Background: Malaria elimination strategies in the Republic of Korea (ROK) have decreased malaria incidence but face challenges due to delayed case detection and response. To improve this, machine learning models for predicting malaria, focusing on high-risk areas, have been developed. Methods: The study targeted the northern region of ROK, near the demilitarized zone, using a 1-km grid to identify areas for prediction. Grid cells without residential buildings were excluded, leaving 8,425 cells. The prediction was based on whether at least one malaria case was reported in each grid cell per month, using spatial data of patient locations. Four algorithms were used: gradient boosted (GBM), generalized linear (GLM), extreme gradient boosted (XGB), and ensemble models, incorporating environmental, sociodemographic, and meteorological data as predictors. The models were trained with data from May to October (2019–2021) and tested with data from May to October 2022. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC). Results: The AUROC of the prediction models performed excellently (GBM = 0.9243, GLM = 0.9060, XGB = 0.9180, and ensemble model = 0.9301). Previous malaria risk, population size, and meteorological factors influenced the model most in GBM and XGB. Conclusion Machine-learning models with properly preprocessed malaria case data can provide reliable predictions. Additional predictors, such as mosquito density, should be included in future studies to improve the performance of models.

Objectives: Severe fever with thrombocytopenia syndrome (SFTS) has no vaccine or treatment and an extremely high fatality rate. We aimed to analyze and evaluate the risk factors for death associated with SFTS. Methods: Among reports from 2018 to 2022, we compared and analyzed 1,034 inpatients aged 18 years or older with laboratory-confirmed SFTS who underwent complete epidemiological investigations. Results: Most of the inpatients with SFTS were aged 50 years or older (average age, 67.6 years). The median time from symptom onset to death was 9 days, and the average case fatality rate was 18.5%. Risk factors for death included age of 70 years or older (odds ratio [OR], 4.82); agriculture-related occupation (OR, 2.01); underlying disease (OR, 7.20); delayed diagnosis (OR, 1.28 per day); decreased level of consciousness (OR, 5.53); fever/chills (OR, 20.52); prolonged activated partial thromboplastin time (OR, 4.19); and elevated levels of aspartate aminotransferase (OR, 2.91), blood urea nitrogen (OR, 2.62), and creatine (OR, 3.21). Conclusion The risk factors for death in patients with SFTS were old age; agriculture-related occupation; underlying disease; delayed clinical suspicion; fever/chills; decreased level of consciousness; and elevated activated partial thromboplastin time, aspartate aminotransferase, blood urea nitrogen, and creatine levels.

The phosphorylated 43-kDa transactive response DNA-binding protein (TDP-43) was identified as a major disease protein in sporadic amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration. We present a case with progressive muscle weakness who was diagnosed with sporadic ALS. On postmortem examination, TDP-43 immunoreactive neuronal cytoplasmic inclusions were noted in motor cortex, hippocampus and anterior horns of spinal cord, which was compatible with ALS-TDP, stage 4. This is the first documented autopsy-confirmed ALS case with ALS-TDP pathology in Korea.

Objective: This study aimed to investigate the impact of baseline values and temporal changes in body composition parameters, including skeletal muscle index (SMI) and visceral adipose tissue area (VAT), measured using serial computed tomography (CT) imaging on the prognosis of operable breast cancers in Asian patients. Materials and Methods: This study retrospectively included 627 Asian female (mean age ± standard deviation [SD], 53.6 ± 8.3 years) who underwent surgery for stage I–III breast cancer between January 2011 and September 2012. Body composition parameters, including SMI and VAT, were semi-automatically calculated on baseline abdominal CT at the time of diagnosis and follow-up CT for post-treatment surveillance. Serial changes in SMI and VAT were calculated as the delta values. Multivariable Cox regression analysis was used to evaluate the association of baseline and delta SMI and VAT values with disease-free survival. Results: Among 627 patients, 56 patients (9.2%) had breast cancer recurrence after a median of 40.5 months. The mean value ± SD of the baseline SMI and baseline VAT were 43.7 ± 5.8 cm2 /m2 and 72.0 ± 46.0 cm2 , respectively. The mean value of the delta SMI was -0.9 cm2 /m2 and the delta VAT was 0.5 cm2 . The baseline SMI and VAT were not significantly associated with disease-free survival (adjusted hazard ratio [HR], 0.983; 95% confidence interval [CI], 0.937–1.031; p = 0.475 and adjusted HR, 1.001; 95% CI, 0.995–1.006; p = 0.751, respectively). The delta SMI and VAT were also not significantly associated with disease-free survival (adjusted HR, 0.894; 95% CI, 0.766–1.043; p = 0.155 and adjusted HR, 1.001; 95% CI, 0.989–1.014; p = 0.848, respectively). Conclusion Our study revealed that baseline and early temporal changes in SMI and VAT were not independent prognostic factors regarding disease-free survival in Asian patients undergoing surgery for breast cancer.

At the request of the authors, the NRF-support number in ‘Acknowledgements’ is modified.

