Natural History of Coronary Artery Disease Studied by Coronary Arteriography

Storstein, O; Enge, Ivar; Erikssen, J; Thaulow, Erik

doi:10.1111/j.0954-6820.1981.tb09775.x

Cited by 11 publications

(1 citation statement)

References 17 publications

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“…Advancing age comes with accumulating amounts of coronary atherosclerosis. This increased plaque burden increases the risk of coronary events [ 14 ]. Furthermore, growing older is often associated with other major risk factors, such as hypertension and diabetes.…”

Section: Discussionmentioning

confidence: 99%

Risk Assessment of Cardiovascular Disease Among Adults Attending Primary Healthcare Centers in Riyadh City 2015

Alibrahim¹,

Sharaheeli²,

Alassaf³

et al. 2022

Cureus

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Background: The prevalence of cardiovascular disease (CVD) risk factors is expected to rise in Saudi Arabia as the prevalence of CVD risk factors rises. Effective primary CVD prevention necessitates risk assessment to categorize patients and select the most appropriate intervention for each category.Objectives: To estimate the prevalence of CVD at primary healthcare (PHC) in Riyadh city and to categorize the at-risk population as a slow, intermediate, or high risk of CVD.Methods: A cross-sectional study was carried out at seven PHC centers in Riyadh. Seven hundred participants (half of whom were males and the other half females) were selected at random from PHCs visitors, and data was collected using a structured questionnaire, as well as required measurements and laboratory investigations. The World Health Organization risk prediction charts were used to calculate CVD risk. Participants were assigned to one of three CVD risk categories (low, intermediate, high).Results: Obesity was found to be the most common risk factor found in this study (53.2%). Overweight (31.2%), with females having higher BMI levels. The study found that 83.4% of participants had low CVD risk, 12.9% had intermediate risk, and 3.7% had high CVD risk category. Age, systolic blood pressure, cholesterol level, smoking, and prior diagnosis of diabetes were all statistically significant predictors of moderate and high CVD risk. Conclusion: CVD risk factors were discovered to be common among study participants. It requires healthcare decision-makers to engage in community-based interventions to decrease the risk of CVD.

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Section: Discussionmentioning

confidence: 99%

Risk Assessment of Cardiovascular Disease Among Adults Attending Primary Healthcare Centers in Riyadh City 2015

Alibrahim¹,

Sharaheeli²,

Alassaf³

et al. 2022

Cureus

View full text Add to dashboard Cite

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On the prediction and prevention of myocardial infarctions: models based on retrospective and doubly censored prospective data

Cooil

Raggi

2005

Statist. Med.

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Early detection of coronary heart disease (CHD) in its pre-clinical stages may offer a way to reduce the impact of this endemic disease on society. Coronary calcification accompanies the development of an atherosclerotic plaque, the pathological substrate of CHD, and its identification is currently possible by means of electron beam tomography (EBT). This is a non-invasive imaging test that quantifies the extent of coronary artery plaque calcification by means of a calcium score. In this study, we show that an age-sex based calcium score percentile (CS%) provides an invaluable predictor for myocardial infarction (MI), and examine how CS% is related to traditional risk factors. We study two separate groups of patients: 172 patients who underwent EBT screening after surviving an MI (retrospective group); and 676 asymptomatic subjects who were screened and followed for several years for the occurrence of an MI (prospective group). We use CS% with traditional risk factors in logistic regression models to: (1) compare patients in the retrospective and prospective groups, and (2) develop a mortality model for MIs that occurred in the prospective group. These logistic regressions are used to develop a joint model for the relative log-odds of an MI, which is non-linear in the covariates of the mortality model. We also use baseline covariates in the prospective group to fit an event-time regression model and estimate probabilities for 2 and 3 year exposure periods. The event-time regression provides independent estimates of the relative odds that are associated with risk factors. CS%, smoking, and their interaction were preeminent as predictors in the joint model for the relative odds of an MI and in the event-time regression, although the effects of smoking and CS% were generally subadditive. These models provide important information on the risks associated with elevated CS% levels.

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