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CPP : Cardiovascular Prevention and Pharmacotherapy

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Original Articles
Development of a predictive model for the side effects of liraglutide
Jiyoung Min, Jiwon Shinn, Hun-Sung Kim
Cardiovasc Prev Pharmacother. 2022;4(2):87-93.   Published online April 27, 2022
DOI: https://doi.org/10.36011/cpp.2022.4.e12
Funded: National Research Foundation of Korea, Ministry of Science and ICT
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  • 14 Download
Abstract PDFSupplementary Material
Background
Liraglutide, a drug used for the management of obesity, has many known side effects. In this study, we developed a predictive model for the occurrence of liraglutide-related side effects using data from electronic medical records (EMRs).
Methods
This study included 237 patients from Seoul St. Mary's Hospital and Eunpyeong St. Mary's Hospital who were prescribed liraglutide. An endocrinologist obtained medical data through an EMR chart review. Model performance was evaluated using the mean of the area under the receiver operating characteristic curve (AUROC) with a 95% confidence interval (CI).
Results
A predictive model was developed for patients who were prescribed liraglutide. However, 37.1% to 75.5% of many variables were missing, and the AUROC of the developed predictive model was 0.630 (95% CI, 0.551–0.708). Patients who had previously taken antiobesity medication had significantly fewer side effects than those without previous antiobesity medication use (20.7% vs. 41.4%, P<0.003). The risk of side effect occurrence was significantly higher in patients with diabetes than in patients without diabetes by 2.389 times (odds ratio, 2.389; 95% CI, 1.115–5.174).
Conclusions
This study did not successfully develop a predictive model for liraglutide-related side effects, primarily due to issues related to missing data. When prescribing antiobesity drugs, detailed records and basic blood tests are expected to be essential. Further large-scale studies on liraglutide-related side effects are needed after obtaining high-quality data.
Indirect comparison of nonvitamin K oral anticoagulants and left atrial appendage occlusion
Sung-Hwan Kim, So-Yoon Park, Seung-Sik Hwang
Cardiovasc Prev Pharmacother. 2022;4(1):18-25.   Published online January 18, 2022
DOI: https://doi.org/10.36011/cpp.2022.4.e1
Funded: Catholic Medical Center Research Foundation
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Abstract PDFSupplementary Material
Background
Anticoagulation is important in atrial fibrillation (AF) patients to reduce the occurrence of thrombotic events. We evaluated the efficacy and safety of percutaneous left atrial appendage occlusion (LAAO) as an alternative to systemic anticoagulation through an indirect comparative analysis.
Methods
An indirect comparative analysis of nonvitamin K oral anticoagulants (NOACs) and LAAO was conducted. Comparisons were made using data from four landmark randomized clinical trials (RE-LY, ROCKET-AF, ARISTOTLE, and PROTECT AF). Using warfarin as the common comparator, an indirect comparison was performed using data from each trial, and the relative risk was calculated between NOACs and LAAO.
Results
NOACs and LAAO showed similar results for the reduction of stroke and systemic embolism, with a non-statistically significant trend favoring NOACs (hazard ratio [HR], 0.74; 95% confidence interval [CI], 0.37–1.46 for dabigatran; HR, 0.99; 95% CI, 0.50–1.92 for rivaroxaban; HR, 0.89; 95% CI, 0.45–1.74 for apixaban). Significantly fewer major bleeding and procedure-related complications were found in patients treated with apixaban compared with LAAO (HR, 0.45; 95% CI, 0.26–0.75). Cardiovascular death occurred more frequently in patients administered NOACs than in patients with LAAO (HR, 2.28; 95% CI, 1.03–5.10 for dabigatran; HR, 2.41; 95% CI, 1.09–5.42 for rivaroxaban; HR, 2.40; 95% CI, 1.10–5.36 for apixaban).
Conclusions
The rate of all-cause death was similar between NOACs and LAAO. Compared with LAAO, NOACs led to a nonsignificant numerical decrease in stroke and embolism in AF patients. Significantly fewer safety events occurred in patients treated with apixaban. LAAO significantly reduced cardiovascular death.
