地高辛血药浓度超出安全限值风险预测模型的建立与评估

目的：探讨地高辛血药浓度超出安全限值（2.0 ng·mL^-1）的影响因素并构建相关风险预测模型，为地高辛的安全合理用药提供参考。方法：回顾性分析2019年1月至2020年12月安徽医科大学附属六安医院服用地高辛进行治疗并接受血药浓度监测的153例住院患者的临床资料，将所纳入患者按地高辛血药浓度监测值分为达标组（0.5 ng·mL^-1≤血药浓度值≤2.0 ng·mL^-1）和超限组（血药浓度值>2.0 ng·mL^-1），对两组患者的性别、年龄、体质指数（BMI）、肾损害情况、日均服药剂量，合并用药情况采用Logistic回归分析筛选地高辛血药浓度超出安全限值的独立影响因素，根据筛选出的独立影响因素建立列线图预测模型，并对该模型进行评估。结果：患者的性别（OR=0.379，95% CI：0.244~0.589）、肾损害情况（OR=0.252，95% CI：0.162~0.391）、日均服药剂量（OR=0.438，95% CI：0.279~0.689）、合用促胃动力药（OR=1.975，95% CI：1.294~3.013）、合用抗菌药物（OR=0.471，95% CI：0.299~0.741），合用β受体阻滞剂（OR=0.454，95% CI：0.277~0.642）以及合用芪苈强心胶囊（OR=0.096，95% CI：0.026~0.353）是地高辛血药浓度超出安全限值的独立影响因素。根据所筛选出的7项独立影响因素，建立了地高辛血药浓度超出安全限值的列线图预测模型，该模型的C-index指数为0.742，表明该列线图模型具有较好的区分度，对该模型进行验证后发现预测值和观察值基本一致，表明该列线图预测模型具有较好的一致性。结论：本研究通过筛选出地高辛血药浓度超出安全限值的独立影响因素建立了能够预测其相关风险的列线图模型，该列线图有着良好的区分度及一致性，具有较高的临床应用价值，对甄别洋地黄中毒高风险人群，提前准备应对方案有着较为重要的指导意义。

Establishment and evaluations of risk prediction model of digoxin blood concentration exceeding a safe limit

OBJECTIVE To explore the influencing factors of digoxin blood concentration exceeding a safe limit and establish a risk prediction model to provide reference for safe and rational dosing of digoxin.METHODS Clinical data were retrospectively reviewed for 153 patients on digoxin therapy and blood concentration was monitored from January 2019 to December 2020. They were divided into goal-attaining group (0.5 ng·mL^-1≤blood concentration≤2.0 ng·mL^-1) and over-limit group (blood concentration >2.0 ng·mL^-1) according to the levels of blood digoxin concentration. Gender, age, body mass index (BMI), kidney damage, daily dose and combined drug dosing of two groups were screened by Logistic regression analysis for independent influencing factors of blood digoxin concentration exceeding a safe limit. A nomogram prediction model was established on the basis of screened independent influencing factors.RESULTS Gender (OR=0.379, 95%CI: 0.244-0.589), kidney damage (OR=0.252, 95%CI:0.162-0.391), daily dose (OR=0.438, 95%CI:0.279-0.689), combination of gastroprokinetic agents (OR=1.975, 95%CI:1.294-3.013), combination of antibiotics (OR=0.471, 95%CI:0.299-0.741), combination of β-receptor blockers (OR=0.454, 95%CI:0.277-0.642) and Qili Qiangxin capsule (OR=0.096, 95%CI:0.026-0.353) were independent influencing factors of blood digoxin concentration exceeding a safe limit. Based upon seven independent influencing factors, a nomogram prediction model for blood digoxin concentration exceeding a safe limit was established. C-index of the model was 0.742, indicating that the nomogram model had a decent discrimination. The validation of the model showed that the predicted and observed values were basically consistent, indicating that the nomogram prediction model had a decent consistency.CONCLUSION The nomogram model based upon independent influencing factors has showed excellent discrimination and consistency. With clinical value in screening patients with a high risk of blood digoxin concentration exceeding a safe limit, it is of great significance to prepare treatment protocols for these patients.