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Abstract Parkinson’s disease (PD) reports high rates of morbidity and mortality, but the risk of adverse cardiovascular outcomes in patients with PD has not been fully elucidated. This bi-center retrospective cohort study using the electronic health records (EHR) database of two tertiary hospitals screened a total of 327,292 subjects who visited the outpatient clinic, and 1194 patients with PD were propensity score-matched with a control population. The primary outcome was the occurrence of major adverse cardiovascular events (MACE). Key secondary outcomes included all-cause death, cardiovascular (CV) death, stroke, myocardial infarction (MI), heart failure hospitalization and 30-day CV death. After PS matching, MACE occurrence was not significantly different between PD and non-PD groups (18.2% vs. 17.5%, log-rank p = 0.98). Key secondary outcomes were also similar between the two groups. In patients with PD, MACE rate, and also CV risk score, were higher in patients with more severe PD (according to Hoehn and Yahr scale and unified Parkinson’s disease rating scale), and after multivariable analysis, PD severity was not an independent predictor of MACE. Patients with PD are at an increased risk of adverse cardiovascular outcomes, but the contribution from other common CV risk factors cannot be ignored. The management of prevalent CV risk factors is therefore important in mitigating adverse outcomes among patients with PD.

Abstract This study evaluated the association of atherogenic index of plasma (AIP) with platelet reactivity and clinical outcomes according to acute myocardial infarction (AMI). The composite of 3-year adverse outcomes of all-cause death, myocardial infarction, and cerebrovascular accident was evaluated in 10,735 patients after successful percutaneous coronary intervention with drug-eluting stents. AIP was defined as the base 10 logarithm of the ratio of triglyceride to high-density lipoprotein cholesterol concentration. High platelet reactivity (HPR) was defined as ≥ 252 P2Y12 reactivity unit. An increase of AIP (per-0.1 unit) was related to the decreased risk of HPR [odds ratio (OR) 0.97, 95% confidence interval (CI) 0.96–0.99; P = 0.001] in non-AMI patients, not in AMI patients (OR 0.98, 95% CI 0.96–1.01; P = 0.138). The HPR was associated with the increased risk of composite outcomes in both non-AMI and AMI patients (all-P

Abstract Emergency departments (ED) are complex, triage is a main task in the ED to prioritize patient with limited medical resources who need them most. Machine learning (ML) based ED triage tool, Score for Emergency Risk Prediction (SERP), was previously developed using an interpretable ML framework with single center. We aimed to develop SERP with 3 Korean multicenter cohorts based on common data model (CDM) without data sharing and compare performance with inter-hospital validation design. This retrospective cohort study included all adult emergency visit patients of 3 hospitals in Korea from 2016 to 2017. We adopted CDM for the standardized multicenter research. The outcome of interest was 2-day mortality after the patients’ ED visit. We developed each hospital SERP using interpretable ML framework and validated inter-hospital wisely. We accessed the performance of each hospital’s score based on some metrics considering data imbalance strategy. The study population for each hospital included 87,670, 83,363 and 54,423 ED visits from 2016 to 2017. The 2-day mortality rate were 0.51%, 0.56% and 0.65%. Validation results showed accurate for inter hospital validation which has at least AUROC of 0.899 (0.858–0.940). We developed multicenter based Interpretable ML model using CDM for 2-day mortality prediction and executed Inter-hospital external validation which showed enough high accuracy.

