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Objectives: Electrocardiography (ECG)-based diagnosis by experts cannot maintain uniform quality because individual differences may occur. Previous public databases can be used for clinical studies, but there is no common standard that would allow databases to be combined. For this reason, it is difficult to conduct research that derives results by combining databases. Recent commercial ECG machines offer diagnoses similar to those of a physician. Therefore, the purpose of this study was to construct a standardized ECG database using computerized diagnoses.Methods: The constructed database was standardized using Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and Observational Medical Outcomes Partnership–common data model (OMOP-CDM), and data were then categorized into 10 groups based on the Minnesota classification. In addition, to extract high-quality waveforms, poor-quality ECGs were removed, and database bias was minimized by extracting at least 2,000 cases for each group. To check database quality, the difference in baseline displacement according to whether poor ECGs were removed was analyzed, and the usefulness of the database was verified with seven classification models using waveforms.Results: The standardized KURIAS-ECG database consists of high-quality ECGs from 13,862 patients, with about 20,000 data points, making it possible to obtain more than 2,000 for each Minnesota classification. An artificial intelligence classification model using the data extracted through SNOMED-CT showed an average accuracy of 88.03%.Conclusions: The KURIAS-ECG database contains standardized ECG data extracted from various machines. The proposed protocol should promote cardiovascular disease research using big data and artificial intelligence.

Purpose: The study aimed to examine whether prophylactic surfactant replacement therapy (SRT) with less invasive surfactant administration (LISA) by tracheal catheterization in a group of spontaneously breathing preterm infants would improve clinical outcomes compared to prophylactic SRT with the INtubation-SURfactantExtubation (INSURE) method.Methods: We compared 20 spontaneously breathing preterm infants, 25 to 29 weeks of gestation or with a birth weight of less than 1,250 g, treated with prophylactic SRT using a gastric tube (LISA group), to the 20 spontaneously breathing preterm infants matched by gestational age and birth weight, managed with prophylactic SRT via the INSURE method (INSURE group, historical control).Results: The LISA group had lower rates of mechanical ventilation (MV) 72 hours after birth (P=0.019) and at any time (P=0.025), lower frequency of bradycardia during SRT (P=0.031), and lower median duration of MV than the INSURE group (P=0.038). In multivariate analysis, the LISA method was associated with a significantly lower likelihood of receiving invasive ventilation during hospitalization (odds ratio [OR], 0.029; 95% confidence interval [CI], 0.001 to 0.938; P=0.046) and a decreased frequency of bradycardia during SRT (OR, 0.020; 95% CI, 0.001 to 0.535; P=0.020) as compared to the INSURE method.Conclusion: Prophylactic SRT using LISA via tracheal catheterization in preterm infants may significantly reduce exposure to MV during hospitalization and bradycardia during surfactant administration.

BackgroundOlder patients who treated by percutaneous coronary intervention (PCI) are at a higher risk of adverse cardiac outcomes. We sought to investigate the clinical impact of bifurcation PCI in older patients from Korea and Italy.MethodsWe selected 5,537 patients who underwent bifurcation PCI from the BIFURCAT (comBined Insights from the Unified RAIN and COBIS bifurcAtion regisTries) database. The primary outcome was a composite of target vessel myocardial infarction, clinically driven target lesion revascularization, and stent thrombosis at two years.ResultsIn patients aged ≥75 years, the mean age was 80.1 ± 4.0 years, 65.2% were men, and 33.7% had diabetes. Older patients more frequently presented with chronic kidney disease (CKD), severe coronary calcification, and left main coronary artery disease (LMCA). During a median follow-up of 2.1 years, older patients showed similar adverse clinical outcomes compared to younger patients (the primary outcome, 5.7% vs. 4.5%; p = 0.21). Advanced age was not an independent predictor of the primary outcome (p = 0.93) in overall patients. Both CKD and LMCA were independent predictors regardless of age group.ConclusionsOlder patients (≥75 years) showed similar clinical outcomes to those of younger patients after bifurcation PCI. Advanced age alone should not deter physicians from performing complex PCIs for bifurcation disease.

Ticagrelor-based dual antiplatelet therapy (TDAPT) provides potent antiplatelet inhibition but may increase the bleeding risk in Asian populations. We investigated the impact of the early use of low-dose TDAPT (l-TDAPT; 120 mg) on clinical outcomes in Korean patients undergoing percutaneous coronary intervention (PCI). A multicenter prospective clinical cohort study was conducted with patients on standard-dose TDAPT (s-TDAPT; 180 mg) after PCI for complex lesions. A major adverse cardiovascular event (MACE) was defined as a composite of cardiovascular death, myocardial infarction, stroke, and repeat revascularization. A net clinical event (NCE) was defined as a composite of bleeding events and MACEs. Among the 772 patients on s-TDAPT, 115 (14.8%) switched to l-TDAPT within 6 months. Common reasons for the regimen changes were switching as planned (38.8%), dyspnea (25.5%), and bleeding (23.6%). A multivariate Cox proportional hazard model (CPH) showed that the risks of MACE, bleeding events, and NCE were not different between the l-TDAPT and s-TDAPT groups during the entire follow-up period and beyond 6 months after PCI. Multivariate time-varying CPH also showed similar results. De-escalation with low-dose ticagrelor within 6 months after PCI is feasible and safe even in patients with complex lesions harboring a high ischemic event risk.

