Eva Hagberg, Elias Björnson, Martin Adiels, Bledar Daka, Louise H Fornander, Josefin Kjelldahl, David Molnar, Carlo Pirazzi, Ulf Strömberg, Gustav Kjellsson, Carl Bonander, Mikael Svensson, Anders Gummessson, Göran Bergström
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引用次数: 0
Abstract
Background: Coronary artery calcium (CAC) imaging directly assesses subclinical calcified coronary atherosclerosis but population-wide imaging is not recommended. Simple prescreening may help identify individuals most likely to benefit from CAC imaging. We previously developed a self-report-based model to estimate the probability of CAC ≥100. This study prospectively evaluated a strategy based on this model to select individuals for CAC imaging. We assessed agreement between model-predicted probability and observed prevalence of CAC ≥100 among participants undergoing CT imaging and examined patterns of preventive lipid-lowering therapy.
Methods: The PRedict and Identify cOronary atherosclerosis-Now (PRIO-Now) study applied a prospective, two-step, population-based screening approach. Individuals aged 59-60 years were invited to complete a self-report questionnaire. Eligible respondents without previous ischaemic heart disease whose model-predicted probability of CAC ≥100 exceeded the predefined threshold were invited to clinical assessment and non-contrast coronary CT imaging. The primary analysis assessed agreement between model-predicted probabilities and the observed prevalence of CAC ≥100 among CT completers.
Results: Of 8000 invited individuals, 2588 (32%) completed the questionnaire. Of 2375 eligible respondents, 814 were classified as high risk and 563 underwent CT imaging. Among CT completers, the mean predicted probability of CAC ≥100 was 28.3% (95% CI 27.2 to 29.3), compared with an observed prevalence of 28.4% (95% CI 24.8 to 32.4), corresponding to an expected/observed ratio of 0.99 and a Brier score of 0.19. Among participants with CAC ≥100, 64% were not receiving lipid-lowering therapy and 11% had low-density lipoprotein cholesterol ≤1.8 mmol/L.
Conclusions: A self-report-guided strategy enabled targeted CAC imaging in a model-selected cohort. Among participants completing CT imaging, the observed prevalence of CAC ≥100 was comparable with the mean model-predicted probability. These findings suggest that self-report data may support preselection for CAC imaging and help identify opportunities for preventive treatment among individuals with elevated CAC.
背景：冠状动脉钙化（CAC）成像直接评估亚临床钙化冠状动脉粥样硬化，但不推荐全民成像。简单的预筛可能有助于识别最有可能从CAC成像中受益的个体。我们之前开发了一个基于自我报告的模型来估计CAC≥100的概率。本研究前瞻性地评估了基于该模型选择CAC成像个体的策略。在接受CT成像的参与者中，我们评估了模型预测的概率和观察到的CAC≥100的患病率之间的一致性，并检查了预防性降脂治疗的模式。方法：预测和识别冠状动脉粥样硬化- now （PRIO-Now）研究采用前瞻性、两步、基于人群的筛查方法。年龄在59-60岁之间的个体被邀请完成一份自我报告问卷。模型预测的CAC≥100的概率超过预定阈值的无缺血性心脏病的合格受试者被邀请进行临床评估和非对比冠状动脉CT成像。初步分析评估了模型预测概率与观察到的CT完井患者CAC≥100的患病率之间的一致性。结果：在被邀请的8000人中，2588人（32%）完成了问卷调查。在2375名符合条件的受访者中，814人被列为高危人群，563人接受了CT成像。在CT完成者中，CAC≥100的平均预测概率为28.3% (95% CI 27.2至29.3)，而观察到的患病率为28.4% (95% CI 24.8至32.4)，对应于预期/观察比为0.99，Brier评分为0.19。在CAC≥100的参与者中，64%未接受降脂治疗，11%的低密度脂蛋白胆固醇≤1.8 mmol/L。结论：自我报告引导策略在模型选择的队列中实现了靶向CAC成像。在完成CT成像的参与者中，观察到的CAC≥100的患病率与平均模型预测概率相当。这些发现表明，自我报告数据可能支持CAC成像的预选，并有助于确定CAC升高个体的预防性治疗机会。
期刊介绍：
Heart is an international peer reviewed journal that keeps cardiologists up to date with important research advances in cardiovascular disease. New scientific developments are highlighted in editorials and put in context with concise review articles. There is one free Editor’s Choice article in each issue, with open access options available to authors for all articles. Education in Heart articles provide a comprehensive, continuously updated, cardiology curriculum.
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