智能分级预警模式在急危重症新生儿院内急救转运中的应用研究  

Application of Intelligent Grading Early Warning Model in In-hospital Emergency Transport of Critically Ill Neonates

作　　者：陈晓辉 林惠 君杨瑞 Chen Xiaohui;Lin Huijun;Yang Rui(Department of Neonatology,Meizhou Maternal and Child Health Hospital,Meizhou 514000,Guangdong Province,China)

机构地区：[1]梅州市妇幼保健院新生儿科,广东梅州514000

出　　处：《中外医药研究》2025年第6期33-35,共3页JOURNAL OF CHINESE AND FOREIGN MEDICINE AND PHARMACY RESEARCH

摘　　要：目的:探讨智能分级预警模式在急危重症新生儿院内急救转运中的应用效果。方法:选取2022年3月—2024年3月于梅州市妇幼保健院进行院内急救转运的66例急危重症新生儿为研究对象,其中2022年3月—2023年3月为常规组(采用常规风险管理),2023年3月—2024年3月为预警组(在常规组基础上采用智能分级预警模式),各33例。比较两组急救成功率、病情严重程度[危重病例评分(NCIS)]、新生儿转运时间、新生儿不良结局发生率。结果:预警组急救成功率高于常规组(P=0.046);抵达接收科室时,两组NCIS评分降低,预警组高于常规组(P<0.05);预警组急救转运时间短于常规组(P=0.010);预警组新生儿不良结局总发生率低于常规组(P=0.017)。结论:智能分级预警模式在急危重症新生儿院内急救转运中的应用效果显著,可缩短转运时间,降低转运后病情严重程度,提高抢救成功率,降低新生儿不良结局发生风险。Objective:To investigate the application effect of the intelligent grading early warning model in the in-hospital emergency transport of critically ill neonates.Methods:A total of 66 critically ill neonates who underwent in-hospital emergency transport at Meizhou Maternal and Child Health Hospital from March 2022 to March 2024 were selected as the study subjects.The period from March 2022 to March 2023 was designated as the conventional group(using conventional risk management),and the period from March 2023 to March 2024 was designated as the early warning group(using the intelligent grading early warning model in addition to conventional management),with 33 cases in each group.The first-aid success rate,disease severity[Neonatal Critical Illness Score(NCIS)],neonatal transport time,and incidence of adverse neonatal outcomes were compared between the two groups.Results:The first-aid success rate in the early warning group was higher than that in the conventional group(P=0.046).Upon arrival at the receiving department,the NCIS scores of both groups decreased,with the early warning group showing higher scores than the conventional group(P<0.05).The emergency transport time in the early warning group was shorter than that in the conventional group(P=0.010).The overall incidence of adverse neonatal outcomes in the early warning group was lower than that in the conventional group(P=0.017).Conclusion:The application of the intelligent grading early warning model in the in-hospital emergency transport of critically ill neonates demonstrates significant effects,including shortened transport time,reduced disease severity post-transport,improved rescue success rate,and decreased risk of adverse neonatal outcomes.

关 键 词：智能分级预警模式 急危重症 新生儿 院内急救转运 

分 类 号：R473.72[医药卫生—护理学]