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作 者:黄昏 春晓 马敬香 钟咏梅 翟志慧 黎明 HUANG Hun;CHUN Xiao;MA Jingxiang;ZHONG Yongmei;ZHAI Zhihui;LI Ming
机构地区:[1]广州市妇女儿童医疗中心儿童重症监护室,广州市510623 [2]广州市妇女儿童医疗中心院感科,广州市510623
出 处:《中华急危重症护理杂志》2022年第1期24-29,共6页Chinese Journal of Emergency and Critical Care Nursing
基 金:广州市妇女儿童医疗中心/儿科研究所内部科研基金(YIP-2018-045)。
摘 要:目的探讨危重症患儿医源性戒断综合征发生的危险因素并构建预测模型。方法采用便利抽样法,收集2019年6月—2020年2月广州市某三级甲等儿童专科医院儿科重症监护室使用镇痛镇静药物患儿的资料,采用单因素分析及多因素Logistic回归分析医源性戒断综合征发生的危险因素,并初步建立预测模型。结果最终纳入危重症患儿110例,发生医源性戒断综合征47例(42.7%)。Logistic回归分析结果显示,咪达唑仑每日累积剂量(mg/kg)、枸橼酸芬太尼每日累积剂量(mcg/kg)为危重症患儿发生医源性戒断综合征的独立危险因素。最终建立的预测模型ROC曲线下面积为0.761[95%CI(0.671,0.851)],Hosmer-Lemeshow检验P=0.662,Omnibus检验P<0.001。结论危重症患儿医源性戒断综合征发生率处于较高水平,咪达唑仑、枸橼酸芬太尼每日累积剂量高的患儿发生医源性戒断综合征风险较高。构建的预测模型可帮助医护人员预测危重症患儿医源性戒断综合征,科学有效地进行镇痛镇静管理。Objective To investigate the risk factors and establish a risk prediction model for iatrogenic withdrawal syndrome in critically ill children. Methods The convenient sampling was used to enroll children with analgesic and sedative drugs in the pediatric intensive care unit of a third-level A children’s specialist hospital in Guangzhou from June 2019 to February 2020. The univariate analysis and multivariate logistic regression analysis were used to analyze risk factors of iatrogenic withdrawal syndrome,and the prediction model was established. Results A total of 110 critically ill children were enrolled in this study. The incidence of iatrogenic withdrawal syndrome in critically ill children was 42.7%. Multivariate logistic regression analysis showed that the independent risk factors of iatrogenic withdrawal syndrome were daily cumulative dose of midazolam and fentanyl. The area under the ROC curve was 0.761[95%CI(0.671,0.851)],and the test result of Hosmer-Lemeshow showed that P=0.662 and the test result of Omnibus showed that P<0.001. Conclusion The incidence of iatrogenic withdrawal syndrome in critically ill children is in high level. The children with higher daily cumulative dose of midazolam and fentanylmay have higher risk of iatrogenic withdrawal syndrome. The prediction model constructed in this study can help medical staff to identify iatrogenic withdrawal syndrome early and manage analgesia and sedation scientifically and effectively.
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