Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Intensive Care Unit Department, No. 23, Mei Shu Guan Hou Jie, Beijing, 100010, Dongcheng, China.
Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221004, Jiangsu, China.
Int Urol Nephrol. 2023 May;55(5):1353-1363. doi: 10.1007/s11255-022-03431-x. Epub 2022 Dec 23.
The occurrence of pulmonary arterial hypertension (PAH) can greatly affect the prognosis of patients with chronic kidney disease (CKD). We aimed to construct a nomogram to predict the probability of PAH development in patients with stage 3-5 CKD to guide early intervention and to improve prognosis.
From August 2018 to December 2021, we collected the data of 1258 patients with stage 3-5 CKD hospitalized at the Affiliated Hospital of Xuzhou Medical University as a training set and 389 patients hospitalized at Zhongda Hospital as a validation set. These patients were divided into PAH and N-PAH groups with pulmonary arterial systolic pressure ≥ 35 mmHg as the cutoff. The results of univariate and multivariate logistic regression analyses were used to establish the nomogram. Then, areas under the receiver operating characteristic curve (AUC-ROCs), a calibration plot, and decision curve analysis (DCA) were used to validate the nomogram.
The nomogram included nine variables: age, diabetes mellitus, hemoglobin, platelet count, serum creatinine, left ventricular end-diastolic diameter, left atrial diameter, main pulmonary artery diameter and left ventricular ejection fraction. The AUC-ROCs of the training set and validation set were 0.801 (95% confidence interval (CI) 0.771-0.830) and 0.760 (95% CI 0.699-0.818), respectively, which showed good discriminative ability of the nomogram. The calibration diagram showed good agreement between the predicted and observed results. DCA also demonstrated that the nomogram could be clinically useful.
The evaluation of the nomogram model for predicting PAH in patients with CKD based on risk factors showed its ideal efficacy. Thus, the nomogram can be used to screen for patients at high risk for PAH and has guiding value for the subsequent formulation of prevention strategies and clinical treatment.
肺动脉高压（PAH）的发生会极大地影响慢性肾脏病（CKD）患者的预后。本研究旨在构建一个预测模型，以预测 3-5 期 CKD 患者发生 PAH 的概率，指导早期干预，改善预后。
本研究纳入了 2018 年 8 月至 2021 年 12 月在徐州医科大学附属医院住院的 1258 例 3-5 期 CKD 患者作为训练集和 389 例在南京鼓楼医院住院的患者作为验证集。根据肺动脉收缩压≥35mmHg 作为截断值，将患者分为 PAH 组和 N-PAH 组。采用单因素和多因素逻辑回归分析结果建立预测模型，然后采用受试者工作特征曲线（ROC）下面积（AUC-ROC）、校准曲线和决策曲线分析（DCA）对预测模型进行验证。
该预测模型包含 9 个变量：年龄、糖尿病、血红蛋白、血小板计数、血清肌酐、左心室舒张末期直径、左心房直径、主肺动脉直径和左心室射血分数。训练集和验证集的 AUC-ROC 分别为 0.801（95%置信区间（CI）：0.771-0.830）和 0.760（95%CI：0.699-0.818），具有良好的判别能力。校准图显示预测结果与实际结果具有良好的一致性。DCA 也表明该预测模型具有临床应用价值。
基于危险因素构建的 CKD 患者 PAH 预测模型评估显示其具有理想的疗效。因此，该预测模型可用于筛选 PAH 高危患者，对后续制定预防策略和临床治疗具有指导意义。
