Prediction of Difficult Mask Ventilation

Author:

Langeron Olivier1,Masso Eva2,Huraux Catherine3,Guggiari Michel3,Bianchi André3,Coriat Pierre4,Riou Bruno5

Affiliation:

1. Assistant Professor.

2. Fellow.

3. Staff Anesthesiologist.

4. Professor and Chairman.

5. Professor.

Abstract

Background Maintenance of airway patency and oxygenation are the main objectives of face-mask ventilation. Because the incidence of difficult mask ventilation (DMV) and the factors associated with it are not well known, we undertook this prospective study. Methods Difficult mask ventilation was defined as the inability of an unassisted anesthesiologist to maintain the measured oxygen saturation as measured by pulse oximetry > 92% or to prevent or reverse signs of inadequate ventilation during positive-pressure mask ventilation under general anesthesia. A univariate analysis was performed to identify potential factors predicting DMV, followed by a multivariate analysis, and odds ratio and 95% confidence interval were calculated. Results A total of 1,502 patients were prospectively included. DMV was reported in 75 patients (5%; 95% confidence interval, 3.9-6.1%), with one case of impossible ventilation. DMV was anticipated by the anesthesiologist in only 13 patients (17% of the DMV cases). Body mass index, age, macroglossia, beard, lack of teeth, history of snoring, increased Mallampati grade, and lower thyromental distance were identified in the univariate analysis as potential DMV risk factors. Using a multivariate analysis, five criteria were recognized as independent factors for a DMV (age older than 55 yr, body mass index > 26 kg/m2, beard, lack of teeth, history of snoring), the presence of two indicating high likelihood of DMV (sensitivity, 0.72; specificity, 0.73). Conclusion In a general adult population, DMV was reported in 5% of the patients. A simple DMV risk score was established. Being able to more accurately predict DMV may improve the safety of airway management.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Anesthesiology and Pain Medicine

Reference26 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3