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Difficult mask ventilation in general surgical population: observation of risk factors and predictors [version 1; referees: 2 approved]

Authors :
Davide Cattano
Peter V. Killoran
Chunyan Cai
Anastasia D. Katsiampoura
Ruggero M. Corso
Carin A. Hagberg
Author Affiliations :
<relatesTo>1</relatesTo>Department of Anesthesiology, University of Texas Medical School at Houston, Houston, TX, 77030, USA<br /><relatesTo>2</relatesTo>Division of Clinical and Translational Sciences, , Department of Internal Medicine, University of Texas Medical School at Houston, Houston, TX, 77030, USA<br /><relatesTo>3</relatesTo>Emergency Department, Anesthesia and Intensive Care Section, “GB Morgagni – L Pierantoni” Hospital, Forli, 47121, Italy
Source :
F1000Research. 3:204
Publication Year :
2014
Publisher :
London, UK: F1000 Research Limited, 2014.

Abstract

Background: There are few predictors of difficult mask ventilation and a simple, objective, predictive system to identify patients at risk of difficult mask ventilation does not currently exist. We present a retrospective - subgroup analysis aimed at identifying predictive factors for difficult mask ventilation (DMV) in patients undergoing pre-operative airway assessment before elective surgery at a major teaching hospital. Methods: Data for this retrospective analysis were derived from a database of airway assessments, management plans, and outcomes that were collected prospectively from August 2008 to May 2010 at a Level 1 academic trauma center. Patients were stratified into two groups based on the difficulty of mask ventilation and the cohorts were analyzed using univariate analysis and stepwise selection method. Results: A total of 1399 pre-operative assessments were completed with documentation stating that mask ventilation was attempted. Of those 1399, 124 (8.9%) patients were found to be difficult to mask ventilate. A comparison of patients with and without difficult mask ventilation identified seven risk factors for DMV: age, body mass index (BMI), neck circumference, history of difficult intubation, presence of facial hair, perceived short neck and obstructive sleep apnea. Although seven risk factors were identified, no individual subject had more than four risk factors. Conclusion: The results of this study confirm that in a real world clinical setting, the incidence of DMV is not negligible and suggest the use of a simple bedside predictive score to improve the accuracy of DMV prediction, thereby improving patient safety. Further prospective studies to validate this score would be useful.

Details

ISSN :
20461402
Volume :
3
Database :
F1000Research
Journal :
F1000Research
Notes :
[version 1; referees: 2 approved]
Publication Type :
Academic Journal
Accession number :
edsfor.10.12688.f1000research.5131.1
Document Type :
research-article
Full Text :
https://doi.org/10.12688/f1000research.5131.1