Abstract Stent thrombosis (ST) is a fatal complication after percutaneous coronary intervention (PCI). The association between P2Y12 reaction unit (PRU) level and stent thrombosis occurrence remains unclear. Based on the multicenter, observational PTRG-DES (Platelet function and genoType-Related long-term proGnosis in DES-treated patients) registry of patients with drug-eluting stents (DES) implantation, a total of 11,714 patients with PRU values were analyzed. We sought to identify the predictors of early stent thrombosis (EST) and compared the primary outcome, a composite of cardiac death, myocardial infarction, and revascularization, between EST and non-EST groups. EST, defined as definite ST within 1 month after index PCI, occurred in 51 patients. PRU values were significantly higher in the EST group (263.5 ± 70.8 vs. 217.5 ± 78.7, p

Abstract Limited knowledge exists regarding the predictors of mortality after successful weaning of venoarterial extracorporeal membrane oxygenation (ECMO). We aimed to identify predictors of in-hospital mortality in patients with cardiogenic shock (CS) after successful weaning from ECMO. Data were obtained from a multicenter registry of CS. Successful ECMO weaning was defined as survival with minimal mean arterial pressure (> 65 mmHg) for > 24 h after ECMO removal. The primary outcome was in-hospital mortality after successful ECMO weaning. Among 1247 patients with CS, 485 received ECMO, and 262 were successfully weaned from ECMO. In-hospital mortality occurred in 48 patients (18.3%). Survivors at discharge differed significantly from non-survivors in age, cardiovascular comorbidities, cause of CS, left ventricular ejection fraction, and use of adjunctive therapy. Five independent predictors for in-hospital mortality were identified: use of continuous renal replacement therapy (odds ratio 5.429, 95% confidence interval [CI] 2.468–11.940; p

Abstract Ticagrelor-based dual antiplatelet therapy (DAPT) provides potent antiplatelet inhibition but may increase the bleeding risk in Asian populations. We investigated the influence of early ticagrelor dose reduction (120 mg) on clinical outcomes in Korean patients undergoing percutaneous coronary intervention (PCI). A multicenter prospective clinical cohort study was conducted with patients who received standard-dose ticagrelor-based DAPT (180 mg) after PCI for complex lesions. Major adverse cardiovascular event (MACE: a composite of cardiovascular death, myocardial infarction, stroke, and repeat revascularization), bleeding, and net adverse clinical events (NACE: a composite of MACE and bleeding) were assessed. Among the 772 patients on standard-dose ticagrelor-based DAPT, 115 (14.8%) switched to low-dose ticagrelor-based DAPT (120 mg) within 6 months. Common reasons for the regimen changes were switching as planned (38.8%), dyspnea (25.5%), and bleeding (23.6%). A multivariable Cox proportional hazard model (CPH) showed that the risks of MACE, bleeding, and NACE were not different between the low-dose and standard-dose groups throughout the entire follow-up period and the period beyond 6 months post-PCI. Time-varying multivariable CPH models of the ticagrelor dose reduction yielded similar results. A reduction of the ticagrelor dose within 6 months after PCI is feasible and safe even in patients with complex lesions harboring a high ischemic event risk.

Abstract 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.

Abstract An increase in antibiotic usage is considered to contribute 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 1938 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.

Abstract Although dual antiplatelet therapy is essential for patients who undergo percutaneous coronary interventions, the risk of bleeding remains an unsolved problem, and there is limited information on the potential relationship between genetic variants and major bleeding. We analyzed the correlations between four major single nucleotide polymorphisms (CYP2C19, ABCB1, PON1, and P2Y12 G52T polymorphisms) and clinical outcomes in 4489 patients from a prospective multicenter registry. The primary endpoint was major bleeding, defined as a Bleeding Academic Research Consortium ≥ 3 bleeding event. The allelic frequencies of ABCB1, PON1, and both individual and combined CYP2C19 variants did not differ significantly between patient groups with and without major bleeding. However, the allelic frequency of the P2Y12 variant differed significantly between the two groups. Focusing on the P2Y12 G52T variant, patients in the TT group had a significantly higher rate of major bleeding (6.4%; adjusted hazard ratio [HR] 2.51; 95% confidence interval [CI] 1.08–5.84; p = 0.033) than patients in the other groups (GG [2.9%] or GT [1.9%]). Therefore, the TT variant of the P2Y12 G52T polymorphism may be an independent predictor of major bleeding. Trial registration: NCT02707445 ( https://clinicaltrials.gov/ct2/show/NCT02707445?term=02707445&draw=2&rank=1 ).