BackgroundDiabetes mellitus (DM) is a critical risk factor for the pathogenesis and progression of coronary artery disease, with a higher prevalence of complex coronary artery disease, including bifurcation lesions. This study aimed to elucidate the optimal stenting strategy for coronary bifurcation lesions in patients with DM.MethodsA total of 905 patients with DM and bifurcation lesions treated with second-generation drug-eluting stents (DES) from a multicenter retrospective patient cohort were analyzed. The primary outcome was the 5-year incidence of target lesion failure (TLF), which was defined as a composite of cardiac death, target vessel myocardial infarction, and target lesion revascularization.ResultsAmong all patients with DM with significant bifurcation lesions, 729 (80.6%) and 176 (19.4%) were treated with one- and two-stent strategies, respectively. TLF incidence differed according to the stenting strategy during the mean follow-up of 42 ± 20 months. Among the stent strategies, T- and V-stents were associated with a higher TLF incidence than one-stent strategy (24.0 vs. 7.3%, p < 0.001), whereas no difference was observed in TLF between the one-stent strategy and crush or culotte technique (7.3 vs. 5.9%, p = 0.645). The T- or V-stent technique was an independent predictor of TLF in multivariate analysis (hazard ratio, 3.592; 95% confidence interval, 2.117–6.095; p < 0.001). Chronic kidney disease, reduced left ventricular ejection fraction, and left main bifurcation were independent predictors of TLF in patients with DM.ConclusionT- or V-stenting in patients with DM resulted in increased cardiovascular events after second-generation DES implantation.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03068494?term=03068494&draw=2&rank=1, identifier: NCT03068494.

Background Acute appendicitis often presents with vague abdominal pain, which fosters diagnostic challenges to clinicians regarding early detection and proper intervention. This is even more problematic with individuals with severe psychiatric disorders who have reduced sensitivity to pain due to long-term or excessive medication use or disturbed bodily sensation perceptions. This study aimed to determine whether psychiatric disorder, psychotropic prescription, and treatment compliance increase the risks of complicated acute appendicitis. Methods The diagnosis records of acute appendicitis from four university hospitals in Korea were investigated from 2002 to 2020. A total of 47,500 acute appendicitis-affected participants were divided into groups with complicated and uncomplicated appendicitis to determine whether any of the groups had more cases of psychiatric disorder diagnoses. Further, the ratio of complicated compared to uncomplicated appendicitis in the mentally ill group was calculated regarding psychotropic dose, prescription duration, and treatment compliance. Results After adjusting for age and sex, presence of psychotic disorder (odds ratio [OR]: 1.951; 95% confidence interval [CI]: 1.218–3.125), and bipolar disorder (OR: 2.323; 95% CI: 1.194–4.520) was associated with a higher risk of having complicated appendicitis compared with absence of psychiatric disorders. Patients who are taking high-daily-dose antipsychotics, regardless of prescription duration, show high complicated appendicitis risks; High-dose antipsychotics for Conclusions This study revealed a close relationship in the possibility of complicated appendicitis in patients with severe psychiatric disorders, including psychotic and bipolar disorders. The effect on complicated appendicitis was more remarkable by the psychiatric disease entity itself than by psychotropic prescription patterns. Good treatment compliance and regular visit may reduce the morbidity of complicated appendicitis in patients with psychiatric disorders.

Background: Metabolic syndrome (MetS) is closely associated with the aging process. However, changes in metabolic conditions and cardiac function that occur in middle aged population remain unclear. We evaluated longitudinal changes in metabolic parameters and cardiac function during a 3-year period in subjects with suspected MetS.Methods: We studied 191 participants with suspected MetS at baseline and after 3 years. Anthropometric parameters, including waist circumference (WC), and metabolic parameters, including fasting blood glucose and lipid profile were measured. Conventional echocardiography with two-dimensional speckle tracking was performed.Results: Mean age was 56.2±4.4 years, and there were 97 women (50.8%). Men had increased WC and triglycerides (TG) (WC 91.2±6.8 cm vs. 84.0±8.0 cm, P

Background A computerized 12-lead electrocardiogram (ECG) can automatically generate diagnostic statements, which are helpful for clinical purposes. Standardization is required for big data analysis when using ECG data generated by different interpretation algorithms. The common data model (CDM) is a standard schema designed to overcome heterogeneity between medical data. Diagnostic statements usually contain multiple CDM concepts and also include non-essential noise information, which should be removed during CDM conversion. Existing CDM conversion tools have several limitations, such as the requirement for manual validation, inability to extract multiple CDM concepts, and inadequate noise removal. Objectives We aim to develop a fully automated text data conversion algorithm that overcomes limitations of existing tools and manual conversion. Methods We used interpretations printed by 12-lead resting ECG tests from three different vendors: GE Medical Systems, Philips Medical Systems, and Nihon Kohden. For automatic mapping, we first constructed an ontology-lexicon of ECG interpretations. After clinical coding, an optimized tool for converting ECG interpretation to CDM terminology is developed using term-based text processing. Results Using the ontology-lexicon, the cosine similarity-based algorithm and rule-based hierarchical algorithm showed comparable conversion accuracy (97.8 and 99.6%, respectively), while an integrated algorithm based on a heuristic approach, ECG2CDM, demonstrated superior performance (99.9%) for datasets from three major vendors. Conclusion We developed a user-friendly software that runs the ECG2CDM algorithm that is easy to use even if the user is not familiar with CDM or medical terminology. We propose that automated algorithms can be helpful for further big data analysis with an integrated and standardized ECG dataset.

Owing to the prevalence of the coronavirus disease (COVID-19), coping with clinical issues at the individual level has become important to the healthcare system. Accordingly, precise initiation of treatment after a hospital visit is required for expedited processes and effective diagnoses of outpatients. To achieve this, artificial intelligence in medical natural language processing (NLP), such as a healthcare chatbot or a clinical decision support system, can be suitable tools for an advanced clinical system. Furthermore, support for decisions on the medical specialty from the initial visit can be helpful.In this study, we propose a medical specialty prediction model from patient-side medical question text based on pre-trained bidirectional encoder representations from transformers (BERT). The dataset comprised pairs of medical question texts and labeled specialties scraped from a website for the medical question-and-answer service. The model was fine-tuned for predicting the required medical specialty labels among 27 labels from medical question texts. To demonstrate the feasibility, we conducted experiments on a real-world dataset and elaborately evaluated the predictive performance compared with four deep learning NLP models through cross-validation and test set evaluation.The proposed model showed improved performance compared with competitive models in terms of overall specialties. In addition, we demonstrate the usefulness of the proposed model by performing case studies for visualization applications.The proposed model can benefit hospital patient management and reasonable recommendations for specialties for patients.

