Abstract:

Objective To determine risk factors of antibiotic associated diarrhea in patients with respiratory diseases,and develop a nomogram model to predict these risks. Methods A total of 291 patients who underwent antibiotics treatment were recruited from January,20l9 and September,2019 at respiratory department in a Level A tertiary hospital in Beijing. Multivariate logistic regression was conducted to identify independent risk factors of antibiotic associated diarrhea in inpatients with respiratory diseases. A nomogram was developed by R software and validated to predict the risk of antibiotic associated diarrhea. Results Multivariate logistic regression analysis revealed that fecal occult blood test[OR=4.517,95%CI（1.440~14.163）],BMI[OR=0.834,95%CI（0.735~0.947）], hemoglobin level[OR=0.970,95%CI（0.946~0.994）],the use of antibiotics before hospitalization[OR=2.957,95%CI（1.076~8.130）] and types of antibiotic[OR=2.148,95%CI（1.146~4.026）] were independent risk factors of antibiotic associated diarrhea in patients with respiratory diseases（P<0.05）. For validation of the nomogram,ROC curve revealed that the model predicting antibiotic associated diarrhea in patients with respiratory diseases was the area under the curve of 0.779,the slope of the calibration plot was close to 1 and the model passed Hosmer-Lemeshow goodness of fit test（ χ²=1.413,P=0.994）,which demonstrated that the model was of good accuracy. Conclusion The nomogram predicting antibiotic associated diarrhea in patients with respiratory diseases was constructed based on fecal occult blood test,BMI,hemoglobin level,the use of antibiotics before hospitalized and types of antibiotic,which has good discrimination and accuracy. It can provide scientific guidance for clinical individualized prevention of antibiotic associated diarrhea.

Key words: Respiratory Tract Diseases, Anti-Bacterial Agents, Antibiotic Associated Diarrhea, Nomogram, Nursing Care

摘要：

目的 通过分析呼吸科住院患者抗生素药物相关腹泻的危险因素,建立并验证呼吸科住院患者抗生素药物相关腹泻风险的列线图模型。 方法 纳入2019年1月—9月于北京市某三级甲等医院呼吸科病房住院使用抗生素治疗的患者291例并收集临床资料。应用Logistic回归模型分析呼吸科住院患者抗生素药物相关腹泻的独立危险因素。应用R软件构建预测呼吸科住院患者抗生素药物相关腹泻风险的列线图模型,并进行验证。 结果 Logistic回归分析显示,大便潜血[OR=4.517,95%CI（1.440~14.163）]、体重指数[OR=0.834,95%CI（0.735~0.947）]、血红蛋白浓度[OR=0.970,95%CI（0.946~0.994）]、院前使用抗生素[OR=2.957,95%CI（1.076~8.130）]及使用抗生素种类[OR=2.148,95%CI（1.146~4.026）]是呼吸科住院患者抗生素药物相关腹泻的独立危险因素（P<0.05）。对列线图模型进行验证,ROC曲线显示该模型预测呼吸科住院患者抗生素药物相关腹泻的风险曲线下面积为0.779;校准曲线为斜率接近于1的直线,Hosmer-Lemeshow拟合优度检验（ χ²=1.413,P=0.994）均显示该模型能够较准确地预测呼吸科住院患者抗生素药物相关腹泻的风险。结论 该研究基于大便潜血、院前使用抗生素、体重指数、血红蛋白浓度、使用抗生素种类数这5项抗生素药物相关腹泻发生的独立危险因素,构建的列线图模型具有良好的区分度与准确度,可为临床个体化预测抗生素药物相关腹泻发生风险提供参考。

关键词: 呼吸道疾病, 抗菌药, 抗生素药物相关腹泻, 列线图, 护理