Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; Department of Vascular Surgery, University Medical Centre Utrecht, Utrecht, The Netherlands.
Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Eur J Vasc Endovasc Surg. 2021 Mar;61(3):365-373. doi: 10.1016/j.ejvs.2020.11.029. Epub 2021 Jan 7.
Asymptomatic carotid stenosis (ACS) is associated with an increased risk of ischaemic stroke and myocardial infarction. Risk scores have been developed to detect individuals at high risk of ACS, thereby enabling targeted screening, but previous external validation showed scope for refinement of prediction by adding additional predictors. The aim of this study was to develop a novel risk score in a large contemporary screened population.
A prediction model was developed for moderate (≥50%) and severe (≥70%) ACS using data from 596 469 individuals who attended screening clinics. Variables that predicted the presence of ≥50% and ≥70% ACS independently were determined using multivariable logistic regression. Internal validation was performed using bootstrapping techniques. Discrimination was assessed using area under the receiver operating characteristic curves (AUROCs) and agreement between predicted and observed cases using calibration plots.
Predictors of ≥50% and ≥70% ACS were age, sex, current smoking, diabetes mellitus, prior stroke/transient ischaemic attack, coronary artery disease, peripheral arterial disease, blood pressure, and blood lipids. Models discriminated between participants with and without ACS reliably, with an AUROC of 0.78 (95% confidence interval [CI] 0.77-0.78) for ≥ 50% ACS and 0.82 (95% CI 0.81-0.82) for ≥ 70% ACS. The number needed to screen in the highest decile of predicted risk to detect one case with ≥50% ACS was 13 and that of ≥70% ACS was 58. Targeted screening of the highest decile identified 41% of cases with ≥50% ACS and 51% with ≥70% ACS.
The novel risk model predicted the prevalence of ACS reliably and performed better than previous models. Targeted screening among the highest decile of predicted risk identified around 40% of all cases with ≥50% ACS. Initiation or intensification of cardiovascular risk management in detected cases might help to reduce both carotid related ischaemic strokes and myocardial infarctions.
无症状颈动脉狭窄(ACS)与缺血性卒中和心肌梗死的风险增加相关。已经开发了风险评分来检测 ACS 风险较高的个体,从而能够进行有针对性的筛查,但以前的外部验证表明,通过添加其他预测因子,可以进一步完善预测。本研究旨在为大型当代筛查人群开发一种新的风险评分。
使用参加筛查诊所的 596469 名个体的数据,为中度(≥50%)和重度(≥70%)ACS 开发预测模型。使用多变量逻辑回归确定独立预测≥50%和≥70%ACS 存在的变量。使用自举技术进行内部验证。使用接受者操作特征曲线下面积(AUROCs)评估区分度,并使用校准图评估预测病例与观察病例之间的一致性。
≥50%和≥70%ACS 的预测因素为年龄、性别、当前吸烟、糖尿病、既往卒中和短暂性脑缺血发作、冠心病、外周动脉疾病、血压和血脂。模型可靠地区分了有和无 ACS 的参与者,对于≥50% ACS 的 AUROC 为 0.78(95%置信区间 [CI] 0.77-0.78),对于≥70% ACS 的 AUROC 为 0.82(95% CI 0.81-0.82)。在预测风险最高的十分位数中,筛查发现≥50%ACS 病例的数量为 13,筛查发现≥70%ACS 病例的数量为 58。针对最高十分位数的靶向筛查确定了 41%的≥50%ACS 病例和 51%的≥70%ACS 病例。
新的风险模型可靠地预测 ACS 的患病率,并且表现优于以前的模型。在预测风险最高的十分位数中进行靶向筛查可以发现大约 40%的所有≥50%ACS 病例。在发现的病例中启动或强化心血管风险管理可能有助于减少颈动脉相关缺血性卒中和心肌梗死。