A limitation of the current guidelines regarding the timing of invasive coronary angiography for patients with non-ST-segment elevation acute coronary syndrome is the randomization time. To date, no study has reported the clinical outcomes of invasive strategy timing on the basis of the time of symptom onset.The aim of this study was to investigate the effect of invasive strategy timing from the time of symptom onset on the 3-year clinical outcomes of patients with non-ST-segment elevation myocardial infarction (NSTEMI).Among 13,104 patients from the Korea Acute Myocardial Infarction Registry-National Institutes of Health, 5,856 patients with NSTE myocardial infarction were evaluated. The patients were categorized according to symptom-to-catheter (StC) time (48 or ≥48 hours). The primary outcome was 3-year all-cause mortality.Overall, 3,919 patients (66.9%) were classified into the StC time 48 hours group. This group had lower all-cause mortality than the group with StC time ≥48 hours (7.3% vs 13.4%; P 0.001). The lower risk for all-cause mortality in the group with StC time 48 hours group was consistent in all subgroups. Notably, emergency medical service use (HR: 0.31; 95% CI: 0.19-0.52) showed a lower risk for all-cause mortality than no emergency medical service use (HR: 0.54; 95% CI: 0.46-0.65; P value for interaction = 0.008).An early invasive strategy on the basis of StC time was associated with a decreased risk for all-cause mortality in patients with NSTEMI. Because the study was based on a prospective registry, the results should be considered hypothesis generating, highlighting the need for further research. (iCReaT Study No. C110016).

BackgroundChronic kidney disease (CKD) is a strong risk factor for cardiovascular disease. Electrocardiogram (ECG) is the basic test for screening cardiovascular disease. However, the impact of ECG abnormalities on cardiovascular prognosis in patients with CKD is largely unknown.MethodsA total of 1,295 patients with CKD (stage 3, 4, and 5) who underwent ECG between 2013 and 2015 were selected from the tertiary hospital in Korea. ECG abnormalities were defined using the Minnesota classification. Five-year major adverse cerebrocardiovascular event (MACCE), a composite of death, myocardial infarction (MI) and stroke, was analyzed after excluding 251 patients (n=1,044) with prior MI or stroke.ResultsThe higher the CKD stage, the higher the proportion of patients with a major ECG abnormality. Five-year MACCE incidences were 34%, 23.9%, and 21.7% in patients with major, minor and no ECG abnormalities. MACCE and MI incidences were significantly higher in patients with severe ECG abnormalities (log-rank p < 0.001). Major ECG abnormalities were significantly associated with MACCE (adjusted HR 1.48, 95% CI 1.11-1.97). In particular, atrial fibrillation, atrial premature complex, and QT interval prolongation were identified as important ECG diagnoses. The accuracy of cardiovascular risk stratification was improved when ECG diagnosis was added to the conventional SCORE model (net reclassification index 0.09).ConclusionsMajor ECG abnormality was a significant predictor of cardiovascular events in CKD patients. ECG diagnosis can be useful in evaluating the risk of cardiovascular disease in CKD patients when applied in addition to the conventional risk stratification model.

Background: Identification of subclinical target organ damage (TOD) at early stage is important for the reduction in cardiovascular risk. This study was performed to assess the association between ...

Background Hypertriglyceridemia is an important feature of dyslipidemia in type 1 and type 2 diabetic patients and associated with the development of atherosclerotic cardiovascular disease. Recently, variability of lipid profile has been suggested as a residual risk factor for cardiovascular disease. This study compared the clinical impact of serum triglyceride variability, and their cumulative exposure estimates on cardiovascular prognosis in diabetic patients. Methods A total of 25,933 diabetic patients who had serum triglyceride levels measured at least 3 times and did not have underlying malignancy, myocardial infarction (MI), and stroke during the initial 3 years (modeling phase) were selected from three tertiary hospitals. They were divided into a high/low group depending on their coefficient of variation (CV) and cumulative exposure estimate (CEE). Incidence of major adverse event (MAE), a composite of all-cause death, MI, and stroke during the following 5 years were compared between groups by multivariable analysis after propensity score matching. Results Although there was a slight difference, both the high CV group and the high CEE group had a higher cardiovascular risk profile including male-dominance, smoking, alcohol, dyslipidemia, and chronic kidney disease compared to the low groups. After the propensity score matching, the high CV group showed higher MAE incidence compared to the low CV group (9.1% vs 7.7%, p = 0.01). In contrast, there was no significant difference of MAE incidence between the high CEE group and the low CEE group (8.6% vs 9.1%, p = 0.44). After the multivariable analysis with further adjustment for potential residual confounding factors, the high CV was suggested as an independent risk predictor for MAE (HR 1.19 [95% CI 1.03–1.37]). Conclusion Visit-to-visit variability of triglyceride rather than their cumulative exposure is more strongly related to the incidence of MAE in diabetic patients.

With advances in deep learning and natural language processing (NLP), the analysis of medical texts is becoming increasingly important. Nonetheless, despite the importance of processing medical texts, no research on Korean medical-specific language models has been conducted. The Korean medical text is highly difficult to analyze because of the agglutinative characteristics of the language, as well as the complex terminologies in the medical domain. To solve this problem, we collected a Korean medical corpus and used it to train the language models. In this paper, we present a Korean medical language model based on deep learning NLP. The model was trained using the pre-training framework of BERT for the medical context based on a state-of-the-art Korean language model. The pre-trained model showed increased accuracies of 0.147 and 0.148 for the masked language model with next sentence prediction. In the intrinsic evaluation, the next sentence prediction accuracy improved by 0.258, which is a remarkable enhancement. In addition, the extrinsic evaluation of Korean medical semantic textual similarity data showed a 0.046 increase in the Pearson correlation, and the evaluation for the Korean medical named entity recognition showed a 0.053 increase in the F1-score.

