Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.

Background/Aims: Bleeding events after percutaneous coronary intervention (PCI) have important prognostic implications. Data on the influence of an abnormal ankle-brachial index (ABI) on both ischemic and bleeding events in patients undergoing PCI are limited. Methods: We included patients who underwent PCI with available ABI data (abnormal ABI, ≤ 0.9 or > 1.4). The primary endpoint was the composite of all-cause death, myocardial infarction (MI), stroke, and major bleeding. Results: Among 4,747 patients, an abnormal ABI was observed in 610 patients (12.9%). During follow-up (median, 31 months), the 5-year cumulative incidence of adverse clinical events was higher in the abnormal ABI group than in the normal ABI group: primary endpoint (36.0% vs. 14.5%, log-rank test, p < 0.001); all-cause death (19.4% vs. 5.1%, log-rank test, p < 0.001); MI (6.3% vs. 4.1%, log-rank test, p = 0.013); stroke (6.2% vs. 2.7%, log-rank test, p = 0.001); and major bleeding (8.9% vs. 3.7%, log-rank test, p < 0.001). An abnormal ABI was an independent risk factor for all-cause death (hazard ratio [HR], 3.05; p < 0.001), stroke (HR, 1.79; p = 0.042), and major bleeding (HR, 1.61; p = 0.034). Conclusions An abnormal ABI is a risk factor for both ischemic and bleeding events after PCI. Our study findings may be helpful in determining the optimal method for secondary prevention after PCI.

Background: Enavogliflozin is a novel sodium-glucose cotransporter-2 inhibitor currently under clinical development. This study evaluated the efficacy and safety of enavogliflozin as an add-on to metformin in Korean patients with type 2 diabetes mellitus (T2DM) against dapagliflozin. Methods: In this multicenter, double-blind, randomized, phase 3 study, 200 patients were randomized to receive enavogliflozin 0.3 mg/day (n=101) or dapagliflozin 10 mg/day (n=99) in addition to ongoing metformin therapy for 24 weeks. The primary objective of the study was to prove the non-inferiority of enavogliflozin to dapagliflozin in glycosylated hemoglobin (HbA1c) change at week 24 (non-inferiority margin of 0.35%) (Clinical trial registration number: NCT04634500). Results: Adjusted mean change of HbA1c at week 24 was –0.80% with enavogliflozin and –0.75% with dapagliflozin (difference, –0.04%; 95% confidence interval, –0.21% to 0.12%). Percentages of patients achieving HbA1c <7.0% were 61% and 62%, respectively. Adjusted mean change of fasting plasma glucose at week 24 was –32.53 and –29.14 mg/dL. An increase in urine glucose-creatinine ratio (60.48 vs. 44.94, P<0.0001) and decrease in homeostasis model assessment of insulin resistance (–1.85 vs. –1.31, P=0.0041) were significantly greater with enavogliflozin than dapagliflozin at week 24. Beneficial effects of enavogliflozin on body weight (–3.77 kg vs. –3.58 kg) and blood pressure (systolic/diastolic, –5.93/–5.41 mm Hg vs. –6.57/–4.26 mm Hg) were comparable with those of dapagliflozin, and both drugs were safe and well-tolerated. Conclusion Enavogliflozin added to metformin significantly improved glycemic control in patients with T2DM and was non-inferior to dapagliflozin 10 mg, suggesting enavogliflozin as a viable treatment option for patients with inadequate glycemic control on metformin alone.

Objectives: The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study leveraged a national-level multicenter approach, utilizing electronic health records (EHRs) from six hospitals in Korea. Methods: A retrospective cohort analysis was conducted using EHRs from six hospitals in Korea, comprising a total of 10,852 patients whose data were converted to the Common Data Model. The study assessed the incidence rate of DILI among patients taking ARBs and compared it to a control group. Temporal patterns of important variables were analyzed using an interpretable timeseries model. Results: The overall incidence rate of DILI among patients taking ARBs was found to be 1.09%. The incidence rates varied for each specific ARB drug and institution, with valsartan having the highest rate (1.24%) and olmesartan having the lowest rate (0.83%). The DILI prediction models showed varying performance, measured by the average area under the receiver operating characteristic curve, with telmisartan (0.93), losartan (0.92), and irbesartan (0.90) exhibiting higher classification performance. The aggregated attention scores from the models highlighted the importance of variables such as hematocrit, albumin, prothrombin time, and lymphocytes in predicting DILI. Conclusions Implementing a multicenter-based timeseries classification model provided evidence that could be valuable to clinicians regarding temporal patterns associated with DILI in ARB users. This information supports informed decisions regarding appropriate drug use and treatment strategies.

In this study, the Search Your Mind (S.Y.M., 心) project aimed to collect prospective digital phenotypic data centered on mood and anxiety symptoms across psychiatric disorders through a smartphone application (app) platform while using both centralized and decentralized research designs: the centralized research design is a hybrid of a general prospective observational study and a digital platform-based study, and it includes face-to-face research such as informed written consent, clinical evaluation, and blood sampling. It also includes digital phenotypic assessment through an application-based platform using wearable devices. Meanwhile, the decentralized research design is a non-face-to-face study in which anonymous participants agree to electronic informed consent forms on the app. It also exclusively uses an application-based platform to acquire individualized digital phenotypic data. We expect to collect clinical, biological, and digital phenotypic data centered on mood and anxiety symptoms, and we propose a possible model of centralized and decentralized research design.