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: and Purpose The Treat Stroke to Target (TST) was a randomized clinical trial involving French and Korean patients demonstrating that a lower low-density lipoprotein cholesterol (LDL-C, <70 mg/dL) target group (LT) experienced fewer cerebro-cardiovascular events than a higher target (90–110 mg/dL) group (HT). However, whether these results can be applied to Asian patients with different ischemic stroke subtypes remains unclear. Methods: Patients from 14 South Korean centers were analyzed separately. Patients with ischemic stroke or transient ischemic attack with evidence of atherosclerosis were randomized into LT and HT groups. The primary endpoint was a composite of ischemic stroke, myocardial infarction, coronary or cerebral revascularization, and cardiovascular death. Results: Among 712 enrolled patients, the mean LDL-C level was 71.0 mg/dL in 357 LT patients and 86.1 mg/dL in 355 HT patients. The primary endpoint occurred in 24 (6.7%) of LT and in 31 (8.7%) of HT group patients (adjusted hazard ratio [HR]=0.78; 95% confidence interval [CI]=0.45–1.33, P=0.353). Cardiovascular events alone occurred significantly less frequently in the LT than in the HT group (HR 0.26, 95% CI 0.09–0.80, P=0.019), whereas there were no significant differences in ischemic stroke events (HR 1.12, 95% CI 0.60–2.10, P=0.712). The benefit of LT was less apparent in patients with small vessel disease and intracranial atherosclerosis than in those with extracranial atherosclerosis. Conclusion In contrast to the French TST, the outcomes in Korean patients were neutral. Although LT was more effective in preventing cardiovascular diseases, it was not so in stroke prevention, probably attributed to the differences in stroke subtypes. Further studies are needed to elucidate the efficacy of statins and appropriate LDL-C targets in Asian patients with stroke.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

Purpose: The classification of asthma phenotypes frequently depends on the age of onset. However, the rationale for specific age cutoffs remains unclear. This study aimed to explore the distribution of asthma onset age, to define subgroups based on onset age, and to examine their characteristics within a broad Korean population. Methods: An analysis of cross-sectional data involving 56,632 participants from the Korean National Health and Nutrition Examination Survey (2010–2016) was conducted. Data on asthma history, including diagnosis, self-reported age of asthma onset, and current disease status, were collected using structured questionnaires. Results: The distribution of asthma onset age showed a distinct peak in early childhood, with a decline between the ages 15 and 20.Based on this distribution, asthma was categorized into childhood-onset ( ≤ 18 years) and adult-onset ( > 18 years) for further analysis.Multivariate analyses indicated that adult-onset asthma was associated with older age, female sex, obesity, and a history of smoking, whereas childhood-onset asthma was linked to younger age, male sex, allergic rhinitis, and atopic dermatitis. Among the adultonset group, current asthma had a later onset age, increased history of smoking history, and atopic dermatitis compared to past asthma. Conclusion This analysis of nationwide general population data suggests that an age threshold around 18 years may be relevant for defining adult-onset asthma.

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.