Secondary dyslipidemia, characterized by elevated blood cholesterol and triglycerides, arises from various underlying conditions. The identification and appropriate handling of these causes is crucial for effective treatment. Major contributors include unhealthy diets, diseases impacting lipid metabolism, and medication side effects. Prioritizing the correction of secondary causes before initiating conventional lipid-lowering therapies is essential. Subsequent lipid profiles guide the selection of appropriate guideline-based lipid-lowering interventions.

Secondary dyslipidemia, characterized by elevated blood cholesterol and triglycerides, arises from various underlying conditions. The identification and appropriate handling of these causes is crucial for effective treatment. Major contributors include unhealthy diets, diseases impacting lipid metabolism, and medication side effects. Prioritizing the correction of secondary causes before initiating conventional lipid-lowering therapies is essential. Subsequent lipid profiles guide the selection of appropriate guideline-based lipid-lowering interventions.

Secondary dyslipidemia, characterized by elevated blood cholesterol and triglycerides, arises from various underlying conditions. The identification and appropriate handling of these causes is crucial for effective treatment. Major contributors include unhealthy diets, diseases impacting lipid metabolism, and medication side effects. Prioritizing the correction of secondary causes before initiating conventional lipid-lowering therapies is essential. Subsequent lipid profiles guide the selection of appropriate guideline-based lipid-lowering interventions.

Secondary dyslipidemia, characterized by elevated blood cholesterol and triglycerides, arises from various underlying conditions. The identification and appropriate handling of these causes is crucial for effective treatment. Major contributors include unhealthy diets, diseases impacting lipid metabolism, and medication side effects. Prioritizing the correction of secondary causes before initiating conventional lipid-lowering therapies is essential. Subsequent lipid profiles guide the selection of appropriate guideline-based lipid-lowering interventions.

Elevated blood cholesterol and triglyceride levels induced by secondary causes are frequently observed. The identification and appropriate handling of these causes are essential for secondary dyslipidemia treatment. Major secondary causes of hypercholesterolemia and hypertriglyceridemia include an unhealthy diet, diseases and metabolic conditions affecting lipid levels, and therapeutic side effects. It is imperative to correct secondary causes prior to initiating conventional lipid-lowering therapy. Guideline-based lipid therapy can then be administered based on the subsequent lipid levels.

Background: and Purpose Accurate classification of ischemic stroke subtype is important for effective secondary prevention of stroke. We used diffusion-weighted image (DWI) and atrial fibrillation (AF) data to train a deep learning algorithm to classify stroke subtype. Methods: Model development was done in 2,988 patients with ischemic stroke from three centers by using U-net for infarct segmentation and EfficientNetV2 for subtype classification. Experienced neurologists (n=5) determined subtypes for external test datasets, while establishing a consensus for clinical trial datasets. Automatically segmented infarcts were fed into the model (DWI-only algorithm). Subsequently, another model was trained, with AF included as a categorical variable (DWI+AF algorithm). These models were tested: (1) internally against the opinion of the labeling experts, (2) against fresh external DWI data, and (3) against clinical trial dataset. Results: In the training-and-validation datasets, the mean (±standard deviation) age was 68.0±12.5 (61.1% male). In internal testing, compared with the experts, the DWI-only and the DWI+AF algorithms respectively achieved moderate (65.3%) and near-strong (79.1%) agreement. In external testing, both algorithms again showed good agreements (59.3%–60.7% and 73.7%–74.0%, respectively). In the clinical trial dataset, compared with the expert consensus, percentage agreements and Cohen’s kappa were respectively 58.1% and 0.34 for the DWI-only vs. 72.9% and 0.57 for the DWI+AF algorithms. The corresponding values between experts were comparable (76.0% and 0.61) to the DWI+AF algorithm. Conclusion Our model trained on a large dataset of DWI (both with or without AF information) was able to classify ischemic stroke subtypes comparable to a consensus of stroke experts.

Elevated blood cholesterol and triglyceride levels induced by secondary causes are frequently observed. The identification and appropriate handling of these causes are essential for secondary dyslipidemia treatment. Major secondary causes of hypercholesterolemia and hypertriglyceridemia include an unhealthy diet, diseases and metabolic conditions affecting lipid levels, and therapeutic side effects. It is imperative to correct secondary causes prior to initiating conventional lipid-lowering therapy. Guideline-based lipid therapy can then be administered based on the subsequent lipid levels.

