Background: Preeclampsia (PE) is a hypertensive pregnancy disorder linked to placental dysfunction, often involving pathological lesions like acute atherosis, decidual vasculopathy, accelerated villous maturation, and fibrinoid deposition. However, there is no gold standard for the pathological diagnosis of PE and this limits the ability of clinicians to distinguish between PE and non-PE pregnancies. Recent advances in computational pathology have provided the opportunity to automate pathological analysis for diagnosis, classification, prediction, and prediction of disease progression. In this study, we assessed whether computational pathology could be used to identify PE placentas. Methods: A total of 168 placental whole-slide images (WSIs) of patients from Seoul National University Hospital (comprising 84 PE cases and 84 normal controls) were used for model development and internal validation. For external validation of the model, 76 placental slides (including 38 PE cases and 38 normal controls) were obtained from the Boramae Medical Center (BMC). To establish standard criteria for diagnosing PE and distinguishing it from controls using placental WSIs, patch characteristics and quantification of terminal and intermediate villi were employed. In unsupervised learning, K-means clustering was conducted as a feature obtained through an Auto Encoder to extract the ratio of each cluster for each WSI. For supervised learning, quantitative assessments of the villi were obtained using a U-Net-based segmentation algorithm. The prediction model was developed using an ensemble method and was compared with a clinical feature model developed by using placental size features. Results: Using ensemble modeling, we developed a model to identify PE placentas.The model showed good performance (area under the precision-recall curve [AUPRC], 0.771; 95% confidence interval [CI], 0.752–0.790), with 77.3% of sensitivity and 71.1% of specificity, whereas the clinical feature model showed an AUPRC 0.713 (95% CI, 0.694–0.732) with 55.6% sensitivity and 86.8% specificity. External validation of the predictive model employing the BMC-derived set of placental slides also showed good discrimination (AUPRC, 0.725; 95% CI, 0.720–0.730). Conclusion The proposed computational pathology model demonstrated a strong ability to identify preeclamptic placentas. Computational pathology has the potential to improve the identification of PE placentas.

Background: The purpose of this study was to evaluate the effect of vanishing twin (VT) on maternal serum marker concentrations and nuchal translucency (NT). Methods: This is a secondary analysis of a multicenter prospective cohort study in 12 institutions. Serum concentrations of pregnancy-associated plasma protein-A in the first trimester and alpha-fetoprotein (AFP), total human chorionic gonadotrophin, unconjugated estriol, and inhibin A in the second trimester were measured, and NT was measured between 10 and 14 weeks of gestation. Results: Among 6,793 pregnant women, 5,381 women were measured for serum markers in the first or second trimester, including 65 cases in the VT group and 5,316 cases in the normal singleton group. The cases in the VT group had a higher median multiple of the median value of AFP and inhibin A than the normal singleton group. The values of other serum markers and NT were not different between the two groups. After the permutation test with adjustment,AFP and inhibin A remained significant differences. The frequency of abnormally increased AFP was also higher in the VT group than in the normal singleton group. Conclusion VT can be considered as an adjustment factor for risk assessment in the secondtrimester serum screening test.

Background/Aims: Hip fracture and acute exacerbation of chronic obstructive pulmonary disease (AE-COPD) could increase mortality in patients with COPD. There are no data on the relationship between AE-COPD and hip fracture, which may significantly affect the prognosis of patients with COPD. Therefore, we conducted this study to determine the effects of AE-COPD on hip fractures in patients with COPD. Methods: This retrospective, nested, case-control study included 253,471 patients with COPD (≥ 40 years of age) identified from the Korea National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) from 2002 to 2015. Among 176,598 patients with COPD, 1,415 patients with hip fractures were identified. Each case was matched to one control for age (within 10 years), sex, and year of COPD diagnosis. We estimated the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for hip fractures associated with AE-COPD using conditional logistic regression analysis, adjusting for underlying diseases and smoking history. Results: In patients with AE-COPD, the risk of hip fracture was 2.50 times higher, regardless of systemic corticosteroid use and underlying disease (aOR, 2.50; 95% CI, 1.67 to 3.75). The risk of hip fracture increased if there was one episode of AE in the year before hip fractures (aOR, 2.25; 95% CI, 1.66 to 3.05). Moreover, the risk of hip fracture also increased in patients with more than two episodes of AE the year before hip fractures (aOR, 2.57; 95% CI, 1.61 to 4.10). Conclusions AE-COPD increases the risk of hip fracture regardless of underlying diseases, including osteoporosis, and treatment with systemic corticosteroids.