Background: Decreased TIMI flow following percutaneous coronary intervention (PCI) is associated with poor clinical outcomes. However, predicting slow TIMI flow after PCI is limited. Herein, we investigated predicting slow TIMI flow based on the lipid core burden (LCB) of target lesion by using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). Methods and Results: This study retrospectively evaluated 636 patients who underwent NIRS-IVUS guided PCI from a single tertiary center registry. Total patients were divided into decreased TIMI flow group (n=90, TIMI 0, 1, and 2) and normal TIMI flow group (n=546, TIMI 3). The extent of LCB in the treatment zone was calculated as the maximal LCB index (maxLCBi) measured by NIRS for each of the 4-mm longitudinal segments in the treatment zone. In three-month composite events including all-cause death, myocardial infarction, stent thrombosis, and re-intervention, decreased TIMI flow group showed worse clinical outcomes compared to normal TIMI flow group (5.6% vs. 1.5%, log-rank p=0.010). To investigate the correlation between TIMI flow and lipid core burden, a receiver-operating characteristic analysis was performed, and a high LCBi group was defined as maxLCBi 4mm ≥353. Multivariate logistic regression analysis revealed that high LCBi group was strongly associated with decreased TIMI flow (OR 2.223, 95% CI 1.341-3.685, p=0.002). Conclusions: High LCBi measured by NIRS-IVUS could be considered an independent predictor for decreased TIMI flow. Furthermore, a high value for LCBi could lead to worse clinical outcomes.

Background and aims Metabolic syndrome (MetS) is a cluster of multiple risk factors including central obesity that may lead to cardiac damage and cardiovascular events. We investigated whether visceral obesity induces cardiac structural and functional remodeling independently from central obesity and other risk factors in subjects with suspected MetS. Methods and results We studied 229 participants with suspected MetS. Visceral fat area (VFA) was measured by bioelectrical impedance analysis. Left ventricular (LV) mass index, early diastolic velocity of mitral annulus (e′), and LV global longitudinal strain (GLS) were measured by echocardiography. Subjects were categorized into high and low VFA group (VFAh and VFAl). MetS was more prevalent in the VFAh than in the VFAl (p = 0.004). The VFAh had a higher waist circumference (WC) than the VFAl (p Conclusions Visceral obesity assessed by VFA was well correlated with parameters of MetS. Visceral obesity, but not central obesity measured by WC, was independently associated with structural and functional cardiac remodeling in subjects with suspected MetS. It suggests that visceral obesity should be considered as an important risk factor for cardiac damage in dysmetabolic subjects. Trial registration NCT02077530 (date of registration: November 1, 2013).

Chronic kidney disease (CKD) is a strong risk factor for cardiovascular disease. An electrocardiogram (ECG) is a basic test for screening cardiovascular disease. However, the impact of ECG abnormalities on cardiovascular prognosis in patients with CKD is largely unknown. A total of 2442 patients with CKD (stages 3–5) who underwent ECG between 2013 and 2015 were selected from the electronic health record database of the Korea University Anam Hospital. ECG abnormalities were defined using the Minnesota classification. The five-year major adverse cerebrocardiovascular event (MACCE), the composite of death, myocardial infarction (MI), and stroke were analyzed. The five-year incidences for MACCE were 27.7%, 20.8%, and 17.2% in patients with no, minor, and major ECG abnormality (p < 0.01). Kaplan–Meier curves also showed the highest incidence of MI, death, and MACCE in patients with major ECG abnormality. Multivariable Cox regression analysis revealed age, sex, diabetes, CKD stage, hsCRP, antipsychotic use, and major ECG abnormality as independent risk predictors for MACCE (adjusted HR of major ECG abnormality: 1.39, 95% CI: 1.09–1.76, p < 01). Among the detailed ECG diagnoses, sinus tachycardia, myocardial ischemia, atrial premature complex, and right axis deviation were proposed as important ECG diagnoses. The accuracy of cardiovascular risk stratification was improved when the ECG results were added to the conventional SCORE model (net reclassification index 0.07). ECG helps to predict future cerebrocardiovascular events in CKD patients. ECG diagnosis can be useful for cardiovascular risk evaluation in CKD patients when applied in addition to the conventional risk stratification model.

Decreased thrombolysis in myocardial infarction (TIMI) flow is associated with poor clinical outcomes. However, its predictors are not fully known. A combination of near-infrared spectroscopy (NIRS) and intravascular ultrasound (IVUS) could be used to detect lesions at high risk of slow TIMI flow. This study evaluated 636 consecutive patients undergoing target-lesion NIRS-IVUS imaging prior to percutaneous coronary intervention (PCI). The maximal lipid core burden index over 4-mm segments (maxLCBI4mm) per target vessel was calculated. The primary endpoint was the association between maxLCBI4mm and post-interventional TIMI flow. A high lipid core burden index (LCBI) cut-off point was determined using receiver-operating characteristic analysis. Decreased TIMI flow (TIMI less than 3) occurred in 90 patients and normal TIMI flow in 546 patients. The decreased TIMI flow group showed significantly higher incidence of cardiovascular events (5.6% vs. 1.5%, log-rank p = 0.010) in three months of composite events including cardiac death, myocardial infarction, stent thrombosis, and target lesion revascularization. In multivariable analysis, a high LCBI (≥354) was independently associated with slow TIMI flow (OR, 2.59 (95% CI, 1.33–5.04), p = 0.005). High LCBI measured using NIRS-IVUS imaging was an independent predictor of decreased post-PCI TIMI flow. Performing PCI for high-LCBI lesions may necessitate adjunctive measures to prevent suboptimal post-PCI reperfusion.

BACKGROUND With advances in deep learning and natural language processing, analyzing medical texts is becoming increasingly important. Nonetheless, a study on medical-specific language models has not yet been conducted given the importance of medical texts. OBJECTIVE Korean medical text is highly difficult to analyze because of the agglutinative characteristics of the language as well as the complex terminologies in the medical domain. To solve this problem, we collected a Korean medical corpus and used it to train language models. METHODS In this paper, we present a Korean medical language model based on deep learning natural language processing. The proposed model was trained using the pre-training framework of BERT for the medical context based on a state-of-the-art Korean language model. RESULTS After pre-training, the proposed method showed increased accuracies of 0.147 and 0.148 for the masked language model with next sentence prediction. In the intrinsic evaluation, the next sentence prediction accuracy improved by 0.258, which is a remarkable enhancement. In addition, the extrinsic evaluation of Korean medical semantic textual similarity data showed a 0.046 increase in the Pearson correlation. CONCLUSIONS The results demonstrated the superiority of the proposed model for Korean medical natural language processing. We expect that our proposed model can be extended for application to various languages and domains.

