Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.

Background: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nodules. Methods: This retrospective analysis included ultrasound images of patients with thyroid nodules investigated by fine-needle aspiration at the thyroid clinic of a single center from April 2010 to September 2012. Thyroid nodules with cytopathologic results of Bethesda category V (suspicious for malignancy) or VI (malignant) were defined as thyroid cancer. Multiple deep learning algorithms based on convolutional neural networks (CNNs) —ResNet, DenseNet, and EfficientNet—were utilized, and Siamese neural networks facilitated multi-view analysis of paired transverse and longitudinal ultrasound images. Results: Among 1,048 analyzed thyroid nodules from 943 patients, 306 (29%) were identified as thyroid cancer. In a subgroup analysis of transverse and longitudinal images, longitudinal images showed superior prediction ability. Multi-view modeling, based on paired transverse and longitudinal images, significantly improved the model performance; with an accuracy of 0.82 (95% confidence intervals [CI], 0.80 to 0.86) with ResNet50, 0.83 (95% CI, 0.83 to 0.88) with DenseNet201, and 0.81 (95% CI, 0.79 to 0.84) with EfficientNetv2_ s. Training with high-resolution images obtained using the latest equipment tended to improve model performance in association with increased sensitivity. Conclusion CNN algorithms applied to ultrasound images demonstrated substantial accuracy in thyroid nodule classification, indicating their potential as valuable tools for diagnosing thyroid cancer. However, in real-world clinical settings, it is important to aware that model performance may vary depending on the quality of images acquired by different physicians and imaging devices.

Background and Objectives: Outcomes of deferring percutaneous coronary intervention (PCI) without invasive physiologic assessment for intermediate coronary lesions is uncertain.We sought to compare long-term outcomes between medical treatment and PCI of intermediate lesions without invasive physiologic assessment. Methods: A total of 899 patients with intermediate coronary lesions between 50% and 70% diameter-stenosis were randomized to the conservative group (n=449) or the aggressive group (n=450). For intermediate lesions, PCI was performed in the aggressive group, but was deferred in the conservative group. The primary endpoint was major adverse cardiac events (MACE, a composite of all-cause death, myocardial infarction [MI], or ischemia-driven any revascularization) at 3 years. Results: The number of treated lesions per patient was 0.8±0.9 in the conservative group and 1.7±0.9 in the aggressive group (p=0.001). At 3 years, the conservative group had a significantly higher incidence of MACE than the aggressive group (13.8% vs. 9.3%; hazard ratio [HR], 1.49; 95% confidence interval [CI], 1.00–2.21; p=0.049), mainly driven by revascularization of target intermediate lesion (6.5% vs. 1.1%; HR, 5.69; 95% CI, 2.20–14.73;p<0.001). Between 1 and 3 years after the index procedure, compared to the aggressive group, the conservative group had significantly higher incidence of cardiac death or MI (3.2% vs.0.7%; HR, 4.34; 95% CI, 1.24–15.22; p=0.022) and ischemia-driven any revascularization. Conclusions For intermediate lesions, medical therapy alone, guided only by angiography, was associated with a higher risk of MACE at 3 years compared with performing PCI, mainly due to increased revascularization.

Background: The novel sodium-glucose cotransporter-2 (SGLT2) inhibitor enavogliflozin effectively lowers glycosylated hemoglobin levels and body weights without the increased risk of serious adverse events; however, the long-term clinical benefits of enavogliflozin in terms of cardiovascular and renal outcomes have not been investigated. Methods: This study is an investigator-initiated, multicenter, randomized, pragmatic, open-label, active-controlled, non-inferiority trial. Eligible participants are adults (aged ≥19 years) with type 2 diabetes mellitus (T2DM) who have a history of, or are at risk of, cardiovascular disease. A total of 2,862 participants will be randomly assigned to receive either enavogliflozin or other SGLT2 inhibitors with proven cardiorenal benefits, such as dapagliflozin or empagliflozin. The primary endpoint is the time to the first occurrence of a composite of major adverse cardiovascular or renal events (Clinical Research Information Service registration number: KCT0009243). Conclusion This trial will determine whether enavogliflozin is non-inferior to dapagliflozin or empagliflozin in terms of cardiorenal outcomes in patients with T2DM and cardiovascular risk factors. This study will elucidate the role of enavogliflozin in preventing vascular complications in patients with T2DM.