate of SAEs is significantly higher at extreme ages.

Background/Aims: Despite proper use of pharmaceuticals, adverse drug reactions (ADRs) can lead to problems related to patient safety. We analyzed the characteristics of ADRs, particularly serious adverse events (SAEs), in a single tertiary medical institution. Methods: Spontaneous ADR report data collected from 2010 to 2019 in Seoul National University Hospital were assessed. Causality was evaluated according to the World Health Organization-Uppsala Monitoring Centre criteria. Age, sex, onset, severity, seriousness, and system organ class (SOC) of ADRs and SAEs were analyzed. Results: During the study period, a total of 49,955 individual case safety reports were assessed as possible, probable, or certain. Although the number of gastrointestinal ADR reports was high (25.9%), severe cases were uncommon (2.6%). By contrast, the number of hematologic disorders was low (6.6%) but 39.2% of them were severe. Among ADRs, 10.2% were assessed as SAEs, the proportion of which was high at extreme ages and in males. Body as a whole-general disorders were the most frequently reported SOC for SAEs, followed by skin and appendage disorders. Antineoplastic agents and antibiotics were the most common causative agents of SAEs and ADRs. Anaphylactic reaction was the most frequent SAE (6.5%). Conclusions The proportion of SAE differs according to SOC and drug. Attention should be paid to SAEs in children and older adults because the rate of SAEs is significantly higher at extreme ages.