Gao Xueyan, Wang Jing, Huang Hui, Ye Xiaoxue, Cui Ying, Ren Wenkai, Xu Fangyan, Qian Hanyang, Gao Zhanhui, Zeng Ming, Yang Guang, Huang Yaoyu, Tang Shaowen, Xing Changying, Wan Huiting, Zhang Lina, Chen Huimin, Jiang Yao, Zhang Jing, Xiao Yujie, Bian Anning, Li Fan, Wei Yongyue, Wang Ningning
Department of Nephrology, The First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, China.
Department of General Medicine, Geriatric Hospital of Nanjing Medical University, Nanjing, China.
Front Genet. 2022 May 16;13:872920. doi: 10.3389/fgene.2022.872920. eCollection 2022.
Heart rate variability (HRV), reflecting circadian rhythm of heart rate, is reported to be associated with clinical outcomes in stage 5 chronic kidney disease (CKD5) patients. Whether CKD related factors combined with HRV can improve the predictive ability for their death remains uncertain. Here we evaluated the prognosis value of nomogram model based on HRV and clinical risk factors for all-cause mortality in CKD5 patients. CKD5 patients were enrolled from multicenter between 2011 and 2019 in China. HRV parameters based on 24-h Holter and clinical risk factors associated with all-cause mortality were analyzed by multivariate Cox regression. The relationships between HRV and all-cause mortality were displayed by restricted cubic spline graphs. The predictive ability of nomogram model based on clinical risk factors and HRV were evaluated for survival rate. CKD5 patients included survival subgroup (n = 155) and all-cause mortality subgroup (n = 45), with the median follow-up time of 48 months. Logarithm of standard deviation of all sinus R-R intervals (lnSDNN) (4.40 ± 0.39 . 4.32 ± 0.42; = 0.007) and logarithm of standard deviation of average NN intervals for each 5 min (lnSDANN) (4.27 ± 0.41 . 4.17 ± 0.41; = 0.008) were significantly higher in survival subgroup than all-cause mortality subgroup. On the basis of multivariate Cox regression analysis, the lnSDNN (HR = 0.35, 95%CI: 0.17-0.73, = 0.01) and lnSDANN (HR = 0.36, 95% CI: 0.17-0.77, = 0.01) were associated with all-cause mortality, their relationships were negative linear. Spearman's correlation analysis showed that lnSDNN and lnSDANN were highly correlated, so we chose lnSDNN, sex, age, BMI, diabetic mellitus (DM), β-receptor blocker, blood glucose, phosphorus and ln intact parathyroid hormone (iPTH) levels to build the nomogram model. The area under the curve (AUC) values based on lnSDNN nomogram model for predicting 3-year and 5-year survival rates were 79.44% and 81.27%, respectively. In CKD5 patients decreased SDNN and SDANN measured by HRV were related with their all-cause mortality, meanwhile, SDNN and SDANN were highly correlated. Nomogram model integrated SDNN and clinical risk factors are promising for evaluating their prognosis.
心率变异性（HRV）反映心率的昼夜节律，据报道与5期慢性肾脏病（CKD5）患者的临床结局相关。CKD相关因素与HRV相结合是否能提高对其死亡的预测能力仍不确定。在此，我们评估了基于HRV和临床危险因素的列线图模型对CKD5患者全因死亡率的预后价值。2011年至2019年期间，在中国多中心招募了CKD5患者。通过多因素Cox回归分析基于24小时动态心电图的HRV参数和与全因死亡率相关的临床危险因素。通过限制性立方样条图展示HRV与全因死亡率之间的关系。评估基于临床危险因素和HRV的列线图模型对生存率的预测能力。CKD5患者包括生存亚组（n = 155）和全因死亡亚组（n = 45），中位随访时间为48个月。生存亚组的所有窦性R-R间期标准差的对数（lnSDNN）（4.40±0.39. 4.32±0.42；P = 0.007）和每5分钟平均NN间期标准差的对数（lnSDANN）（4.27±0.41. 4.17±0.41；P = 0.008）显著高于全因死亡亚组。基于多因素Cox回归分析，lnSDNN（HR = 0.35，95%CI：0.17 - 0.73，P = 0.01）和lnSDANN（HR = 0.36，95%CI：0.17 - 0.77，P = 0.01）与全因死亡率相关，它们的关系呈负线性。Spearman相关性分析显示lnSDNN和lnSDANN高度相关，因此我们选择lnSDNN、性别、年龄、体重指数、糖尿病（DM）、β受体阻滞剂、血糖、磷和完整甲状旁腺激素（iPTH）水平来构建列线图模型。基于lnSDNN列线图模型预测3年和5年生存率的曲线下面积（AUC）值分别为79.44%和81.27%。在CKD5患者中，通过HRV测量的SDNN和SDANN降低与他们的全因死亡率相关，同时SDNN和SDANN高度相关。整合SDNN和临床危险因素的列线图模型在评估他们的预后方面很有前景。