Review Article
Anti-inflammatory effects of colchicine on coronary artery disease
Hun-Jun Park
Cardiovasc Prev Pharmacother. 2022;4(1):7-12.   Published online January 20, 2022
DOI: https://doi.org/10.36011/cpp.2022.4.e5
Funded: National Research Foundation of Korea
  • 1,149 View
  • 49 Download
Abstract PDF
Inflammation plays a crucial role in the pathophysiology of coronary artery disease (CAD). Several types of sterile inflammation are mediated through the nucleotide-binding oligomerization domain-like receptor pyrin domain containing 3 (NLRP3) inflammasome. Colchicine has recently been shown to effectively block NLRP3 inflammasome assembly in addition to several other actions on inflammatory cells. Recent evidence also points to favorable effects of colchicine in patients with CAD, including lower levels of inflammatory markers, coronary plaque stabilization, and more favorable cardiac recovery after injury. This review focuses on the role of colchicine in the process of atherosclerosis and discusses its potential as a therapeutic option for the prevention and treatment of CAD.
Original Articles
Relationship between Retinal Nerve Fiber Layer Defects and Coronary Artery Calcium Score in Patients at Risk for Cardiovascular Disease
Chan Joo Lee, Joo Youn Shin, Jaewon Oh, Sang-Hak Lee, Seok-Min Kang, Sungha Park, Suk Ho Byeon
Cardiovasc Prev Pharmacother. 2021;3(4):95-105.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e11
Funded: National Research Foundation of Korea, Ministry of Science and ICT
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Abstract PDF
Background
Noninvasive fundus imaging may provide useful information on blood vessels. This study investigated the relationship between localized retinal nerve fiber layer defects (RNFLDs) and vascular biomarkers.
Methods
This study included 1,316 participants without cardiovascular disease who were registered in a cardiovascular high-risk cohort. Examined vascular biomarkers included central hemodynamics, carotid-femoral pulse wave velocity (cfPWV), left ventricular hypertrophy (LVH) on electrocardiogram, and coronary artery calcium score (CACS). Fundus photography and optical coherence tomography were used to evaluate RNFLDs. The associations between RNFLDs and established high-risk cutoff points for each biomarker (central blood pressure [BP] ≥125/80 mmHg, central pulse pressure [PP] ≥50 mmHg, cfPWV ≥10 m/s, presence of LVH, and CACS ≥300) were assessed.
Results
RNFLD was identified in 394 participants (29.9%) who had higher fasting glucose level, lower renal function, and higher BP than those without RNFLDs. Additionally, central BP, central PP, cfPWV, CACS, and the percentage of subjects with LVH were higher in the RNFLD group. After adjusting for confounders, RNFLDs were not associated with LVH or an elevated central BP, central PP, or cfPWV. However, they were associated with an elevated CACS (odds ratio, 1.44; 95% confidence interval, 1.04–2.00; p=0.029).
Conclusions
Non-glaucomatous localized RNFLDs were associated with elevated CACS. Therefore, evaluating RNFLDs using fundus imaging may aid in the assessment of cardiovascular disease risk.
Development of a Predictive Model for Glycated Hemoglobin Values and Analysis of the Factors Affecting It
HyeongKyu Park, Da Young Lee, So young Park, Jiyoung Min, Jiwon Shinn, Dae Ho Lee, Soon Hyo Kwon, Hun-Sung Kim, Nan Hee Kim
Cardiovasc Prev Pharmacother. 2021;3(4):106-114.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e14
Funded: National Research Foundation of Korea, Ministry of Science and ICT
  • 1,181 View
  • 32 Download
Abstract PDF
Background
Glycated hemoglobin (HbA1c), which reflects the patient's blood sugar level, can only be measured in a hospital setting. Therefore, we developed a model predicting HbA1c using personal information and self-monitoring of blood glucose (SMBG) data solely obtained by a patient.
Methods
Leave-one-out cross-validation (LOOCV) was performed at two university hospitals. After measuring the baseline HbA1c level before SMBG (Pre_HbA1c), the SMBG was recorded over a 3-month period. Based on these data, an HbA1c prediction model was developed, and the actual HbA1c value was measured after 3 months. The HbA1c values of the prediction model and actual HbA1c values were compared. Personal information was used in addition to SMBG data to develop the HbA1c predictive model.
Results
Thirty model training sessions and evaluations were conducted using LOOCV. The average mean absolute error of the 30 models was 0.659 (range, 0.005–2.654). Pre_HbA1c had the greatest influence on HbA1c prediction after 3 months, followed by post-breakfast blood glucose level, oral hypoglycemic agent use, fasting glucose level, height, and weight, while insulin use had a limited effect on HbA1c values.
