Rheumatology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Italy.
Clin Exp Rheumatol. 2020 Jul-Aug;38(4):602-608. Epub 2019 Oct 28.
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).
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.
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.
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.
我们旨在比较三种心血管（CV）风险评估算法，即 Framingham、ACC/AHA 和 QRISK3，在系统性红斑狼疮（SLE）患者队列中的应用。
纳入符合 ACR 标准的连续 SLE 患者。评估传统危险因素、正在进行的治疗、合并症和 SLE 特异性评估。在那些没有既往心肌梗死或中风的患者中，随后使用 Framingham、ACC/AHA 和 QRISK3 算法来估计未来 10 年内发生 CV 疾病的个体风险。
在纳入的 135 名患者中，有 123 名患者符合 CV 风险评估条件。Framingham 指数报告的中位数风险评分为 4.7%（IQR 9.5-2.2），考虑到 29 名患者（23.6%）存在高 CV 风险。ACC/AHA 指数显示中位数风险评分为 1.4%（IQR 4.5-0.7），17 名患者（13.8%）存在高风险。QRISK3 显示中位数风险评分为 6.2%（IQR 12.5-2.8），可能将 44 名患者（35.8%）归类为高 CV 风险。对于年龄大于 40 岁的患者的亚组分析，Framingham 和 ACC/AHA 两种算法均确认了相同数量的高危患者，而 QRISK3 将 38 名患者归类为高 CV 风险。
与 Framingham 和 ACC/AHA 等经典算法相比，QRISK3 可以将更多的 SLE 患者归类为未来 10 年内发生 CV 疾病的高风险患者。如果其预测准确性能被纵向数据证实，QRISK3 将成为早期发现相当一部分 CV 高危 SLE 患者的重要工具，而这些患者在应用经典算法时可能被低估。
