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最优风险计算器设计的中风和心血管风险因素的排名:逻辑回归方法。

Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach.

机构信息

Department of Neurology, IMIM - Hospital Del Mar, Barcelona, Spain.

Department of ECE, VNIT, Nagpur, Maharashtra, India.

出版信息

Comput Biol Med. 2019 May;108:182-195. doi: 10.1016/j.compbiomed.2019.03.020. Epub 2019 Mar 25.

Abstract

PURPOSE

Conventional cardiovascular risk factors (CCVRFs) and carotid ultrasound image-based phenotypes (CUSIP) are independently associated with long-term risk of cardiovascular (CV) disease. In this study, 26 cardiovascular risk (CVR) factors which consisted of a combination of CCVRFs and CUSIP together were ranked. Further, an optimal risk calculator using AtheroEdge composite risk score (AECRS1.0) was designed and benchmarked against seven conventional CV risk (CVR) calculators.

METHODS

Two types of ranking were performed: (i) ranking of 26 CVR factors and (ii) ranking of eight types of 10-year risk calculators. In the first case, multivariate logistic regression was used to compute the odds ratio (OR) and in the second, receiver operating characteristic curves were used to evaluate the performance of eight types of CVR calculators using SPSS23.0 and MEDCALC12.0 with validation against STATA15.0.

RESULTS

The left and right common carotid arteries (CCA) of 202 Japanese patients were examined to obtain 404 ultrasound scans. CUSIP ranked in the top 50% of the 26 covariates. Intima-media thickness variability (IMTV) and IMTV were the most influential carotid phenotypes for left CCA (OR = 250, P < 0.0001 and OR = 207, P < 0.0001 respectively) and right CCA (OR = 1614, P < 0.0001 and OR = 626, P < 0.0001 respectively). However, for the mean CCA, AECRS1.0 and AECRS1.0 reported the most highly significant OR among all the CVR factors (OR = 1.073, P < 0.0001 and OR = 1.104, P < 0.0001). AECRS1.0 also reported highest area-under-the-curve (AUC = 0.904, P < 0.0001) compared to seven types of conventional calculators. Age and glycated haemoglobin reported highest OR (1.96, P < 0.0001 and 1.05, P = 0.012) among all other CCVRFs.

CONCLUSION

AECRS1.0 demonstrated the best performance due to presence of CUSIP and ranked at the first place with highest AUC.

摘要

目的

传统心血管危险因素(CCVRF)和颈动脉超声图像表型(CUSIP)与心血管疾病(CV)的长期风险独立相关。在这项研究中,对由 CCVRF 和 CUSIP 组合而成的 26 个心血管风险(CVR)因素进行了排名。此外,还设计了一种基于 AtheroEdge 综合风险评分(AECRS1.0)的最优风险计算器,并与七种传统 CV 风险(CVR)计算器进行了基准比较。

方法

进行了两种类型的排名:(i)26 个 CVR 因素的排名和(ii)十种 10 年风险计算器的排名。在第一种情况下,使用多元逻辑回归计算比值比(OR),在第二种情况下,使用 SPSS23.0 和 MEDCALC12.0 中的接收器工作特征曲线评估八种类型的 CVR 计算器的性能,并与 STATA15.0 进行验证。

结果

对 202 名日本患者的左右颈总动脉(CCA)进行了检查,共获得 404 个超声扫描。CUSIP 在 26 个协变量的前 50%中排名。内中膜厚度变异性(IMTV)和 IMTV 是左 CCA(OR=250,P<0.0001 和 OR=207,P<0.0001)和右 CCA(OR=1614,P<0.0001 和 OR=626,P<0.0001)最具影响力的颈动脉表型。然而,对于平均 CCA,AECRS1.0 和 AECRS1.0 在所有 CVR 因素中报告的 OR 最为显著(OR=1.073,P<0.0001 和 OR=1.104,P<0.0001)。与七种传统计算器相比,AECRS1.0 还报告了最高的曲线下面积(AUC=0.904,P<0.0001)。年龄和糖化血红蛋白在所有其他 CCVRF 中报告的 OR 最高(1.96,P<0.0001 和 1.05,P=0.012)。

结论

AECRS1.0 由于存在 CUSIP,表现出最佳性能,排名第一,AUC 最高。

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