Yu Shasha, Yang Hongmei, Wang Bo, Guo Xiaofan, Li Guangxiao, Sun Yingxian
Department of Cardiology, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
Department of Clinical Epidemiology, Institute of Cardiovascular Diseases, First Hospital of China Medical University, Shenyang 110001, Liaoning Province, China.
J Transl Int Med. 2024 Jul 27;12(3):244-252. doi: 10.2478/jtim-2023-0003. eCollection 2024 Jun.
Cumulative evidence confirms that mild renal dysfunction (MRD) is correlated with many cardiovascular risk factors and increases cardiovascular morbidity and mortality. The purpose of this study was to establish an effective nomogram for predicting the risk of MRD in the rural population of Northeast China.
We analyzed the reports of 4944 subjects from the Northeast China Rural Cardiovascular Health Study (NCRCHS). All the participants completed the questionnaires, anthropometric measurements, and blood tests during the baseline study (2012-2013) and the follow-up study during 2015-2017 (an average of 4.6 years). The Chronic Kidney Disease Epidemiology (CKD-EPI) equation was used to calculate the estimated glomerular filtration rate (eGFR), and eGFR in the range of 60-90 mL/min/1.73m2 was defined as MRD.
The study revealed that a total of 889 subjects (18.0%) had MRD. Multivariate logistic analysis showed that annual income, abdominal obesity, hypertension, hyperglycemia, and frequent tea consumption were the independent risk factors ( < 0.05) for MRD. Thereafter, a nomogram with an area under the receiver operating characteristic curve (AUC) of 0.705 was constructed to accurately predict MRD. The calibration plot also showed an excellent consistency between the probability of prediction and observation.
We constructed a nomogram based on epidemiological data, which could provide an individual prediction of MRD with good accuracy.
累积证据证实,轻度肾功能不全(MRD)与多种心血管危险因素相关,并增加心血管疾病的发病率和死亡率。本研究的目的是建立一种有效的列线图,用于预测中国东北地区农村人口发生MRD的风险。
我们分析了来自中国东北地区农村心血管健康研究(NCRCHS)的4944名受试者的报告。所有参与者在基线研究(2012 - 2013年)和2015 - 2017年的随访研究(平均4.6年)期间完成了问卷调查、人体测量和血液检测。采用慢性肾脏病流行病学协作组(CKD - EPI)方程计算估算肾小球滤过率(eGFR),eGFR在60 - 90 mL/min/1.73m²范围内被定义为MRD。
研究显示,共有889名受试者(18.0%)患有MRD。多因素逻辑回归分析表明,年收入、腹型肥胖、高血压、高血糖和频繁饮茶是MRD的独立危险因素(<0.05)。此后,构建了一个受试者工作特征曲线下面积(AUC)为0.705的列线图,以准确预测MRD。校准图也显示预测概率与观察值之间具有良好的一致性。
我们基于流行病学数据构建了一个列线图,它可以对MRD进行个体预测,且准确性良好。