Background and Objectives: Real-world trends in the utility and type of gatekeeping studies in invasive coronary angiography (ICA) requires further investigation. Methods: We identified outpatients who underwent noninvasive cardiac tests or directly ICA for suspected coronary artery disease (CAD) from the nationwide Korea Health Insurance Review and Assessment Service-National Patient Sample database between 2012 and 2018. Results: Among 71,401 patients, the percentage of patients who were evaluated for suspected CAD was 34.7% for treadmill test (TMT), 4.2% for single-photon emission computed tomography (SPECT), 24.2% for coronary computed tomography angiography (CCTA), 1.6% for multiple gatekeepers, and 32.3% for directly ICA without noninvasive studies. The proportion of CCTA as a gatekeeper showed linear increase, (18.6% in 2012 and 28.8% in 2018; p<0.001), while those of TMT, SPECT, and direct ICA have decreased (p<0.001, p=0.03, and p<0.001, respectively). The overall incidence of downstream ICA after gatekeeper was 13.8% (6,662/48,346), and SPECT showed higher ICA rate in pairwise comparison with TMT and CCTA (p<0.001). Patients who performed gatekeepers before ICA showed higher rate of subsequent PCI (34.7% vs. 32.3%; p<0.001) and CABG (3.5% vs. 1.0%; p<0.001), compared to those who directly underwent ICA, and CCTA was associated with higher revascularization rate after ICA in pairwise comparison with TMT and SPECT (p<0.001). Conclusions Nationwide database demonstrated that CCTA is utilized increasingly as a gatekeeper for ICA and is associated with high revascularization rate after ICA in outpatients with suspected CAD.

Background and Objectives: Few studies have investigated the obesity paradox in clinical outcomes of peripheral artery disease (PAD). We investigated the association between body massindex (BMI) and clinical outcomes in PAD patients undergoing endovascular therapy (EVT). Methods: Patients (n=2,914) from the retrospective Korean Vascular Intervention Society Endovascular Therapy in Lower Limb Artery Disease registry were categorized according to BMI: underweight (<18.5 kg/m2 , n=204), normal weight (18.5–25 kg/m2 , n=1,818), overweight (25–30 kg/m2 , n=766), or obese (≥30 kg/m2 , n=126). Groups were compared for major adverse cardiovascular events (MACE) and major adverse limb events (MALE). Results: The underweight and obese groups were older and had more frequent critical limb ischemia and infrapopliteal artery disease than the normal or overweight groups (all p<0.001). Hypertension and diabetes were more frequent and current smoking was less frequent in the overweight and obese groups than the underweight or normal weight groups (all p <0.001). The underweight group showed the higher rates of MACE and MALE at 3 years (17.2%, 15.7%) compared with the normal weight (10.8%, 11.7%), overweight (8.4%, 10.7%), or obese groups (8.7%, 14.3%) (log-rank p<0.001, p=0.015). In contrast, the risk of MACE was lower in the overweight than the normal weight group (adjusted hazard ratio, 0.706; 95% CI, 0.537–0.928). Conclusions In PAD patients undergoing EVT, underweight was an independent predictor for MACE and MALE, whereas MACE risk was lower for overweight than normal weight patients.

Background and Objectives: Few studies have investigated the obesity paradox in clinical outcomes of peripheral artery disease (PAD). We investigated the association between body massindex (BMI) and clinical outcomes in PAD patients undergoing endovascular therapy (EVT). Methods: Patients (n=2,914) from the retrospective Korean Vascular Intervention Society Endovascular Therapy in Lower Limb Artery Disease registry were categorized according to BMI: underweight (<18.5 kg/m2 , n=204), normal weight (18.5–25 kg/m2 , n=1,818), overweight (25–30 kg/m2 , n=766), or obese (≥30 kg/m2 , n=126). Groups were compared for major adverse cardiovascular events (MACE) and major adverse limb events (MALE). Results: The underweight and obese groups were older and had more frequent critical limb ischemia and infrapopliteal artery disease than the normal or overweight groups (all p<0.001). Hypertension and diabetes were more frequent and current smoking was less frequent in the overweight and obese groups than the underweight or normal weight groups (all p <0.001). The underweight group showed the higher rates of MACE and MALE at 3 years (17.2%, 15.7%) compared with the normal weight (10.8%, 11.7%), overweight (8.4%, 10.7%), or obese groups (8.7%, 14.3%) (log-rank p<0.001, p=0.015). In contrast, the risk of MACE was lower in the overweight than the normal weight group (adjusted hazard ratio, 0.706; 95% CI, 0.537–0.928). Conclusions In PAD patients undergoing EVT, underweight was an independent predictor for MACE and MALE, whereas MACE risk was lower for overweight than normal weight patients.