In this study, we evaluated the performance of the Framingham cardiovascular disease (CVD) and the United Kingdom Prospective Diabetes Study (UKPDS) risk equations to predict the 10-year CVD risk among type 2 diabetes mellitus (T2DM) patients in Malaysia. T2DM patients (n = 660) were randomly selected, and their 10-year CVD risk was calculated using both the Framingham CVD and UKPDS risk equations. The performance of both equations was analyzed using discrimination and calibration analyses. The Framingham CVD, UKPDS coronary heart disease (CHD), UKPDS Fatal CHD, and UKPDS Stroke equations have moderate discrimination (area under the receiver operating characteristic [aROC] curve = 0.594-0.709). The UKPDS Fatal Stroke demonstrated a good discrimination (aROC curve = 0.841). The Framingham CVD, UKPDS Stroke, and UKPDS Fatal Stroke equations showed good calibration ( = .129 to .710), while the UKPDS CHD and UKPDS Fatal CHD are poorly calibrated ( = .035; = .036). The UKPDS is a better prediction equation of the 10-year CVD risk among T2DM patients compared with the Framingham CVD equation.
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http://dx.doi.org/10.1177/1010539519873487 | DOI Listing |
Comput Med Imaging Graph
January 2025
Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, South Korea; Department of Family Medicine, Seoul National University Hospital, Seoul, South Korea. Electronic address:
This study introduces the Deep Learning-based Cardiovascular Disease Incident (DL-CVDi) score, a novel biomarker derived from routine abdominal CT scans, optimized to predict cardiovascular disease (CVD) risk using deep survival learning. CT imaging, frequently used for diagnosing various conditions, contains opportunistic biomarkers that can be leveraged beyond their initial diagnostic purpose. Using a Cox proportional hazards-based survival loss, the DL-CVDi score captures complex, non-linear relationships between anatomical features and CVD risk.
View Article and Find Full Text PDFPLoS One
January 2025
Equity Research and Innovation Center, Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
Background: Accurate assessment of cardiovascular disease (CVD) risk is crucial for effective prevention and resource allocation. However, few CVD risk estimation tools consider social determinants of health (SDoH), despite their known impact on CVD risk. We aimed to estimate 10-year CVD risk in the Eastern Caribbean Health Outcomes Research Network Cohort Study (ECS) across multiple risk estimation instruments and assess the association between SDoH and CVD risk.
View Article and Find Full Text PDFJ Psychiatr Res
January 2025
Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa; South African Medical Research Council Genomics of Brain Disorders Unit, Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, South Africa.
Background: The pathophysiology of posttraumatic stress disorder (PTSD) involves dysregulation of stress-sensitive biological systems due to repeated trauma exposure, predisposing individuals to the development of cardiovascular disease (CVD). Allostatic load (AL), an indicator of maladaptive stress responses, could shed light on the underlying biological mechanisms. We determined whether CVD risk and AL were associated with trauma load and resilience in women with PTSD and trauma-exposed controls (TEC).
View Article and Find Full Text PDFClin Rheumatol
January 2025
Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Science, School of Biological Sciences, Faculty of Biological Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
Introduction: Risk prediction is important for preventing and managing cardiovascular disease (CVD). CVD risk prediction tools designed for the general population may be inaccurate in people with inflammatory diseases.
Objectives: To investigate the performance of four cardiovascular risk prediction tools (QRISK3, Framingham Risk Score, Reynolds Risk Score and SCORE) in psoriatic arthritis (PsA) and psoriasis.
Diabetol Metab Syndr
January 2025
Department of Radiology, Shanghai Health and Medical Center, No. 67 Dajishan, Binhu District, Wuxi, 214065, China.
Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by the presence of at least one cardiovascular disease (CVD) risk factor, underscoring its potential to elevate CVD risk in affected individuals. However, evidence linking MASLD to subclinical coronary atherosclerosis remains scarce, and further investigations are necessary to elucidate the independent role of varying MASLD severities as a CVD risk factor.
Methods: This study analyzed 7,507 participants aged ≥ 40 who underwent comprehensive health evaluations at the Shanghai Health and Medical Center.
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