An understanding of the knowledges, attitudes and perceptions of different populations is key for public health policy makers. Here, a survey was performed on knowledge, attitudes, and perceptions about malaria diagnosis, prevention, control, and treatment. The 407 survey participants included both uninfected inhabitants and patients from 2 cities (Gimpo- and Paju-si) of Northern Gyeonggi-do, known as high-risk areas for vivax malaria. We used community-based study design and non-probability sampling method using the primary data. Association between variables were tested using χ2-tests. In general, the information on malaria reported by the participants in this study was unsystematic and included inaccurate details. The knowledge of malaria symptoms, identified as headache, chills and fever, was high, but the surveyed community lacks knowledge of the specific medications used for malaria treatment, with a large number of respondents having no knowledge of any form of medication. Survey questions with high correct answer rates included questions about easy treatment of malaria in Korea, the high daytime activity of malaria-borne mosquitoes, and the infection risk posed by outdoor activities. However, a large portion of the respondents was unable to provide simple medical and biological information about the disease. This study aimed to comprehensively evaluate the knowledge, attitude, and practical behavior of the surveyed community with respect to malaria and the implications reported here could be applicable to other malaria endemic areas in Korea.

Purpose: To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). Materials and Methods: A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions.Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. Results: The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. Conclusion The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS.

Background/Aims: Atrial fibrillation (AF)-related stroke accounts for 20% of ischemic strokes. Rivaroxaban use in AF patients for preventing stroke and systemic embolism was approved in 2013 in Korea. This study was to investigate the safety and effectiveness of rivaroxaban use in Korean patients with non-valvular AF in a real-world setting. Methods: This was an analysis of the Korean patients in Xarelto for Prevention of Stroke in Patients with Atrial Fibrillation in Asia-Pacific (XANAP), which was a prospective, observational cohort study including patients with non-valvular AF starting rivaroxaban treatment to prevent stroke or non-central nervous system systemic embolism (non-CNS SE), conducted in 10 Asian countries. Results: A total of 844 patients were enrolled in the Korean portion of the XANAP study. In XANAP Korea, the mean age was 70.1 years and 62.6% were males. The mean CHADS2 score was 2.5 and the mean CHA2DS2-VASc score was 3.8. 47% of the patients had experienced prior stroke or non-CNS SE or transient ischemic attack. 73.6% of the patients had CHADS2 score ≥ 2. Incidence proportions of 0.8% of the patients (1.1 per 100 patient-years) developed adjudicated treatment-emergent major bleeding. Death was observed in 1.2% of the patients. The incidence of non-major bleeding as well as thromboembolic event were 8.4% (11.6 per 100 patient-years) and 1.5% (2.0 per 100 patient-years), respectively. Conclusions This study reaffirmed the consistent safety profile of rivaroxaban. We found consistent results with overall XANAP population for rivaroxaban in terms of safety in non-valvular AF patients for the prevention of stroke and non-CNS SE.

Background/Aims: Atrial fibrillation (AF)-related stroke accounts for 20% of ischemic strokes. Rivaroxaban use in AF patients for preventing stroke and systemic embolism was approved in 2013 in Korea. This study was to investigate the safety and effectiveness of rivaroxaban use in Korean patients with non-valvular AF in a real-world setting. Methods: This was an analysis of the Korean patients in Xarelto for Prevention of Stroke in Patients with Atrial Fibrillation in Asia-Pacific (XANAP), which was a prospective, observational cohort study including patients with non-valvular AF starting rivaroxaban treatment to prevent stroke or non-central nervous system systemic embolism (non-CNS SE), conducted in 10 Asian countries. Results: A total of 844 patients were enrolled in the Korean portion of the XANAP study. In XANAP Korea, the mean age was 70.1 years and 62.6% were males. The mean CHADS2 score was 2.5 and the mean CHA2DS2-VASc score was 3.8. 47% of the patients had experienced prior stroke or non-CNS SE or transient ischemic attack. 73.6% of the patients had CHADS2 score ≥ 2. Incidence proportions of 0.8% of the patients (1.1 per 100 patient-years) developed adjudicated treatment-emergent major bleeding. Death was observed in 1.2% of the patients. The incidence of non-major bleeding as well as thromboembolic event were 8.4% (11.6 per 100 patient-years) and 1.5% (2.0 per 100 patient-years), respectively. Conclusions This study reaffirmed the consistent safety profile of rivaroxaban. We found consistent results with overall XANAP population for rivaroxaban in terms of safety in non-valvular AF patients for the prevention of stroke and non-CNS SE.

