摘要
目的:建立有效的气管插管困难综合预测系统。方法:选择260例口腔颌面外科手术患者,应用Logistic回归分析插管困难的各种影响因素,包括病史、性别、年龄、身高、体重、ASA分级、上下切牙间距离、下颌骨长度、颏至甲状软骨间距离、颏至胸骨间距离、颈部后仰度、Mallampati试验、深覆盖。插管困难的标准为Cormack-Lehane喉头Ⅲ级、Ⅳ级或无法置入直接喉镜。结果:插管困难相关因素为:有否困难病史、体重、上下切牙间距离、颏至甲状软骨间距离、颈部后仰度和Mallampati试验等,其相对危险度分别为3.218、3.416、3.371、5.930、3.326、2.631(P<0.05);插管困难综合预测系统的建立:将已得出的6项相关因素作为预测指标,每项分别设为1、2、3分,总分18分,分数越大,发生插管困难的危险性越大;与Mallampati试验或Wilson评分比较,插管困难综合预测系统的敏感度高(94.9%)(P<0.05),漏诊率低(5.1%)(P<0.05)。结论:气管插管困难综合预测系统是预测插管困难的有效方法,可为术前识别困难病例提供依据。
PURPOSE: To build up an effective system for predicting difficult tracheal intubation. METHODS: 260 cases of oral maxillofacial surgery were selected. Using Logistic regression method to analyse relative factors,including healthy history,sex,age,height,weight,ASA,upper-lower incisor teeth distance, mandibular length, thyroid-mentum distance,thyroid-sternum distance, neck upward degree, Mallampati test, over bite.The standard of difficult intubation was Cormack-Lehane classes III-IV and difficulty in inserting a laryngoscope. RESULTS: The relative factors of difficult intubation were difficult airway history,weight, upper-lower incisor teeth distance, thyroid-mentum distance, neck upward degree, Mallampati test,their relative risks were 3.218,3.416,3.371,5.930,3.326,2.631(P<0.05).To build up a comprehensive system for predicting difficult intubation,the predicting standards included the six relative factors, each factor had 1 score,2 score,3 score, the higher score,means the more risks.To compare with Mallampati test and Wilson score,the comprehesive system had higher sensitivity (94.9%)(P<0.05)with lower misdiagnosis rate(5.1%). CONCLUSION: The comprehesive system is an effective method for predicting difficult intubation.It can help to identify difficult cases according to the results of this predicting system.
出处
《中国口腔颌面外科杂志》
CAS
2004年第2期73-76,共4页
China Journal of Oral and Maxillofacial Surgery
基金
上海第二医科大学校优秀青年教师培养基金(2003)
关键词
气管插管
综合预测系统
预测手段
评分方法
Oral maxillofacial surgery
Perioperative period
Difficult airway
Difficult tracheal intubation
Prediction
