Predicting efficiency of post-induction mask ventilation based on demographic and anatomical factors

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background

Failure to ventilate patients by mask leads to serious complications especially if associated with difficult intubation. Previous studies have used subjective and indirect measures to evaluate difficulty in mask ventilation, which are associated with high inter-observer discrepancies. In this study, we have defined and used efficiency of mask ventilation (EMV) as an objective and direct surrogate for ease of mask ventilation in patients undergoing GA and mask ventilation using neuromuscular relaxation.

Materials and Methods

1050 adult patients prospectively were evaluated with respect to different patients demographic and physical factors and EMV. EMV was defined as the ratio of minute ventilation via anesthesia mask to that via tracheal tube expressed as percentage. Edentolous patients were ventilated using lip-over-mask techniques. Separate analyses were done for edentolous and non-edentolous patients.

Results

EMV in edentolous patients (n=269) using the lip-over-mask method was relatively high (90.9 ± 14.3%, 60.14-128.57 range). The result of multiple regression analysis in patients with normal denture determined receded chin, presence of beard, male gender, high Mallampati classes, high neck circumference, low inter-incisors gap, and old age as independent factors for estimating EMV. A regression formula for predicting EMV was developed which had an acceptable R-square value with a good model fit.

Conclusions

Using EMV is an easy and reliable tool for measuring efficiency of mask ventilation. Based on the result of this study, EMV can be estimated from patient's demographic and physical factors. In edentolous patients, using the lip-over-mask method results in adequate ventilation of lungs.

Language:
English
Published:
Advanced Biomedical Research, Volume:2 Issue: 2, May 2012
Page:
10
https://www.magiran.com/p2330310  
سامانه نویسندگان
  • Saghaei، Mahmoud
    Corresponding Author (1)
    Saghaei, Mahmoud
    Assistant Professor Department of Anesthesia and Critical Care, Isfahan University Of Medical Sciences, Isfahan, Iran
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