动脉粥样硬化性心血管疾病的风险预测模型:一项特别针对卡塔尔的系统评估
Risk prediction models for atherosclerotic cardiovascular disease: A systematic assessment with particular reference to Qatar.
作者信息
Sheikh Aziz, Nurmatov Ulugbek, Al-Katheeri Huda Amer, Ali Al Huneiti Rasmeh
机构信息
Usher Institute, University of Edinburgh, Edinburgh, UK E-mail:
School of Medicine, Cardiff University, Cardiff, UK.
出版信息
Qatar Med J. 2021 Sep 26;2021(2):42. doi: 10.5339/qmj.2021.42. eCollection 2021.
BACKGROUND
Atherosclerotic cardiovascular disease (ASCVD) is a common disease in the State of Qatar and results in considerable morbidity, impairment of quality of life and mortality. The American College of Cardiology/American Heart Association Pooled Cohort Equations (PCE) is currently used in Qatar to identify those at high risk of ASCVD. However, it is unclear if this is the optimal ASCVD risk prediction model for use in Qatar's ethnically diverse population.
AIMS
This systematic review aimed to identify, assess the methodological quality of and compare the properties of established ASCVD risk prediction models for the Qatari population.
METHODS
Two reviewers performed head-to-head comparisons of established ASCVD risk calculators systematically. Studies were independently screened according to predefined eligibility criteria and critically appraised using Prediction Model Risk Of Bias Assessment Tool. Data were descriptively summarized and narratively synthesized with reporting of key statistical properties of the models.
RESULTS
We identified 20,487 studies, of which 41 studies met our eligibility criteria. We identified 16 unique risk prediction models. Overall, 50% (n = 8) of the risk prediction models were judged to be at low risk of bias. Only 13% of the studies (n = 2) were judged at low risk of bias for applicability, namely, PREDICT and QRISK3.Only the PREDICT risk calculator scored low risk in both domains.
CONCLUSIONS
There is no existing ASCVD risk calculator particularly well suited for use in Qatar's ethnically diverse population. Of the available models, PREDICT and QRISK3 appear most appropriate because of their inclusion of ethnicity. In the absence of a locally derived ASCVD for Qatar, there is merit in a formal head-to-head comparison between PCE, which is currently in use, and PREDICT and QRISK3.
背景
动脉粥样硬化性心血管疾病(ASCVD)在卡塔尔国是一种常见疾病,会导致相当高的发病率、生活质量受损及死亡率。美国心脏病学会/美国心脏协会合并队列方程(PCE)目前在卡塔尔用于识别ASCVD高风险人群。然而,尚不清楚这是否是适用于卡塔尔种族多样化人群的最佳ASCVD风险预测模型。
目的
本系统评价旨在识别、评估已建立的针对卡塔尔人群的ASCVD风险预测模型的方法学质量并比较其特性。
方法
两名评价者对已建立的ASCVD风险计算器进行了系统的直接比较。根据预先定义的纳入标准独立筛选研究,并使用预测模型偏倚风险评估工具进行严格评价。对数据进行描述性总结,并对模型的关键统计特性进行叙述性综合。
结果
我们识别出20487项研究,其中41项研究符合我们的纳入标准。我们识别出16种独特的风险预测模型。总体而言,50%(n = 8)的风险预测模型被判定为低偏倚风险。只有13%的研究(n = 2)在适用性方面被判定为低偏倚风险研究,即PREDICT和QRISK3。只有PREDICT风险计算器在两个领域均得分低风险。
结论
目前没有特别适合在卡塔尔种族多样化人群中使用的ASCVD风险计算器。在现有模型中,PREDICT和QRISK3似乎最合适,因为它们纳入了种族因素。在没有针对卡塔尔的本地推导的ASCVD模型的情况下,对目前正在使用的PCE与PREDICT和QRISK3进行正式的直接比较是有价值的。
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