中国血液净化

中国血液净化 ›› 2023, Vol. 22 ›› Issue (12): 909-915.doi: 10.3969/j.issn.1671-4091.2023.12.006

• 临床研究 • 上一篇    下一篇

维持性血液透析患者心力衰竭住院预测模型的开发和外部验证

唐文武   袁心柱   杨小华    陈晓霞    王只欣    张 英    谢席胜   

  1. 637001 南充，1川北医学院附属南充市中心医院肾内科
    628000 广元，2广元市中心医院肾内科
    629000 遂宁，3遂宁市中心医院肾内科
  • 收稿日期:2023-08-22 修回日期:2023-10-11 出版日期:2023-12-12 发布日期:2023-11-30
  • 通讯作者: 谢席胜 E-mail:xishengx@163.com
  • 基金资助:
    四川省科技厅科研专项基金(2021YFS0259)；南充市科技局科研专项基金(22JCYJPT0005)

Construction and external validation of a risk prediction model for hospitalization and mortality in hemodialysis patients with heart failure

TANG Wen-wu, YUAN Xin-zhu, YANG Xiao-hua, CHEN Xiao-xia, WANG Zhi-xin, ZHANG Ying, XIE Xi-sheng   

  1. Department of Nephrology, Nanchong Central Hospital Affiliated to North Sichuan Medical College, Nanchong 637001, China; 2Department of Nephrology, Guangyuan Central Hospital, Guangyuan 628000, China; 3Department of Nephrology, Suining Central Hospital, Suining 629000, China
  • Received:2023-08-22 Revised:2023-10-11 Online:2023-12-12 Published:2023-11-30
  • Contact: 637001 南充，1川北医学院附属南充市中心医院肾内科 E-mail:xishengx@163.com

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摘要： 目的　构建列线图预测维持性血液透析(maintenance hemodialysis，MHD)患者心力衰竭(heart failure，HF)住院的发生风险。 方法　纳入2017—2023年南充市中心医院、遂宁市中心医院、广元市中心医院、蓬安县人民医院4个中心的MHD患者，收集基础信息、病例资料、实验室及影像学资料。以2个中心为训练集(n=386)，另外2个中心为外部验证集(n=116)；利用最小绝对收缩和选择算子(least absolute shrinkageand selection operator，LASSO)回归与COX回归分析相关危险因素，建立HF住院风险的列线图模型。以受试者工作特征曲线下面积评估模型预测效能，运用校准曲线、决策曲线分析评估模型的准确度及实用性。 结果　训练集与外部验证集的中位随访时间分别为15(9，24)个月和14(10，21)个月，分别有140例(36.27%)和28例(24.14%)患者发生HF住院。COX回归分析结果显示N末端B型利钠肽前体(HR=1.532，95% CI：1.244～1.886,P＜0.001)、淋巴细胞百分比(HR=0.975，95% CI：0.952～0.999,P=0.038)、右心房直径(HR=1.060,95% CI：1.017～1.105,P=0.005)/心室直径(HR=1.033,95% CI：0.998～1.062,P=0.064)、每周透析时长(HR=0.667,95% CI：0.459～0.968,P=0.033)、HF评分(HR=1.778, 95% CI：1.130～2.798,P=0.013)、“血管紧张素转换酶抑制剂/血管紧张素Ⅱ受体拮抗剂”类药物使用(HR=0.569,95% CI：0.353～0.917,P=0.020)、冠心病/糖尿病病史(HR=1.582,95% CI：1.002～2.500,P=0.049)与HF住院独立相关。内外部验证的C指数分别为0.836(95% CI：0.802～0.870)和 0.819(95% CI：0.786～0.853)。校准曲线表明实际HF住院概率与预测概率之间一致性良好(2年的校准斜率中位数为1.018)；决策曲线显示临床净收益较高。 结论　本研究的预测模型可对MHD患者HF住院风险进行准确、个性化评估，具有一定的临床实用价值。

关键词: 维持性血液透析, 心力衰竭, 预测模型, 外部验证, 列线图

Abstract: Objective  To construct a nomogram to predict the risk of hospitalization for heart failure (HF) in maintenance hemodialysis (MHD) patients.  Methods  MHD patients from four centers in northeast Sichuan during 2017 to 2023 were included in this study. Their basic information, clinical data, laboratory and imaging results were collected. Patients in the two centers were used as the training set (n=386), and those in the other two centers were used as the external validation set (n=116). Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were used to analyze the related risk factors. A nomogram model for the risk of HF hospitalization was established. The prediction efficiency of the model was evaluated by the area under the receiver operating characteristic (ROC) curve, and the accuracy and practicability of the model were analyzed and evaluated by the calibration curve and the decision curve.  Results  The median follow-up periods of the training set and external validation set were 15 months (9, 24) and 14 months (10, 21), respectively. HF hospitalization occurred in 140 cases (36.27%) and 28 cases (24.14%) in training set and external validation set, respectively. Cox regression showed that the N-terminal pro-brain natriuretic peptide (HR=1.532, 95% CI:1.244～1.886, P<0.001), percentage of lymphocytes (HR=0.975, 95% CI:0.952～0.999, P=0.038), right atrium diameter (HR=1.060, 95% CI:1.017～1.105, P=0.005)/right ventricle diameter (HR=1.033, 95% CI:0.998～1.062, P=0.064), weekly dialysis duration (HR=0.667, 95% CI:0.459～0.968, P=0.033), HF score (HR=1.778, 95% CI:1.130～2.798, P=0.013), use of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker medications (HR=0.569, 95% CI: 0.353～0.917, P=0.020), and history of coronary heart disease/diabetes (HR=1.582, 95% CI:1.002～2.500, P=0.049) were independently associated with HF hospitalization. The C-statistic for internal and external validation were 0.836 (95% CI:0.802～0.870) and 0.819 (95% CI:0.786～0.853), respectively. The calibration curve showed that there was a good consistency between actual probability and predicted probability of HF hospitalization (the median of the 2-year calibration slope was 1.018). The decision curve showed that the clinical net income was higher.  Conclusion  The prediction model of this study can accurately and individually evaluate the risk of HF hospitalization in MHD patients, and is of clinical practice value.

Key words: Maintenance hemodialysis, Heart failure, Prediction model, External verification, Nomogram

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