Conclusions
The patient's SMBG data and personal information strongly influenced the HbA1c predictive model. In the future, it will be necessary to develop sophisticated predictive models using large samples for stable SMBG in patients.
Modeling of Changes in Creatine Kinase after HMG-CoA Reductase Inhibitor Prescription
Hun-Sung Kim, Jiyoung Min, Jiwon Shinn, Oak-Kee Hong, Jang-Won Son, Seong-Su Lee, Sung-Rae Kim, Soon Jib Yoo
Cardiovasc Prev Pharmacother. 2021;3(4):115-123.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e15
Funded: National Research Foundation of Korea, Ministry of Science and ICT
  • 1,002 View
  • 14 Download
Abstract PDF
Background
Statin-associated muscle symptoms are one of the side effects that physicians should consider when prescribing statins. In this study, creatine kinase (CK) levels were measured following statin prescription, and various factors affecting the CK levels were determined using machine learning.
Methods
Changes in the CK were observed every 3 months for a 12-month period in patients who received statins for the first time at Seoul St. Mary's Hospital. For each visit, we developed four basic models based on changes in the CK levels. Extreme gradient boosting, a scalable end-to-end tree boosting algorithm, which employs a decision-tree-based ensemble machine learning algorithm, was used for the prediction of changes in the CK.
Results
A total of 23,860 patients were included. Among them, 19 patients (0.08%) had increased CK levels of 2,000 IU·L−1 or more 3 months after statin prescription, and 65 patients (0.27%) exhibited CK levels of over 2,000 IU·L−1 at least once during the 12-month study period. The area under the receiver operator characteristic of each model for each visit was 0.709–0.769, and the accuracy was 0.700–0.803. In each of the models, the variables that had the strongest influence on changes in the CK were sex and previous CK value.
Conclusions
Through machine learning, factors influencing changes in the CK were identified. These results will provide the basis for future research, through which the optimal parameters of the CK prediction model can be found and the model can be used in clinical applications.
Special Articles
Perceptron: Basic Principles of Deep Neural Networks
Eung-Hee Kim, Hun-Sung Kim
Cardiovasc Prev Pharmacother. 2021;3(3):64-72.   Published online July 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e9
Funded: National Research Foundation of Korea, Ministry of Science and ICT
  • 662 View
  • 12 Download
Abstract PDF
Big data, artificial intelligence, machine learning, and deep learning have received considerable attention in the medical field. Attempts to use such machine learning in areas where medical decisions are difficult or necessary are continuously being made. To date, there have been many attempts to solve problems associated with the use of machine learning by using deep learning; hence, physicians should also have basic knowledge in this regard. Deep neural networks are one of the most actively studied methods in the field of machine learning. The perceptron is one of these artificial neural network models, and it can be considered as the starting point of artificial neural network models. Perceptrons receive various inputs and produce one output. In a perceptron, various weights (ω) are given to various inputs, and as ω becomes larger, it becomes an important factor. In other words, a perceptron is an algorithm with both input and output. When an input is provided, the output is produced according to a set rule. In this paper, the decision rules of the perceptron and its basic principles are examined. The intent is to provide a wide range of physicians with an understanding of the latest machine-learning methodologies based on deep neural networks.
Update on the Pharmacotherapy of Heart Failure with Reduced Ejection Fraction
Eui-Soon Kim, Jong-Chan Youn, Sang Hong Baek
Cardiovasc Prev Pharmacother. 2020;2(4):113-133.   Published online October 31, 2020
DOI: https://doi.org/10.36011/cpp.2020.2.e17
Funded: National Research Foundation of Korea, Ministry of Science, ICT and Future Planning
  • 3,928 View
  • 48 Download
  • 8 Citations
Abstract PDF
Heart failure (HF) is an important cardiovascular disease because of the increasing prevalence, high morbidity and mortality, and rapid expansion of health care costs. Over the past decades, efforts have been made to modify the prognosis of patients with HF. Regarding HF with reduced ejection fraction (HFrEF), several drugs have shown to improve mortality and morbidity, based on large-scale randomized controlled trials, leading to a critical paradigm shift in its pharmacological treatment. The paradigm of HFrEF pathophysiology has shifted from cardiorenal disease to hemodynamic changes, and neurohormonal activation is currently considered the prime pathophysiological mechanism of HFrEF. This review summarizes evidence on the pharmacological management of HFrEF derived from major randomized controlled trials, which have accomplished improvements in survival benefits.
