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开发用于慢性肾脏病的风险预测评分和方程:一项回顾性队列研究。

Development of a risk prediction score and equation for chronic kidney disease: a retrospective cohort study.

机构信息

Department of Cardiovascular Medicine and Hypertension, Graduate School of Medical and Dental Sciences, Kagoshima University, 8-35-1 Sakuragaoka, Kagoshima, 890-0075, Japan.

Digestive and Lifestyle Diseases, Department of Human and Environmental Sciences, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan.

出版信息

Sci Rep. 2023 Mar 27;13(1):5001. doi: 10.1038/s41598-023-32279-z.

Abstract

Chronic kidney disease (CKD) is a risk factor for end-stage renal disease and contributes to increased risk of cardiovascular disease morbidity and mortality. We aimed to develop a risk prediction score and equation for future CKD using health checkup data. This study included 58,423 Japanese participants aged 30-69 years, who were randomly assigned to derivation and validation cohorts at a ratio of 2:1. The predictors were anthropometric indices, life style, and blood sampling data. In derivation cohort, we performed multivariable logistic regression analysis and obtained the standardized beta coefficient of each factor that was significantly associated with new-onset CKD and assigned scores to each factor. We created a score and an equation to predict CKD after 5 years and applied them to validation cohort to assess their reproducibility. The risk score ranged 0-16, consisting of age, sex, hypertension, dyslipidemia, diabetes, hyperuricemia, and estimated glomerular filtration rate (eGFR), with area under the curve (AUC) of 0.78 for the derivation cohort and 0.79 for the validation cohort. The CKD incidence gradually and constantly increased as the score increased from ≤ 6 to ≥ 14. The equation consisted of the seven indices described above, with AUC of 0.88 for the derivation cohort and 0.89 for the validation cohort. We developed a risk score and equation to predict CKD incidence after 5 years in Japanese population under 70 years of age. These models had reasonably high predictivity, and their reproducibility was confirmed through internal validation.

摘要

慢性肾脏病(CKD)是终末期肾脏疾病的危险因素,并增加了心血管疾病发病率和死亡率的风险。我们旨在使用健康检查数据开发一种用于未来 CKD 的风险预测评分和方程。本研究包括 58423 名年龄在 30-69 岁的日本参与者,他们被随机分配到推导和验证队列,比例为 2:1。预测因子是人体测量指数、生活方式和血液采样数据。在推导队列中,我们进行了多变量逻辑回归分析,并获得了与新发 CKD 显著相关的每个因素的标准化β系数,并为每个因素分配了分数。我们创建了一个评分和方程来预测 5 年后的 CKD,并将其应用于验证队列以评估其可重复性。风险评分范围为 0-16,由年龄、性别、高血压、血脂异常、糖尿病、高尿酸血症和估计肾小球滤过率(eGFR)组成,推导队列的曲线下面积(AUC)为 0.78,验证队列为 0.79。随着评分从≤6 增加到≥14,CKD 的发病率逐渐持续增加。该方程由上述七个指数组成,推导队列的 AUC 为 0.88,验证队列为 0.89。我们在 70 岁以下的日本人群中开发了一种预测 5 年后 CKD 发生率的风险评分和方程。这些模型具有相当高的预测能力,并通过内部验证确认了其可重复性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be25/10042816/f8d9bf931706/41598_2023_32279_Fig1_HTML.jpg

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