The generation of mature ventricular cardiomyocytes (CMs) resembling adult CMs from human pluripotent stem cells (hPSCs) is necessary for disease modeling and drug discovery. To investigate the effect of self-organizing capacity on the generation of mature cardiac organoids (COs), we generated cardiac mesoderm cell-derived COs (CMC-COs) and CM-derived COs (CM-COs) and evaluated COs. CMC-COs exhibited more organized sarcomere structures and mitochondria, well-arranged t-tubule structures, and evenly distributed intercalated discs. Increased expressions of ventricular CM, cardiac metabolic, t-tubule formation, K+ ion channel, and junctional markers were confirmed in CMC-COs. Mature ventricular-like function such as faster motion vector speed, decreased beats per min, increased peak-to-peak duration, and prolonged APD50 and APD90 were observed in CMC-COs. Transcriptional profiling revealed that extracellular matrix-integrin, focal adhesion, and LEFTY-PITX2 signaling pathways are upregulated in CMC-COs. LEFTY knockdown affected ECM-integrin-FA signaling pathways in CMC-COs. Here, we found that high self-organizing capacity of CMCs is critical for the generation of mature and ventricular COs. We also demonstrated that LEFTY-PITX2 signaling plays key roles for CM maturation and specification into ventricular-like CM subtype in CMC-COs. CMC-COs are an attractive resource for disease modeling and drug discovery.

Background The fact that medical terms require special expertise and are becoming increasingly complex makes it difficult to employ natural language processing techniques in medical informatics. Several human-validated reference standards for medical terms have been developed to evaluate word embedding models using the semantic similarity and relatedness of medical word pairs. However, there are very few reference standards in non-English languages. In addition, because the existing reference standards were developed a long time ago, there is a need to develop an updated standard to represent recent findings in medical sciences. Objective We propose a new Korean word pair reference set to verify embedding models. Methods From January 2010 to December 2020, 518 medical textbooks, 72,844 health information news, and 15,698 medical research articles were collected, and the top 10,000 medical terms were selected to develop medical word pairs. Attending physicians (n=16) participated in the verification of the developed set with 607 word pairs. Results The proportion of word pairs answered by all participants was 90.8% (551/607) for the similarity task and 86.5% (525/605) for the relatedness task. The similarity and relatedness of the word pair showed a high correlation (ρ=0.70, P Conclusions Korean medical word pair reference standard sets for semantic similarity and relatedness were developed based on medical documents from the past 10 years. It is expected that our word pair reference sets will be actively utilized in the development of medical and multilingual natural language processing technology in the future.

BACKGROUND The fact that medical terms require special expertise and are becoming increasingly complex makes it difficult to employ natural language processing techniques in medical informatics. Several human-validated reference standards for medical terms have been developed to evaluate word embedding models using the semantic similarity and relatedness of medical word pairs. However, there are very few reference standards in non-English languages. In addition, because the existing reference standards were developed a long time ago, there is a need to develop an updated standard to represent recent findings in medical sciences. OBJECTIVE We propose a new Korean word pair reference set to verify embedding models. METHODS From January 2010 to December 2020, 518 medical textbooks, 72,844 health information news, and 15,698 medical research articles were collected, and the top 10,000 medical terms were selected to develop medical word pairs. Attending physicians (n=16) participated in the verification of the developed set with 607 word pairs. RESULTS The proportion of word pairs answered by all participants was 90.8% (551/607) for the similarity task and 86.5% (525/605) for the relatedness task. The similarity and relatedness of the word pair showed a high correlation (ρ=0.70, Pρ=0.12 vs with medical text for the similarity task, ρ=0.47; namu, ρ=0.02 vs with medical text for the relatedness task, ρ=0.30). CONCLUSIONS Korean medical word pair reference standard sets for semantic similarity and relatedness were developed based on medical documents from the past 10 years. It is expected that our word pair reference sets will be actively utilized in the development of medical and multilingual natural language processing technology in the future. CLINICALTRIAL

An increase in antibiotic usage is considered to attribute to the emergence of antimicrobial resistance. Although experts are counting on the antimicrobial stewardship programs to reduce antibiotic usage, their effect remains uncertain. In this study, we aimed to evaluate the impact of antibiotic usage and forecast the prevalence of hospital-acquired extended spectrum β-lactamase (ESBL) - producing Escherichia coli (E. coli) using time-series analysis. Antimicrobial culture information of E. coli was obtained using a text processing technique that helped extract free-text electronic health records from standardized data. The antimicrobial use density (AUD) of antibiotics of interest was used to estimate the quarterly antibiotic usage. Transfer function model was applied to forecast relationship between antibiotic usage and ESBL-producing E. coli. Of the 1,938 hospital-acquired isolates, 831 isolates (42.9%) were ESBL-producing E. coli. Both the proportion of ESBL-producing E. coli and AUD increased over time. The transfer model predicted that ciprofloxacin AUD is related to the proportion of ESBL-producing E. coli two quarters later. In conclusion, excessive use of antibiotics was shown to affect the prevalence of resistant organisms in the future. Therefore, the control of antibiotics with antimicrobial stewardship programs should be considered to restrict antimicrobial resistance.

