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Framingham, ACC/AHA or QRISK3: which is the best in systemic lupus erythematosus cardiovascular risk estimation?
Marco Di Battista1, Chiara Tani1, Elena Elefante1
1Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
Insights
The QRISK3 algorithm identifies more patients with systemic lupus erythematosus (SLE) at high cardiovascular (CV) risk than Framingham or ACC/AHA. This improved identification may aid early intervention for CV disease in SLE patients.
Area of Science:
- Cardiovascular Medicine
- Rheumatology
- Epidemiology
Background:
- Systemic lupus erythematosus (SLE) is associated with an increased risk of cardiovascular (CV) disease.
- Accurate CV risk stratification is crucial for timely intervention in SLE patients.
- Existing CV risk algorithms may underestimate risk in this population.
Purpose of the Study:
- To compare the performance of three CV risk estimation algorithms: Framingham, ACC/AHA, and QRISK3.
- To evaluate their effectiveness in identifying high-risk individuals within a cohort of SLE patients.
Main Methods:
- 123 SLE patients meeting ACR criteria were assessed for traditional CV risk factors, therapies, and comorbidities.
- Framingham, ACC/AHA, and QRISK3 algorithms were applied to estimate 10-year CV disease risk.
- Patients with prior myocardial infarction or stroke were excluded from risk calculation.
Main Results:
- QRISK3 identified 35.8% of patients as high CV risk, compared to 23.6% for Framingham and 13.8% for ACC/AHA.
- Median risk scores were 6.2% (QRISK3), 4.7% (Framingham), and 1.4% (ACC/AHA).
- In patients over 40, QRISK3 also identified more high-risk individuals than the other two algorithms.
Conclusions:
- QRISK3 classifies a significantly higher proportion of SLE patients at high CV risk compared to Framingham and ACC/AHA.
- QRISK3 may be a more sensitive tool for detecting CV risk in SLE patients.
- Further validation with longitudinal data is needed to confirm QRISK3's predictive accuracy and clinical utility in SLE.
Objectives:
Our objective was to compare three algorithms for cardiovascular (CV) risk estimation, namely Framingham, ACC/AHA and QRISK3, in a cohort of patients with systemic lupus erythematosus (SLE).
Methods:
Consecutive patients with SLE according to the ACR criteria were enrolled. Traditional risk factors, ongoing therapies, comorbidities and SLE-specific evaluations were assessed. In those without previous myocardial infarction or stroke, Framingham, ACC/AHA and QRISK3 algorithms were then used to estimate the individual risk of developing a CV disease over the next 10 years.
Results:
Patients eligible for CV risk estimation were 123 out of 135 enrolled. Framingham index reported a median risk score of 4.7% (IQR 9.5-2.2), considering 29 patients (23.6%) at high CV risk. ACC/AHA index showed a median risk score of 1.4% (IQR 4.5-0.7), with 17 patients (13.8%) at high-risk. QRISK3 revealed a median risk score of 6.2% (IQR 12.5-2.8), making it possible to classify 44 patients (35.8%) at high CV risk. The subgroup analysis of subjects older than 40 years confirmed the same number of high-risk patients for both Framingham and ACC/AHA, whereas QRISK3 classified 38 subjects at high CV risk.
Conclusions:
QRISK3 classifies a greater number of SLE patients at high-risk of developing CV diseases over the next 10 years in comparison with classic algorithms as Framingham and ACC/AHA. If its predictive accuracy were confirmed by longitudinal data, QRISK3 could become an important tool in the early detection of a considerable part of CV high-risk SLE patients that would be underestimated when applying classic algorithms.
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