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CPP : Cardiovascular Prevention and Pharmacotherapy

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Volume 3(4); October 2021
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Review Articles
Body Weight Change and Cardiovascular Disease: Effect of Weight Gain, Weight Loss, and Weight Cycling
Jung-Hwan Cho, Eun-Jung Rhee, Won-Young Lee
Cardiovasc Prev Pharmacother. 2021;3(4):73-81.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e12
  • 1,004 View
  • 43 Download
Abstract PDF
Obesity is an independent risk factor for the development and progression of cardiovascular disease (CVD). Various cardiovascular outcomes are related to the association between body weight change and CVD. Metabolically healthy obese individuals could have a better prognosis in terms of cardiovascular morbidity and mortality than metabolically unhealthy obese individuals. Smoking cessation causes significant weight gain and consequent deterioration of the metabolic profile despite not impairing the cardiovascular benefits. Intentional weight loss has a consistent cardiovascular protective effect, but unintentional weight loss due to progressive catabolism and loss of muscle mass could be associated with poor cardiovascular outcomes. Obese individuals who are successful in losing weight with subsequent regain (weight cycling) could have an unfavorable cardiometabolic profile and the risk of CVD. Further studies are needed to evaluate the impact of weight changes on CVD by identifying unknown pathophysiology and to decide appropriate management and interventions for various phenotypes of weight change.
Diabetes in People with Disabilities: a Call for Action
Inha Jung, Eun-Jung Rhee, Won-Young Lee
Cardiovasc Prev Pharmacother. 2021;3(4):82-85.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e13
  • 365 View
  • 13 Download
Abstract PDF
Previous researchers have suggested that people with disabilities have a higher prevalence and risk of type 2 diabetes mellitus than the general population. As diabetes is a well-known risk factor for cardiovascular disease (CVD), developing strategies to prevent and delay its occurrence in people with disabilities is important to reduce the burden of CVD. However, people with disabilities are often excluded from studies and have received little attention from public health authorities and researchers. These unmet needs for health care and being left out of research may affect the progression of diabetes in people with disabilities. Herein, we would like to briefly discuss the increased risk of diabetes and related conditions in people with disabilities and suggest that more attention should be given to this population.
Antiplatelet Therapy for Secondary Stroke Prevention in Patients with Ischemic Stroke or Transient Ischemic Attack
Kyung-Yul Lee
Cardiovasc Prev Pharmacother. 2021;3(4):86-94.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e10
  • 783 View
  • 22 Download
Abstract PDF
The risk of stroke recurrence is highest in the acute phase after transient ischemic attack (TIA) or ischemic stroke. Therefore, patients with TIA or ischemic stroke should be treated with antiplatelet medication for stroke prevention. The short-term use of dual antiplatelet therapy between 21 and 90 days may be considered in those with acute minor stroke or TIA and highrisk of recurrence. However, the long-term use of dual antiplatelet therapy is not recommended due to the risk of bleeding. The current stroke guideline does not specify the administration of an antiplatelet for the secondary prevention of ischemic stroke. However, as clinical studies progress, antiplatelet therapy may become a personalized treatment in the future.
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
  • 330 View
  • 15 Download
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
  • 838 View
  • 31 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
  • 566 View
  • 11 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.
Association between Myocardial Infarction Location and In-Hospital Mortality in Iran: A Nationwide Study
Mohammad Shahbaz, Seyed Saeed Hashemi Nazari, Amineh Salehipour, Roya Karimi
Cardiovasc Prev Pharmacother. 2021;3(4):124-133.   Published online October 31, 2021
DOI: https://doi.org/10.36011/cpp.2021.3.e16
  • 379 View
  • 13 Download
Abstract PDF
Background
Myocardial infarction (MI) is one of the most important health problems in the world, including Iran. The rate of in-hospital mortality in MI patients ranges from 7.7% to 19.2% in different countries. Despite the promotion and utilization of new therapeutic approaches, MI-related morbidity and mortality have remained high . The recognition of risk factors for MI-related mortality plays an important role in reducing post-MI mortality.
Methods
In this study, we used national MI registry data. In total, 33,831 patients who had been hospitalized in the coronary care unit of Iranian hospitals from 2012 to 2014 were analyzed. Using multivariable logistic regression, we estimated the impact of various risk factors on in-hospital mortality after MI.
Results
The in-hospital mortality rate in patients with ST-elevation MI was higher than that of patients with non–ST-elevation MI. In-hospital mortality was most strongly associated with left-location MI (odds ratio [OR] relative to the non-ST-elevation MI group, 2.15), in comparison with middle-location MI (OR, 1.47) and right-location MI (OR, 1.43). Ventricular fibrillation (OR, 7.7) and ventricular tachycardia (OR, 2.78) were predictors of in-hospital mortality. Receiving treatment reduced the odds of death and age, sex, and diabetes were risk factors associated with in-hospital mortality after MI.
Conclusions
Age, sex, right bundle branch block arrhythmia, atrial fibrillation, ventricular tachycardia, left bundle branch block arrhythmia, ventricular fibrillation, dyspnea, diabetes, and ST-elevation MI were associated with increased ORs for mortality after MI. Thus, patients with these factors require special attention during hospitalization.

CPP : Cardiovascular Prevention and Pharmacotherapy