Although lowering low-density lipoprotein cholesterol (LDL-C) levels following acute myocardial infarction (MI) is the cornerstone of secondary prevention, the attainment of recommended LDL-C goals remains suboptimal in real-world practice. We sought to investigate recurrent adverse events in post-MI patients. From the Korea Acute Myocardial Infarction-National Institutes of Health registry, a total of 5049 patients with both measurements of plasma LDL-C levels at index admission and at the one-year follow-up visit were identified. Patients who achieved an LDL-C reduction ≥ 50% from the index MI and an LDL-C level ≤ 70 mg/dL at follow-up were classified as target LDL-C achievers. The primary endpoint was a two-year major adverse cardiac and cerebrovascular event (MACCE), including cardiovascular mortality, recurrent MI, and ischemic stroke. Among the 5049 patients, 1114 (22.1%) patients achieved the target LDL-C level. During a median follow-up of 2.1 years, target LDL-C achievers showed a significantly lower incidence (2.2% vs. 3.5%, log-rank p = 0.022) and a reduced adjusted hazard of MACCE (0.63; p = 0.041). In patients with acute MI, achieving a target LDL-C level was associated with a lower incidence and a reduced hazard of recurrent clinical events. These results highlight the need to improve current practices for managing LDL-C levels in real-world settings.

Pathology reports contain the essential data for both clinical and research purposes. However, the extraction of meaningful, qualitative data from the original document is difficult due to the narrative and complex nature of such reports. Keyword extraction for pathology reports is necessary to summarize the informative text and reduce intensive time consumption. In this study, we employed a deep learning model for the natural language process to extract keywords from pathology reports and presented the supervised keyword extraction algorithm. We considered three types of pathological keywords, namely specimen, procedure, and pathology types. We compared the performance of the present algorithm with the conventional keyword extraction methods on the 3115 pathology reports that were manually labeled by professional pathologists. Additionally, we applied the present algorithm to 36,014 unlabeled pathology reports and analysed the extracted keywords with biomedical vocabulary sets. The results demonstrated the suitability of our model for practical application in extracting important data from pathology reports.

BACKGROUND Existing bacterial culture test results for infectious diseases are written in unrefined text, resulting in many problems, including typographical errors and stop words. Effective spelling correction processes are needed to ensure the accuracy and reliability of data for the study of infectious diseases, including medical terminology extraction. If a dictionary is established, spelling algorithms using edit distance are efficient. However, in the absence of a dictionary, traditional spelling correction algorithms that utilize only edit distances have limitations. OBJECTIVE In this research, we proposed a similarity-based spelling correction algorithm using pretrained word embedding with the BioWordVec technique. This method uses a character-level N-grams–based distributed representation through unsupervised learning rather than the existing rule-based method. In other words, we propose a framework that detects and corrects typographical errors when a dictionary is not in place. METHODS For detected typographical errors not mapped to Systematized Nomenclature of Medicine (SNOMED) clinical terms, a correction candidate group with high similarity considering the edit distance was generated using pretrained word embedding from the clinical database. From the embedding matrix in which the vocabulary is arranged in descending order according to frequency, a grid search was used to search for candidate groups of similar words. Thereafter, the correction candidate words were ranked in consideration of the frequency of the words, and the typographical errors were finally corrected according to the ranking. RESULTS Bacterial identification words were extracted from 27,544 bacterial culture and antimicrobial susceptibility reports, and 16 types of spelling errors and 914 misspelled words were found. The similarity-based spelling correction algorithm using BioWordVec proposed in this research corrected 12 types of typographical errors and showed very high performance in correcting 97.48% (based on F1 score) of all spelling errors. CONCLUSIONS This tool corrected spelling errors effectively in the absence of a dictionary based on bacterial identification words in bacterial culture and antimicrobial susceptibility reports. This method will help build a high-quality refined database of vast text data for electronic health records.

Elderly patients treated with percutaneous coronary intervention (PCI) have a higher risk of both ischemic and bleeding complications than younger patients. However, few studies have reported how genetic information of elderly patients treated with PCI affects clinical outcomes. We investigated the impact of genetic variants on clinical outcomes in elderly patients. Correlations between single-nucleotide polymorphisms (CYP2C19 and P2Y12 receptor gene G52T polymorphism) and clinical outcomes were analyzed in 811 elderly patients (≥75 years of age) from a prospective multicenter registry. The primary endpoint was a composite of myocardial infarction and death. Secondary endpoints were an individual event of death, cardiac death, myocardial infarction, stent thrombosis, target lesion revascularization, stroke, and major bleeding (Bleeding Academic Research Consortium ≥3). Regarding CYP2C19, patients with poor metabolizers had a significantly higher risk for the primary endpoint (hazard ratio [HR] 2.43; 95% confidence interval [95% CI] 1.12-5.24; p=0.024) and secondary endpoints (death and cardiac death). Regarding P2Y12 G52T, the TT group had a significantly higher occurrence of major bleeding than the other groups (HR 3.87; 95% CI 1.41-10.68; p=0.009). In conclusion, poor metabolizers of CYP2C19 and TT groups of P2Y12 G52T may be significant predictors of poor clinical outcomes in elderly patients.

What is known and objective Pre-treatment of clopidogrel 600 mg is better than 300 mg loading for reducing periprocedural myocardial infarction (PMI). We aimed to evaluate pre-treatment methods for preventing PMI among patients undergoing conventional coronary angiography (CAG) for stable angina pectoris. Materials and methods The study analyzed 402 patients who underwent percutaneous coronary intervention (PCI) during 2010 - 2011 at three Korean hospitals. Clopidogrel-naive patients received routine maintenance therapy (75 mg/day for ≥ 5 days) and were randomly assigned to a 300-mg reload (RL) or only the maintenance dose (MD). Patients who received a loading dose (LD; 600 mg at 2 - 24 hours before the procedure) were entered into a non-randomized group. Results After excluding patients who showed an abnormal creatinine kinase myocardial band (CK-MB) level, the study included 233 patients in the LD group, 85 patients in the RL group and 84 patients in the MD group. The LD group had a significantly higher rate of PMI (LD: 21, RL: 3, MD: 0 cases; p = 0.007) and a significant increase in the mean CK-MB levels after 8 hours (p = 0.016) and 24 h (p = 0.01). However, there was no difference in PMI between the RL and MD groups. Furthermore, no significant differences between the three groups were observed in the P2Y12 reaction unit (PRU) values (p = 0.57). Albeit not significantly, the LD group had a higher rate of moderate-to-severe GUSTO bleeding within 7 days. What is new and conclusion Clopidogrel maintenance is better than 600-mg loading for preventing PMI, and the RL protocol did not further prevent PMI. .

