New Questions on PAD Alter Framingham Risk Assessment

2006 ◽  
Vol 39 (17) ◽  
pp. 43
Author(s):  
BRUCE JANCIN
Keyword(s):  
Risk Assessment ◽  
Framingham Risk

Skin cholesterol adds to Framingham risk assessment

2006 ◽  
Vol 152 (4) ◽  
pp. 694-696 ◽  
Author(s):  
Dennis L. Sprecher ◽  
Gregory L. Pearce
Keyword(s):  
Risk Assessment ◽  
Framingham Risk

scholarly journals FRAMINGHAM RISK ASSESSMENT BY ACTUAL CARDIOVASCULAR EVENT DATA IN RENAL TRANSPLANT RECIPIENTS

2008 ◽  
Vol 86 (Supplement) ◽  
pp. 472-473
Author(s):  
E S. Woodle ◽  
A H. Rike ◽  
J Everly ◽  
R R. Alloway ◽  
M Cardi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Renal Transplant ◽  
Cardiovascular Event ◽  
Renal Transplant Recipients ◽  
Event Data ◽  
Transplant Recipients ◽  
Framingham Risk

scholarly journals New Zealand Diabetes Cohort Study cardiovascular risk score for people with Type 2 diabetes: validation in the PREDICT cohort

2012 ◽  
Vol 4 (3) ◽  
pp. 181 ◽  
Author(s):  
Tom Robinson ◽  
C Raina Elley ◽  
Sue Wells ◽  
Elizabeth Robinson ◽  
Tim Kenealy ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Cohort Study ◽  
New Zealand ◽  
Cardiovascular Event ◽  
Cvd Risk ◽  
Risk Equation ◽  
Framingham Risk

INTRODUCTION: New Zealand (NZ) guidelines recommend treating people for cardiovascular disease (CVD) risk on the basis of five-year absolute risk using a NZ adaptation of the Framingham risk equation. A diabetes-specific Diabetes Cohort Study (DCS) CVD predictive risk model has been developed and validated using NZ Get Checked data. AIM: To revalidate the DCS model with an independent cohort of people routinely assessed using PREDICT, a web-based CVD risk assessment and management programme. METHODS: People with Type 2 diabetes without pre-existing CVD were identified amongst people who had a PREDICT risk assessment between 2002 and 2005. From this group we identified those with sufficient data to allow estimation of CVD risk with the DCS models. We compared the DCS models with the NZ Framingham risk equation in terms of discrimination, calibration, and reclassification implications. RESULTS: Of 3044 people in our study cohort, 1829 people had complete data and therefore had CVD risks calculated. Of this group, 12.8% (235) had a cardiovascular event during the five-year follow-up. The DCS models had better discrimination than the currently used equation, with C-statistics being 0.68 for the two DCS models and 0.65 for the NZ Framingham model. DISCUSSION: The DCS models were superior to the NZ Framingham equation at discriminating people with diabetes who will have a cardiovascular event. The adoption of a DCS model would lead to a small increase in the number of people with diabetes who are treated with medication, but potentially more CVD events would be avoided. KEYWORDS: Cardiovascular disease; diabetes; prevention; risk assessment; reliability and validity

Abstract 144: Residual Cardiovascular Risk After Cardiac Rehabilitation

2014 ◽  
Vol 7 (suppl_1) ◽  
Author(s):  
Divya Ratan Verma ◽  
Shirely Noon ◽  
Taylor Rose ◽  
Dawn Young ◽  
Lillian Khor
Keyword(s):  
Risk Assessment ◽  
Cardiac Rehabilitation ◽  
Patient Characteristics ◽  
Residual Risk ◽  
Risk Scores ◽  
Central Adiposity ◽  
Risk Calculator ◽  
Residual Cardiovascular Risk ◽  
Framingham Risk ◽  
Ascvd Risk

Background: CAD is the leading cause of death and disability in US. Cardiac rehabilitation (CR) program is an important secondary-prevention intervention to reduce mortality, cardiovascular (CV) events, & disability. At start of CR program, patients undergo extensive risk assessment to guide risk reduction goals. However, the residual risk at CR completion is not well studied. We sought to investigate the residual modifiable risk factors of patients completing CR Methods: We retrospectively reviewed our center’s data on consecutive patients between October 2012 and November 2013 who were entered into the American Association of Cardiovascular and Pulmonary Rehabilitation (AACVPR) registry and identified those who completed the CR program. We calculated their residual risk using the newly released ACC/AHA’s ‘Pooled Cohort Equations CV Risk Calculator’ (ACC/AHA risk) and Framingham risk (FR) calculator Results: Out of 128 consecutive CR participants, 44 (34%) completed the program. Patient characteristics and risk assessment are summarized in table 1. As per AACVPR risk stratification algorithm, 37 (84%) of patients were intermediate to high risk. Compared to the start, at completion of CR program, there was a significant improvement in 6-minute walk distance (365±107 vs 484± 137, p<0.001), favorable reduction in total cholesterol, LDL-C, non-HDL-C (p<0.001) and metabolic syndrome (p=0.02). At time of completion, calculated 10 year CV risk using ACC/AHA risk calculator was still elevated (14±10%), while 64% of patients had elevated risk≥7.5% (mean 19.3±9%). FR estimation was low (9±4%). The two risk scores showed moderate correlation (Pearson’s r=0.6, p<0.001), but the ACC/AHA risk was significantly higher than the FR estimation (p<0.001). In multivariate linear regression model, waist circumference (WC) at discharge was significant modifiable independent predictor of ASCVD risk, while systolic BP showed a trend towards significance Conclusion: Successful completion of CR program is associated with improvement in CV risk profile. However, the residual CV risk remains elevated at time of CR completion and is driven by WC & systolic BP. Elevated WC from central adiposity is the main residual atherogenic CV risk factor post CR completion. Further research on significant WC reduction during CR is needed

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