Barriers in Salt Reduction Strategies: Time to Acting for the Future
Yong-Jae Kim
Cardiovasc Prev Pharmacother. 2020;2(4):134-141.   Published online October 31, 2020
DOI: https://doi.org/10.36011/cpp.2020.2.e16
Funded: Korea Disease Control and Prevention Agency
  • 685 View
  • 9 Download
Abstract PDF
Salt reduction is important for reducing hypertension and the risk of cardiovascular events and stroke. Despite knowledge about the ill consequences, many people continue to consume high levels of salt in their diet. This paper introduces salt-reducing programs for individual, population, and country-level strategies to reduce salt intake. To effectively decrease salt intake, it is necessary to reduce the consumption of high-salt foods and replace high-salt seasonings with low-salt alternatives. Thus, healthcare professionals must effectively provide information on salt-reduction for patients with hypertension. Social strategies, such as voluntary sodium reduction targets for the food industry, are necessary to promote population strategies for salt reduction. In this paper, we examine a brief report on new salt intake values based on chronic disease risk reduction and explain the utilization of mobile health technologies to reduce salt consumption. Considering the relationship between dietary salt intake and the risk of chronic disease, ways to remove the barriers to strategies for salt reduction should be considered, as it is the most effective way for the prevention and control of hypertension and cardiovascular disease in the future.
Review Articles
Recent Technology-Driven Advancements in Cardiovascular Disease Prevention
Jisan Lee, Hun-Sung Kim, Dai-Jin Kim
Cardiovasc Prev Pharmacother. 2019;1(2):43-49.   Published online October 31, 2019
DOI: https://doi.org/10.36011/cpp.2019.1.e7
Funded: Ministry of SMEs and Startups, National Research Foundation of Korea, Ministry of Education
  • 1,970 View
  • 7 Download
  • 3 Citations
Abstract PDFSupplementary Material
Recent dramatic developments in information and communication technologies have been widely applied to medicine and healthcare. In particular, biometric sensors in wearable devices linked to smartphones are collecting vast amounts of personal health data. To best use these accumulated data, personalized healthcare services are emerging, and digital platforms are being developed and studied to enable data integration and analysis. The implementation of biometric sensors and smartphones for cardiovascular and cerebrovascular healthcare emerged from the research on the feasibility and efficacy of the devices in the clinical environment. It is important to understand the recent research trends in data generation, integration, and application to prevent and treat cardiovascular and cerebrovascular diseases. This paper describes these recent developments in treating cardiovascular diseases.
Asian Cohort Studies on Cardiovascular Risk Factors in Childhood
Sun Jae Jung, Hyeon Chang Kim, Il Suh
Cardiovasc Prev Pharmacother. 2019;1(1):3-9.   Published online July 31, 2019
DOI: https://doi.org/10.36011/cpp.2019.1.e2
Funded: National Research Foundation of Korea
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  • 7 Download
  • 1 Citations
Abstract PDF
Long-term cohort studies have shown that cardiovascular risk factors measured during childhood were associated with levels of adult cardiovascular risk factors and also with the lifetime risk of cardiovascular disease (CVD). However, most of the epidemiologic evidence was from Western studies and relatively small in the Asian population. From the literature, we identified and reviewed 8 Asian cohort studies focusing on cardiovascular risk factors among children. The Asian cohort studies have confirmed that childhood risk factors can predict later levels of adult risk factors. Besides, it has been shown that childhood risk factors are associated with intermediate phenotypes, such as metabolic disturbance and degenerative vascular changes, in adulthood. These findings reaffirmed the importance of screening and managing cardiovascular risk factors from early life in Asia. However, there is little evidence on CVD incidence and mortality because there is no Asian cohort study, which observed from childhood until middle-aged or old ages. Longer follow-up data are required to measure the impact of childhood cardiovascular risk factors, especially since obesity and other cardiovascular risk factors are increasing in Asian children and adolescents.

CPP : Cardiovascular Prevention and Pharmacotherapy