中华护理杂志 ›› 2024, Vol. 59 ›› Issue (21): 2611-2619.DOI: 10.3761/j.issn.0254-1769.2024.21.008

• 专科护理实践与研究 • 上一篇    下一篇

维持性血液透析中低血压风险预测的Meta建模及验证

吕桂兰(), 曹虎男, 王浩, 樊蕊   

  1. 210002 南京市 解放军东部战区总医院国家肾脏疾病临床医学研究中心(吕桂兰,樊蕊);南京医科大学附属宿迁第一人民医院急诊科(曹虎男,王浩)
  • 收稿日期:2024-01-23 出版日期:2024-11-10 发布日期:2024-11-04
  • 作者简介:吕桂兰:女,硕士,主任护师,科护士长,E-mail:2271500539@qq.com
  • 基金资助:
    东部战区总医院院管课题(YYHL2021062);2023年宿迁市第一人民医院科研专项(KY202307)

Meta-modeling and validation of a risk prediction model for intradialytic hypotension in maintenance hemodialysis patients

LÜ Guilan(), CAO Hunan, WANG Hao, FAN Rui   

  • Received:2024-01-23 Online:2024-11-10 Published:2024-11-04

摘要:

目的 基于Meta建模构建维持性血液透析中低血压(intradialytic hypotension,IDH)风险预测模型并进行验证。方法 检索Cochrane Library、PubMed、Web of Science、EBSCO、Scopus、CINAHL、中国知网、万方数据库自建库至2023年3月31日报告IDH危险因素的文献。使用随机效应模型合并OR值,筛选P<0.05的因素并通过其β系数建立模型,选择286例血液透析患者作为验证集评估模型的区分度、校准度和临床实用度。结果 共纳入39篇文献,涉及25 546例患者,选取14个影响因素用于构建风险预测模型。IDH发生风险得分=-0.301 × 男性+0.015 × 年龄+0.004 × 透析龄+0.988 × 合并糖尿病+0.730 × 合并心血管疾病-0.042 × 透析前舒张压+0.666 × 采用血液透析滤过模式+0.076 × 加热温度+0.159 × 超滤率+0.476 × 超滤量+1.024 × 透析间期体重增加+0.053 × 血清磷+0.023 × 血尿素氮+0.040 × β2微球蛋白,选择肾脏病预后质量倡议、透析中最低收缩压<90 mmHg(1 mmHg=0.133 kPa)、透析中收缩压下降≥20 mmHg及英国肾脏病协会指南定义的透析中低血压作为4种结局指标。IDH预测模型在4种结局指标的曲线下面积分别为0.830、0.648、0.647和0.763。校准曲线显示模型在前2种结局下预测与实际大致相符(χ2=14.824,P=0.064;χ2=12.016,P=0.149)。决策分析显示在所有定义下模型整体上比全部干预和全部不干预的策略有更好的净获益。结论 该研究利用Meta建模开发的IDH风险预测模型预测性能良好,具有一定的临床应用价值。

关键词: 血液透析, 低血压, 预测模型, Meta分析, 护理

Abstract:

Objective Meta modelling was employed to develop a risk prediction model for intradialytic hypotension(IDH) and validate the model. Methods Literature on risk factors for IDH published up to March 31,2023 was retrieved from 8 databases,including Cochrane Library,PubMed,Web of Science,EBSCO,Scopus,CINAHL,CNKI and Wanfang Database. Random effects model was used to combine ORs,and factors with P<0.05 were selected to establish the model based on their regression coefficients. 286 maintenance hemodialysis patients were selected as a validation cohort to evaluate the model’s discrimination,calibration and clinical utility. Results 39 studies were included,involving 25 546 patients. 14 factors were identified to establish the risk prediction model. The risk score for IDH occurrence was calculated as -0.301 × male+0.015 × age+0.004 × dialysis vintage+0.988 × diabetes+0.730 × cardiovascular disease-0.042 × predialysis systolic blood pressure+0.666 × dialysis mode of hemodialysis filter+0.076 × temperature+0.159 × ultrafiltration rate+0.476 × ultrafiltration volume+1.024 × weight gain between dialysis+0.053 × serum phosphorus+0.023 × blood urea nitrogen+0.040 × β2-microglobulin. Definition in the Kidney Disease Outcomes Quality Initiative guideline,nadir intradialytic systolic blood pressure <90 mmHg(1 mmHg=0.133 kPa),falling intradialytic systolic blood pressure ≥20 mmHg,and definition in the United Kingdom Kidney Association guideline were selected as 4 outcomes. The areas under the curve for the prediction model with respect to these 4 outcomes were 0.830,0.648,0.647,and 0.763,respectively. Calibration curves showed that the model predictive outcomes were consistent with actual outcomes for the first 2 outcomes(χ2=14.824,P=0.064;χ2=12.016,P=0.149). Decision curve analysis indicated that the model had better net benefit compared to either intervention/no intervention for all definitions. Conclusion The IDH risk prediction model developed by meta-modeling in this study has good predictive performance and certain application value.

Key words: Hemodialysis, Hypotension, Prediction Model, Meta-Analysis, Nursing Care