血液透析患者发生高钾血症的相关因素分析及风险评估模型的建立与验证

Analysis of risk factors for hyperkalemia in hemodialysis patients and establishment and verification of risk assessment model of hyperkalemia

目的探讨血液透析(HD)患者发生高钾血症的相关因素,建立规律HD患者发生高钾血症的风险评估模型并进行验证。方法回顾性收集2020年4月至2021年1月郑州大学第一附属医院肾脏内科规律HD患者的临床资料。通过转换-随机数字生成器分为训练集和验证集。选取训练集数据,采用多因素logistic回归分析筛选高钾血症的相关因素并赋分,建立高钾血症的风险评估模型;将验证集数据代入模型,绘制受试者工作特征(ROC)曲线,计算曲线下面积(AUC),对模型评估高钾血症的效能进行验证。结果共入选502例患者,年龄(54±13)岁,其中男268例,女234例。训练集372例,验证集130例。最终纳入酸中毒、高钾饮食、既往高钾史、既往心力衰竭、心电图改变、通路功能不良、距离末次透析间隔时间进行多因素logistic分析,并根据这些因素建立风险评估模型。在验证集中绘制ROC曲线,计算AUC为0.799。建议≥5分为发生高钾血症的风险阈值,该cut-off值下对于高血钾事件评估的灵敏度为61.4%,特异度为86.3%。结论本研究初步建立了HD患者发生高钾血症的风险评估模型,可在一定程度上帮助临床医师管理HD患者的血钾水平。

Objective To explore risk factors for hyperkalemia in hemodialysis(HD)patients,and establish and verify a risk assessment model of hyperkalemia in HD patients.Methods The clinical data of HD patients who were admitted to the Department of Nephrology of the First Affiliated Hospital of Zhengzhou University between April 2020 and January 2021 were retrospectively collected and divided into training dataset and validation dataset by using the conversion-random number generator.In the training dataset,multivariate logistic regression analysis was used to screen the risk factors for hyperkalemia in HD patients and the factors were scored to establish the risk assessment model.The validation dataset was substituted into the model and the receiver operating characteristic(ROC)curve was drawn and the area under the curve(AUC)was calculated to verify the effectiveness of the risk prediction model in predicting hyperkalemia.Results A total of 502 HD patients were enrolled and further divided into training dataset(n=372)and validation dataset(n=130).There were 268 males and 234 females,with a mean age of(54±13)years.Multivariate logistic regression analysis showed that metabolic acidosis,high potassium diet,history of hyperkalemia,the change of electrocardiogram(ECG),disfunction of vascular access and time interval from last dialysis were risk factors for causing hyperkalemia in patients undergoing HD.Risk assessment model was established based on these risk factors.The AUC of the ROC curve was 0.799.Using 5 as the cut-off value,the sensitivity and specificity for predicting hyperkalemia events was 61.4%and 86.3%,respectively.Conclusion The current study preliminarily established a risk assessment model for hyperkalemia in HD patients,which can help clinicians manage the potassium level of HD patients.