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心血管病防治知识 ›› 2026, Vol. 16 ›› Issue (12): 18-22.

• 临床研究 • 上一篇    下一篇

心力衰竭患者血液超滤治疗发生低血压的列线图风险模型构建

高伟1, 王艺鹏1,*, 郝青青2   

  1. 1、通用环球中铁西安医院,陕西 西安 710000;
    2、西安市碑林区太乙路第二社区卫生服务中心,陕西 西安 710000
  • 出版日期:2026-06-30 发布日期:2026-09-03
  • 通讯作者: *王艺鹏

Construction of a nomogram risk model for hypotension in heart failure patients undergoing blood ultrafiltration

GAO Wei1, WANG Yipeng1, HAO Qingqing2   

  1. 1. Genertec Universal CREC Xi’an Hospital, Xi’an 710000, China;
    2. Taiyi Road No.2 Community Health Service Center of Beilin District, Xi’an 710000, China
  • Online:2026-06-30 Published:2026-09-03

摘要: 目的 探究心力衰竭患者血液超滤治疗发生低血压的列线图风险模型构建。方法 选取2023年1月至2024年12月于本院实施血液超滤的心力衰竭患者80例。根据患者治疗后有无低血压分为低血压组(n=26)和非低血压组(n=54)。记录两组患者的一般资料,通过Logistic回归分析确定心力衰竭患者血液超滤治疗发生低血压的影响因素,建立风险预测模型的列线图,并绘制受试者工作特征(ROC)曲线对预测模型进行评估。结果 低血压组收缩压低于非低血压组[(150.33±12.42 vs 118.65±14.28)mmHg],差异具有统计学意义(P<0.05);低血压组血磷[(2.53±0.67 vs 1.72±0.56)mmol/L]、血浆白蛋白[(36.72±4.97 vs 40.78±5.62)g/L]、CRP[(8.86±0.97 vs 3.85±0.58)mg/L]、超滤速率[(280.05±45.36 vs 220.53±40.64)mL/h]均高于非低血压组,差异具有统计学意义(P<0.05)。结果显示,血磷、血浆白蛋白、超滤速率是心力衰竭患者血液超滤治疗发生低血压的危险因素[比值比(odds ratio,OR)=1.863、2.258、2.752,P<0.05]。根据影响因素构建出列线图模型,曲线下面积为0.948(95%CI:0.874-0.985),灵敏度为88.89%,特异性为88.46%。结论 本研究构建的列线图模型能有效预测心力衰竭患者血液超滤治疗中的低血压风险,关键因素包括超滤速率、血浆白蛋白及血磷水平。

关键词: 心力衰竭, 血液超滤, 低血压, 风险, 模型构建

Abstract: Objective To construct a nomogram risk model for hypotension in patients with heart failure undergoing blood ultrafiltration. Methods A total of 80 patients with heart failure who underwent blood ultrafiltration in our hospital from January 2023 to December 2024 were enrolled, and according to the presence or absence of hypotension after treatment, the patients were divided into hypotension group with 26 patients and non-hypotension group with 54 patients. General information was recorded for both groups, and the logistic regression analysis was used to investigate the influencing factors for hypotension in patients with heart failure undergoing blood ultrafiltration. A nomogram was constructed for the risk prediction model, and the receiver operating characteristic (ROC) curve was plotted to assess the predictive model. Results Compared with the non-hypotension group, the hypotension group had a significantly lower systolic blood pressure (118.65±14.28 mmHg vs 150.33±12.42 mmHg, P<0.05) and significantly higher blood phosphorus (2.53±0.67 mmol/L vs 1.72±0.56 mmol/L, P<0.05), plasma albumin (40.78±5.62 g/L vs 36.72±4.97 g/L, P<0.05), CRP (8.86±0.97 mg/L vs 3.85±0.58 mg/L, P<0.05), and ultrafiltration rate (280.05±45.36 mL/h vs 220.53±40.64 mL/h, P<0.05). The results showed that blood phosphorus, plasma albumin, and ultrafiltration rate were risk factors for hypotension in patients with heart failure undergoing blood ultrafiltration (odds ratio=1.863, 2.258, and 2.752, P<0.05). A nomogram model was constructed based on the influencing factors, with an area under the ROC curve of 0.948 (95% confidence interval: 0.874-0.985), a sensitivity of 88.89%, and a specificity of 88.46%. Conclusion The nomogram model constructed in this study can effectively predict the risk of hypotension in patients with heart failure during blood ultrafiltration, and the key factors include ultrafiltration rate, plasma albumin, and blood phosphorus.

Key words: Heart failure, Blood ultrafiltration, Hypotension, Risk, Model construction