scholarly journals An independent external validation and evaluation of QRISK cardiovascular risk prediction: a prospective open cohort study

BMJ ◽  
2009 ◽  
Vol 339 (jul07 2) ◽  
pp. b2584-b2584 ◽  
Author(s):  
G. S Collins ◽  
D. G Altman
Keyword(s):  
Cohort Study ◽  
Cardiovascular Risk ◽  
Risk Prediction ◽  
External Validation ◽  
Cardiovascular Risk Prediction

scholarly journals External validation and comparison of four cardiovascular risk prediction models with data from the Australian Diabetes, Obesity and Lifestyle study

2019 ◽  
Vol 210 (4) ◽  
pp. 161-167 ◽  
Author(s):  
Loai Albarqouni ◽  
Jennifer A Doust ◽  
Dianna Magliano ◽  
Elizabeth LM Barr ◽  
Jonathan E Shaw ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Prediction Models ◽  
External Validation ◽  
Risk Prediction Models ◽  
Cardiovascular Risk Prediction

scholarly journals Performance of the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis in a geographically distant National Register-based cohort: an external validation

RMD Open ◽  
2018 ◽  
Vol 4 (2) ◽  
pp. e000771 ◽  
Author(s):  
Lotta Ljung ◽  
Peter Ueda ◽  
Katherine P Liao ◽  
Jeffrey D Greenberg ◽  
Carol J Etzel ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cardiovascular Risk ◽  
Risk Stratification ◽  
Risk Prediction ◽  
External Validation ◽  
Risk Groups ◽  
Prediction Score ◽  
Swedish Population ◽  
Quality Register ◽  
Cardiovascular Risk Prediction

BackgroundCardiovascular (CV) risk stratification for patients with rheumatoid arthritis (RA) should facilitate evidence-based management. Prior work has derived an internally validated a CV risk score, the Expanded Cardiovascular Risk Prediction Score for Rheumatoid Arthritis (ERS-RA), using US data. The aim of this study was to perform an external validation among unselected patients with RA from Europe.MethodsThree large, partially overlapping, cohorts of patients with RA from the Swedish Rheumatology Quality register were identified for external validation, two with information on smoking and two with close to 10 years of median follow-up. The 10 -year rate of first CV events was assessed using the Kaplan-Meier method. The performance of ERS-RA was assessed using C-index and comparisons of observed versus predicted risks.ResultsThe C-index for ERS-RA varied across the three RA cohorts, from 0.75 to 0.78. Predicted risks corresponded well to observed risks among individuals with ≤10 % observed 10- year CV risk, but underestimated risk in individuals with a higher observed risk. In the absence of data on smoking, ERS-RA underestimated the CV risk by 3.3%, whereas in the cohorts including data on smoking, the calibration was within 1% (0.06% and 0.7%). In the clinically relevant risk intervals (<5%, 5.0%–<7.5%, 7.5%–<10%), ERS-RA performed well.ConclusionsIn an unselected Swedish population with RA, ERS-RA performed well, although the 10-year CV risk was underestimated in high-risk groups and in the absence of data on smoking. ERS-RA could be considered as a risk stratification tool for targeted preventive interventions in clinical rheumatology practice.

Cardiovascular Risk Prediction using JBS3 Tool: A Kerala based Study

2020 ◽  
Vol 16 ◽  
Author(s):  
Paulin Paul ◽  
Noel George ◽  
B. Priestly Shan
Keyword(s):  
Logistic Regression ◽  
Cardiovascular Risk ◽  
Risk Prediction ◽  
Goodness Of Fit ◽  
Significant Risk ◽  
Lifetime Risk ◽  
British Society ◽  
Cvd Risk ◽  
South Indian ◽  
Cardiovascular Risk Prediction

Background: The accuracy of Joint British Society calculator3 (JBS3) cardiovascular risk prediction may vary within Indian population, and is not yet studied using south Indian Kerala based population data. Objectives: To evaluate the cardiovascular disease (CV) risk estimation using the traditional CVD risk factors (TRF) in Kerala based population. Methods: This cross sectional study has 977 subjects aged between 30 and 80 years. The traditional CVD risk markers are recorded from the medical archives of clinical locations at Ernakulum district, in Kerala The 10 year risk categories used are low (<7.5%), intermediate (≥7.5% and <20%), and high (≥20%). The lifetime classifications low lifetime (≤39%) and high lifetime (≥40%) are used. The study was evaluated using statistical analysis. Chi-square test was done for dependent and categorical CVD risk variable comparison. Multivariate ordinal logistic regression for 10-year risk model and odds logistic regression analysis for lifetime model was used to identify significant risk variables. Results: The mean age of the study population is 52.56±11.43 years. The risk predictions has 39.1% in low, 25.0% in intermediate, and 35.9% had high 10-year risk. The low lifetime risk had 41.1% and 58.9% is high lifetime risk. Reclassifications to high lifetime are higher from intermediate 10-year risk category. The Hosmer-Lemeshow goodness-of-fit statistics indicates a good model fit. Conclusion: The risk prediction and timely intervention with appropriate therapeutic and lifestyle modification is useful in primary prevention. Avoiding short-term incidences and reclassifications to high lifetime can reduce the CVD mortality rates.

scholarly journals POS-296 CARDIOVASCULAR RISK PREDICTION WITH AORTIC PULSE WAVE VELOCITY: A CARTAGENE STUDY

2021 ◽  
Vol 6 (4) ◽  
pp. S127
Author(s):  
S. Veillette ◽  
F. Lamarche ◽  
M. Agharazii ◽  
S. Wassertheurer ◽  
B. Hametner ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Pulse Wave Velocity ◽  
Risk Prediction ◽  
Wave Velocity ◽  
Pulse Wave ◽  
Aortic Pulse Wave Velocity ◽  
Cardiovascular Risk Prediction
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