Thymosin Beta4 (Tβ4) is a G-actin sequestering protein that contributes to diverse cellular activities, such as migration and angiogenesis. In this study, the beneficial effects of combined cell therapy with Tβ4 and human adipose-derived stem cells (hASCs) in a mouse ischemic hindlimb model were investigated. We observed that exogenous treatment with Tβ4 enhanced endogenous TMSB4X mRNA expression and promoted morphological changes (increased cell length) in hASCs. Interestingly, Tβ4 induced the active state of hASCs by up-regulating intracellular signaling pathways including the PI3K/AKT/mTOR and MAPK/ERK pathways. Treatment with Tβ4 significantly increased cell migration and sprouting from microbeads. Moreover, additional treatment with Tβ4 promoted the endothelial differentiation potential of hASCs by up-regulating various angiogenic genes. To evaluate the in vivo effects of the Tβ4-hASCs combination on vessel recruitment, dorsal window chambers were transplanted, and the co-treated mice were found to have a significantly increased number of microvessel branches. Transplantation of hASCs in combination with Tβ4 was found to improve blood flow and attenuate limb or foot loss post-ischemia compared to transplantation with hASCs alone. Taken together, the therapeutic application of hASCs combined with Tβ4 could be effective in enhancing endothelial differentiation and vascularization for treating hindlimb ischemia.

UNSTRUCTURED Common data model (CDM) is a data representation standard that unifies the observational database scheme for each medical institution and allows an analysis using the same tools. Although the analysis for CDM data does not directly examine a medical institution’s original data, it is essential to establish a policy that considers the CDM database operating environment because privacy issues cannot be avoided. The observational medical outcomes partnership common data model (OMOP CDM) defined by Observational Health Data Sciences and Informatics, a nonprofit organization, eliminates most personal information when constructing the database by design principles. When transforming the database of the medical institution to the OMOP CDM structure, the original data “source_value” is maintained to minimize information loss, which may cause the re-identification of the individual. This review presents a de-identification strategy for the original data, which can be considered when operating a CDM database in a public computing environment such as cloud computing. Furthermore, we evaluate the re-identification risk to the CDM database based on the proposed strategy using privacy models such as k-anonymity, l-diversity, and t-closeness. The analysis shows that the CDM database is highly anonymized on average (the highest re-identification record ration is 11.3 %), but every table in the CDM database contains one or more re-identifiable records. It has been confirmed that the risk of re-identification is reduced significantly by applying a de-identification strategy.

There have been limited clinical trials comparing drug eluting stents (DESs) and drug coated balloons (DCBs) in the treatment of femoropopliteal artery disease. This two centre retrospective and prospective cohort study sought to compare DES with DCB for the treatment of native femoropopliteal artery disease.A total of 288 limbs (242 patients) with native femoropopliteal artery disease were treated with DESs (Zilver PTX; 102 limbs) or DCBs (IN.PACT Admiral; 186 limbs) in two Korean endovascular centres between 19 January 2013 and 5 May 2018 and followed for a median duration of 19.6 months. The primary endpoint was primary clinical patency. Propensity score matching (PSM, 162 limbs) and inverse probability weighted (IPW) adjustment were performed to adjust for confounding baseline characteristics.The DCB group had fewer lesions with Trans-Atlantic Inter-Society Consensus (TASC) II type C/D (55.9% vs. 70.6%, p = .021) or total occlusions (43.5% vs. 77.5%, p .001) and showed shorter lesion lengths (164.2 ± 105.4 mm vs. 194.8 ± 86.8 mm, p = .009) than the DES group. After PSM, baseline clinical and lesion characteristics of the two groups were comparable except for larger reference vessel diameter in the DES group (5.4 ± 0.6 vs. 5.1 ± 0.7, p = .025). Adjunctive atherectomy was performed in 32.1% of the DCB group and in 2.5% of the DES group (p .001). The provisional stenting was required in 14.8% of the DCB group. At two year follow up, the DCB group showed higher primary clinical patency (74.6% vs. 56.7%, hazard ratio [HR] 0.51, 95% confidence interval [CI] 0.27-0.96, p = .032) and freedom from target lesion revascularisation (85.9% vs. 71.3%, HR 0.39, 95% CI 0.17-0.89, p = .021) than the DES group. Survival from all cause death did not differ between groups (87.6% vs. 92.1%, HR 1.85, 95% CI 0.62-5.52, p = .26).In this two centre cohort, DCBs with selective use of adjunctive atherectomy achieved more favourable outcomes than DESs for native femoropopliteal artery disease.

Background The current guidelines recommend both repeat stenting and drug-coated balloons (DCB) for in-stent restenosis (ISR) lesions, if technically feasible. However, real-world clinical data on the interventional strategies in patients with left main bifurcation (LMB)-ISR have not been elucidated. Methods Seventy-five patients with LMB-ISR, who underwent percutaneous coronary intervention (PCI) between January 2009 and July 2015, were retrospectively reviewed for the present study (repeat drug eluting stent [DES] implantation [n = 51], DCB angioplasty [n = 24]). Results Analysis of the baseline characteristics showed that the patients in the DCB group had a lower incidence of non-ST segment elevation myocardial infarction/ST segment elevation myocardial infarction at the index PCI (8.3% vs. 25.5%; p = 0.12), higher low-density lipoprotein-cholesterol level (92.9 mg/dL vs. 81.7 mg/dL; p = 0.09), and more “stent-in-stent” lesions (25% vs. 7.8%; p = 0.07) than those in the DES group. A smaller post-procedural minimal target lesion lumen diameter was also noted in the DCB group than in the DES group (2.71 mm vs. 2.85 mm; p = 0.03). The cumulative incidence rates of major adverse cardiac events (MACEs) were similar between both groups (median follow-up duration, 868 days; MACE rate, 25% in the DCB group vs. 25.5% in the DES group; p = 0.96). The multivariate Cox regression analysis indicated that the true bifurcation of ISR was an independent risk predictor of MACEs (hazard ratio, 4.62; 95% confidence interval, 1.572–13.561; p Conclusions DES and DCB showed comparable long-term clinical results in patients with LMB-ISR lesions.