OBJECTIVE: This in-vivo study aimed to compare landmark identification errors in anteroposterior (AP) and posteroanterior (PA) cephalograms generated from cone-beam computed tomography (CBCT) scan data in order to examine the feasibility of using AP cephalograms in clinical settings. METHODS: AP and PA cephalograms were generated from CBCT scans obtained from 25 adults. Four experienced and four inexperienced examiners were selected depending on their experience levels in analyzing frontal cephalograms. They identified six cephalometric landmarks on AP and PA cephalograms. The errors incurred in positioning the cephalometric landmarks on the AP and PA cephalograms were calculated by using the straight-line distance and the horizontal and vertical components as parameters. RESULTS: Comparison of the landmark identification errors in CBCT-generated frontal cephalograms revealed that landmark-dependent differences were greater than experience- or projection-dependent differences. Comparisons of landmark identification errors in the horizontal and vertical directions revealed larger errors in identification of the crista galli and anterior nasal spine in the vertical direction and the menton in the horizontal direction, in comparison with the other landmarks. Comparison of landmark identification errors between the AP and PA projections in CBCT-generated images revealed a slightly higher error rate in the AP projections, with no inter-examiner differences. Statistical testing of the differences in landmark identification errors between AP and PA cephalograms showed no statistically significant differences for all landmarks. CONCLUSIONS: The reproducibility of CBCT-generated AP cephalograms is comparable to that of PA cephalograms; therefore, AP cephalograms can be generated reliably from CBCT scan data in clinical settings.
Adult ; Cone-Beam Computed Tomography* ; Humans ; Spine

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BACKGROUND AND PURPOSE: Visual assessment of medial temporal-lobe atrophy (MTA) has been quick, reliable, and easy to apply in routine clinical practice. However, one of the limitations in visual assessments of MTA is the lack of widely accepted age-adjusted norms and cutoff scores for MTA for a diagnosis of Alzheimer's disease (AD). This study aimed to determine the optimal cutoff score on a T1-weighted axial MTA Visual Rating Scale (VRS) for differentiating patients with AD from cognitively normal elderly people. METHODS: The 3,430 recruited subjects comprising 1,427 with no cognitive impairment (NC) and 2003 AD patients were divided into age ranges of 50–59, 60–69, 70–79, and 80–89 years. Of these, 446 participants (218 in the NC group and 228 in the AD group) were chosen by random sampling for inclusion in this study. Each decade age group included 57 individuals, with the exception of 47 subjects being included in the 80- to 89-year NC group. The scores on the T1-weighted axial MTA VRS were graded by two neurologists. The cutoff values were evaluated from the area under the receiver operating characteristic curve. RESULTS: The optimal axial MTA VRS cutoff score from discriminating AD from NC increased with age: it was ≥as ≥1, ≥2, and ≥3 in subjects aged 50–59, 60–69, 70–79, and 80–89 years, respectively (all p < 0.001). CONCLUSIONS: These results show that the optimal cutoff score on the axial MTA VRS for diagnosing of AD differed according to the decade age group. This information could be of practical usefulness in the clinical setting.
Aged ; Alzheimer Disease* ; Atrophy* ; Cognition Disorders ; Dementia* ; Diagnosis ; Humans ; Korea* ; Pemetrexed ; ROC Curve

OBJECTIVES: The Behavioral Activation of Depression Scale (BADS) has been reported to be a valid tool for assessing the different behavioral aspects of depression, such as activation, rumination or avoidance, and functional impairment. The aim of this study was to assess the reliability and validity of the Korean version of BADS (K-BADS). METHODS: A sample of 196 outpatients completed the K-BADS and the data were analyzed for internal consistency and factor structures. An additional 51 outpatients re-filled the K-BADS after two weeks for the test-retest reliability. To test for the validity, the Hospital Anxiety and Depression Scale (HADS), Working Alliance Inventory (WAI), Drug Attitude Inventory-10 (DAI-10), and Mindfulness Attention Awareness Scale (MAAS) were administered. RESULTS: Internal consistency of K-BADS was good (Cronbach's alpha=0.843) and principal component factor analysis revealed the four-factor structure. The K-BADS showed a reasonable test-retest reliability (r=0.863, p<0.001). The total score of K-BADS correlated significantly with the total scores of the HADS depression (r=−0.694) and HADS anxiety (r=−0.681). No correlations were found between the K-BADS and the K-WAI (r=0.170) and between the K-BADS and the K-DAI-10 (r=0.311). CONCLUSION: The K-BADS is a reliable and valid instrument for measuring the behavioral activation for depression in Korean patients with depressive symptoms.
Anxiety ; Depression* ; Humans ; Mindfulness ; Outpatients ; Reproducibility of Results*

Carbon dioxide (CO2) laser is one of the most widely used lasers in dermatology. CO2 laser can precisely ablate the skin with good hemostasis, which makes it an ideal surgical laser. With the development of pulsed CO2 laser, which enabled cleaner ablation with less residual thermal damage, CO2 laser resurfacing became the gold standard for skin rejuvenation. The rejuvenation effect of full-face CO2 laser resurfacing is unparalleled to other methods; however, it is associated with a relative high incidence of side effects and prolonged downtime. Fractional CO2 laser was developed to overcome this problem. With a new technology of fractionating the laser beam into hundreds of microbeams, fractional CO2 laser resurfacing can improve various skin conditions including skin laxity, photodamage, and acne scars with short downtime and significantly lesser side effects. For optimal treatment results, clinicians have to decide the treatment depth and density based on proper understanding of the laser tissue interaction and underlying skin conditions.
Acne Vulgaris ; Carbon Dioxide* ; Carbon* ; Cicatrix ; Dermatology ; Hemostasis ; Incidence ; Lasers, Gas* ; Rejuvenation ; Skin