Background: Atherosclerotic cardiovascular disease (ASCVD) is a major health concern, and lipoprotein(a) (Lp(a)) is an independent risk factor. However, there is limited evidence regarding Lp(a) and the risk of ASCVD in Asian populations. This study aimed to assess the predictive value of changes in coronary artery calcification (CAC) for ASCVD risk associated with Lp(a) level. Methods: Participants (n=2,750) were grouped according to their Lp(a) levels, and the association between Lp(a) and CAC progression was examined. CAC progression was defined as the occurrence of incident CAC or a difference ≥2.5 between the square root (√) of baseline and follow-up coronary artery calcium scores (CACSs) (Δ√transformed CACS). To adjust for differences in follow-up periods, Δ√transformed CACS was divided by the follow- up period (in years). Results: Over an average follow-up of 3.07 years, 18.98% of participants experienced CAC progression. Those with disease progression had notably higher Lp(a) levels. Higher Lp(a) tertiles correlated with increased baseline and follow-up CACS, CAC progression (%), and Δ√transformed CACS. Even after adjustment, higher Lp(a) levels were associated with CAC progression. However, annualized Δ√transformed CACS analysis yielded no significant results. Conclusion This study demonstrated an association between elevated Lp(a) levels and CAC progression in a general population without ASCVD. However, longer-term follow-up studies are needed to obtain meaningful results regarding CAC progression. Further research is necessary to utilize Lp(a) level as a predictor of cardiovascular disease and to establish clinically relevant thresholds specific to the Korean population.

Background: Atherosclerotic cardiovascular disease (ASCVD) is a major health concern, and lipoprotein(a) (Lp(a)) is an independent risk factor. However, there is limited evidence regarding Lp(a) and the risk of ASCVD in Asian populations. This study aimed to assess the predictive value of changes in coronary artery calcification (CAC) for ASCVD risk associated with Lp(a) level. Methods: Participants (n=2,750) were grouped according to their Lp(a) levels, and the association between Lp(a) and CAC progression was examined. CAC progression was defined as the occurrence of incident CAC or a difference ≥2.5 between the square root (√) of baseline and follow-up coronary artery calcium scores (CACSs) (Δ√transformed CACS). To adjust for differences in follow-up periods, Δ√transformed CACS was divided by the follow- up period (in years). Results: Over an average follow-up of 3.07 years, 18.98% of participants experienced CAC progression. Those with disease progression had notably higher Lp(a) levels. Higher Lp(a) tertiles correlated with increased baseline and follow-up CACS, CAC progression (%), and Δ√transformed CACS. Even after adjustment, higher Lp(a) levels were associated with CAC progression. However, annualized Δ√transformed CACS analysis yielded no significant results. Conclusion This study demonstrated an association between elevated Lp(a) levels and CAC progression in a general population without ASCVD. However, longer-term follow-up studies are needed to obtain meaningful results regarding CAC progression. Further research is necessary to utilize Lp(a) level as a predictor of cardiovascular disease and to establish clinically relevant thresholds specific to the Korean 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: Atherosclerotic cardiovascular disease (ASCVD) is a major health concern, and lipoprotein(a) (Lp(a)) is an independent risk factor. However, there is limited evidence regarding Lp(a) and the risk of ASCVD in Asian populations. This study aimed to assess the predictive value of changes in coronary artery calcification (CAC) for ASCVD risk associated with Lp(a) level. Methods: Participants (n=2,750) were grouped according to their Lp(a) levels, and the association between Lp(a) and CAC progression was examined. CAC progression was defined as the occurrence of incident CAC or a difference ≥2.5 between the square root (√) of baseline and follow-up coronary artery calcium scores (CACSs) (Δ√transformed CACS). To adjust for differences in follow-up periods, Δ√transformed CACS was divided by the follow- up period (in years). Results: Over an average follow-up of 3.07 years, 18.98% of participants experienced CAC progression. Those with disease progression had notably higher Lp(a) levels. Higher Lp(a) tertiles correlated with increased baseline and follow-up CACS, CAC progression (%), and Δ√transformed CACS. Even after adjustment, higher Lp(a) levels were associated with CAC progression. However, annualized Δ√transformed CACS analysis yielded no significant results. Conclusion This study demonstrated an association between elevated Lp(a) levels and CAC progression in a general population without ASCVD. However, longer-term follow-up studies are needed to obtain meaningful results regarding CAC progression. Further research is necessary to utilize Lp(a) level as a predictor of cardiovascular disease and to establish clinically relevant thresholds specific to the Korean 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: Atherosclerotic cardiovascular disease (ASCVD) is a major health concern, and lipoprotein(a) (Lp(a)) is an independent risk factor. However, there is limited evidence regarding Lp(a) and the risk of ASCVD in Asian populations. This study aimed to assess the predictive value of changes in coronary artery calcification (CAC) for ASCVD risk associated with Lp(a) level. Methods: Participants (n=2,750) were grouped according to their Lp(a) levels, and the association between Lp(a) and CAC progression was examined. CAC progression was defined as the occurrence of incident CAC or a difference ≥2.5 between the square root (√) of baseline and follow-up coronary artery calcium scores (CACSs) (Δ√transformed CACS). To adjust for differences in follow-up periods, Δ√transformed CACS was divided by the follow- up period (in years). Results: Over an average follow-up of 3.07 years, 18.98% of participants experienced CAC progression. Those with disease progression had notably higher Lp(a) levels. Higher Lp(a) tertiles correlated with increased baseline and follow-up CACS, CAC progression (%), and Δ√transformed CACS. Even after adjustment, higher Lp(a) levels were associated with CAC progression. However, annualized Δ√transformed CACS analysis yielded no significant results. Conclusion This study demonstrated an association between elevated Lp(a) levels and CAC progression in a general population without ASCVD. However, longer-term follow-up studies are needed to obtain meaningful results regarding CAC progression. Further research is necessary to utilize Lp(a) level as a predictor of cardiovascular disease and to establish clinically relevant thresholds specific to the Korean 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.

Objectives: Skin cancer is a prevalent type of malignancy, necessitating efficient diagnostic tools. This study aimed to develop an automated skin lesion classification model using the dynamically expandable representation (DER) incremental learning algorithm. This algorithm adapts to new data and expands its classification capabilities, with the goal of creating a scalable and efficient system for diagnosing skin cancer. Methods: The DER model with incremental learning was applied to the HAM10000 and ISIC 2019 datasets. Validation involved two steps: initially, training and evaluating the HAM10000 dataset against a fixed ResNet-50; subsequently, performing external validation of the trained model using the ISIC 2019 dataset. The model’s performance was assessed using precision, recall, the F1-score, and area under the precision-recall curve. Results: The developed skin lesion classification model demonstrated high accuracy and reliability across various types of skin lesions, achieving a weighted-average precision, recall, and F1-score of 0.918, 0.808, and 0.847, respectively. The model’s discrimination performance was reflected in an average area under the curve (AUC) value of 0.943. Further external validation with the ISIC 2019 dataset confirmed the model’s effectiveness, as shown by an AUC of 0.911. Conclusions This study presents an optimized skin lesion classification model based on the DER algorithm, which shows high performance in disease classification with the potential to expand its classification range. The model demonstrated robust results in external validation, indicating its adaptability to new disease classes.