Purpose: To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). Materials and Methods: A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions.Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. Results: The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. Conclusion The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS.

BACKGROUND: Twin-to-twin transfusion syndrome (TTTS) is a serious complication of monochorionic twin pregnancies. It results from disproportionate blood supply to each fetus caused by abnormal vascular anastomosis within the placenta. Amniotic fluid (AF) is an indicator reflecting the various conditions of the fetus, and an imbalance in AF volume is essential for the antenatal diagnosis of TTTS by ultrasound. In this study, two different mass spectrometry quantitative approaches were performed to identify differentially expressed proteins (DEPs) within matched pairs of AF samples.METHODS: We characterized the AF proteome in pooled AF samples collected from donor and recipient twin pairs (n = 5 each) with TTTS by a global proteomics profiling approach and then preformed the statistical analysis to determine the DEPs between the two groups. Next, we carried out a targeted proteomic approach (multiple reaction monitoring) with DEPs to achieve high-confident TTTS-associated AF proteins.RESULTS: A total of 103 AF proteins that were significantly altered in their abundances between donor and recipient fetuses. The majority of upregulated proteins identified in the recipient twins (including carbonic anhydrase 1, fibrinogen alpha chain, aminopeptidase N, alpha-fetoprotein, fibrinogen gamma chain, and basement membrane-specific heparan sulfate proteoglycan core protein) have been associated with cardiac or dermatologic disease, which is often seen in recipient twins as a result of volume overload. In contrast, proteins significantly upregulated in AF collected from donor twins (including IgGFc-binding protein, apolipoprotein C-I, complement C1q subcomponent subunit B, apolipoprotein C-III, apolipoprotein A-II, decorin, alpha-2-macroglobulin, apolipoprotein A-I, and fibronectin) were those previously shown to be associated with inflammation, ischemic cardiovascular complications or renal disease.CONCLUSION: In this study, we identified proteomic biomarkers in AF collected from donor and recipient twins in pregnancies complicated by TTTS that appear to reflect underlying functional and pathophysiological challenges faced by each of the fetuses.

Background: Nonalcoholic fatty liver disease (NAFLD) is now considered as a hepatic manifestation of metabolic syndrome and elevated alanine aminotransferase (ALT) is commonly related to NAFLD in the absence of viral hepatitis or alcohol abuse. Previous studies have indicated that elevated ALT is associated with diabetes or metabolic syndrome in adults, but the clinical significance of ALT or NAFLD in pregnancy has not been well determined. The objective of this study was to determine the association between elevated ALT in early pregnancy and the development of gestational diabetes or preeclampsia in late pregnancy. Methods: In this retrospective cohort study, pregnant women who met the following inclusion criteria were included: 1) singleton pregnancy; 2) ALT levels were measured in antenatal outpatient clinic at 4–20 weeks of gestation; 3) patients were screened for gestational diabetes and delivered in Cheil General Hospital and Women's Healthcare Center. Cases with viral hepatitis or other liver diseases were excluded. The early ALT levels were divided into two groups (normal ALT [≤ 95th percentile] and elevated ALT [> 95th percentile]), and the frequency of gestational diabetes and preeclampsia was compared between the two groups of cases. Gestational diabetes was screened and diagnosed by two-step procedure (50 g oral glucose challenge test and 75 g glucose challenge test with World Health Organization [WHO] criteria). Results: A total of 2,322 women met the inclusion criteria. Cases with elevated early ALT levels (> 95th percentile) had a higher risk of subsequent gestational diabetes and preeclampsia (gestational diabetes by WHO criteria, 2.1% in normal ALT vs. 6.5% in elevated ALT, P < 0.01; preeclampsia, 1.0% in normal ALT vs. 4.1% in elevated ALT, P < 0.05). This relationship between elevated ALT and increased risk of gestational diabetes/preeclampsia remained significant after adjustment for maternal age and pre-pregnancy body mass index. Conclusion Elevated unexplained ALT in early pregnancy is associated with the risk of subsequent development of gestational diabetes and preeclampsia in late pregnancy.