BACKGROUND AND OBJECTIVES The Sapien 3 (S3) valve has not been compared to the Sapien XT (SXT) valve in Korea. We compared procedural and clinical outcomes between the 2 devices. METHODS A total of 189 patients who underwent transcatheter aortic valve replacement (TAVR) with S3 (n=95) or SXT (n=94) valve was analyzed. The primary endpoint was cardiovascular mortality at 1 year. The median follow-up duration was 438 days. RESULTS The Society of Thoracic Surgeons score was similar between the 2 groups. The device success rate (90.4% vs. 97.9%; p=0.028) was higher in the S3 than in the SXT. The S3 showed significantly fewer cases of moderate or severe paravalvular leakage (PVL) (16.7% vs. 0.0%; p=0.001) than the SXT. However, effective orifice area (EOA) (2.07±0.61 vs. 1.70±0.49 cm²; p

Background Sca-1+ cardiac stem cells and their limited proliferative potential were major limiting factors for use in various studies. Methods Therefore, the effects of sphere genetically engineered cardiac stem cells (S-GECS) inserted with telomerase reverse transcriptase (TERT) were investigated to examine cardiomyocyte survival under hypoxic conditions. GECS was obtained from hTERT-immortalized Sca-1+ cardiac stem cell (CSC) lines, and S-GECS were generated using poly-HEMA. Results The optimal conditions for S-GECS was determined to be 1052 GECS cells/mm2 and a 48 h culture period to produce spheroids. Compared to adherent-GECS (A-GECS) and S-GECS showed significantly higher mRNA expression of SDF-1α and CXCR4. S-GECS conditioned medium (CM) significantly reduced the proportion of early and late apoptotic cardiomyoblasts during CoCl2-induced hypoxic injury; however, gene silencing via CXCR4 siRNA deteriorated the protective effects of S-GECS against hypoxic injury. As downstream pathways of SDF-1α/CXCR4, the Erk and Akt signaling pathways were stimulated in the presence of S-GECS CM. S-GECS transplantation into a rat acute myocardial infarction model improved cardiac function and reduced the fibrotic area. These cardioprotective effects were confirmed to be related with the SDF-1α/CXCR4 pathway. Conclusions Our findings suggest that paracrine factors secreted from transplanted cells may protect host cardiomyoblasts in the infarcted myocardium, contributing to beneficial left ventricle (LV) remodeling after acute myocardial infarction (AMI).

Platelet function test (PFT) results and genotype hold unique prognostic implications in East Asian patients. The aim of the PTRG-DES (Platelet function and genoType-Related long-term proGnosis in Drug-Eluting Stent-treated Patients with coronary artery disease) consortium is to assess the clinical impact thereof on long-term clinical outcomes in Korean patients with coronary artery disease during dual antiplatelet therapy (DAPT) including clopidogrel.Searching publications on the PubMed, we reviewed clopidogrel treatment studies with PFT and/or genotype data for potential inclusion in this study. Lead investigators were invited to share PFT/genotype results, patient characteristics, and clinical outcomes to evaluate relationships among them.Nine registries from 32 academic centers participated in the PTRG-DES consortium, contributing individual patient data from 13160 patients who underwent DES implantation between July 2003 and August 2018. The PTRG-PFT cohort was composed of 11714 patients with available VerifyNow assay results. Platelet reactivity levels reached 218±79 P2Y12 reaction units (PRU), and high on-clopidogrel platelet reactivity based on a consensus-recommended cutoff (PRU208) was observed in 55.9%. The PTRG-Genotype cohort consisted of 8163 patients with candidate genotypes related with clopidogrel responsiveness. Of those with cytochrome P450 (CYP) 2C19 genotype, frequencies of carrying one and two loss-of-function allele (s) (The PTRG-DES consortium highlights unique values for on-clopidogrel platelet reactivity and CYP2C19 phenotype that may be important to developing optimal antiplatelet regimens in East Asian patients.ClinicalTrials.gov Identifier: NCT04734028.

Background/Aims: Although epigallocatechin-3-gallate (EGCG), which is found in high contents in the dried leaves of green tea, has been reported to have an an ti-platelet effect, synergistic effects of EGCG in addition to current anti-platelet medications remains to be elucidated. Methods: Blood samples were obtained from 40 participants who took aspirin (ASA, n = 10), clopidogrel (CPD, n = 10), ticagrelor (TCG, n = 10) and no anti-plate let medication (Control, n = 10). Ex vivo platelet aggregation and adhesion under various stimulators were analyzed by multiple electrode aggregometry (MEA) and Impact-R systems. PAC-1 and P-selectin expressions in human platelets were ana lyzed by flow cytometry. Results: In MEA analysis, adenosine diphosphate (ADP) and thrombin receptor activating peptide (TRAP)-induced platelet aggregations were lower in the CPD and the TCG groups; arachidonic acid (AA)-induced platelet aggregation was low er in the ASA group, whereas collagen (COL)-induced platelet aggregations were comparable among four groups. EGCG significantly reduced ADP- and COL-in duced platelet aggregation in dose-dependent manner (ADP, p = 0.04; COL, p < 0.01). There were no additional suppressions of platelet aggregation stimulated by AA in the ASA group, and by ADP in the CPD and TCG groups. Moreover, EGCG suppressed shear stress-induced platelet adhesion on Impact-R, and had no effect on P-selectin and PAC-1 expressions. Conclusions: Ex vivo treatment of EGCG inhibited platelet adhesion and aggrega tion without changes in P-selectin and PAC-1 expression. There was no additional suppressions in platelet aggregation stimulated by AA in the ASA group and ADP in the CPD and TCG groups.