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Rivista di Anestesia, Rianimazione, Terapia Antalgica e Terapia Intensiva
Minerva Anestesiologica 2014 February;80(2):149-57
Difficult mask ventilation in obese patients: analysis of predictive factors
Leoni A. 1, Arlati S. 2, Ghisi D. 3, Verwej M. 1, Lugani D. 1, Ghisi P. 1, Cappelleri G. 1, Cedrati V. 1, El Tantawi Ali Alsheraei A. 1, Pocar M. 4, Ceriani V. 5, Aldegheri G. 1 ✉
1 Department of Anesthesia, IRCCS Multimedica, Sesto San Giovanni, Milan, Italy;
2 Intensive Care Unit G. Bozza, Niguarda Ca’ Granda, Milan, Italy;
3 Department of Anesthesia, Intensive Care and Pain Therapy, University Hospital, Parma, Italy;
4 Department of Cardiac Surgery, IRCCS Multimedica, Sesto San Giovanni, Milan, Italy;
5 Department of Surgery, IRCCS Multimedica, Sesto San Giovanni, Milan, Italy
Background: This study aimed to determine the accuracy of commonly used preoperative difficult airway indices as predictors of difficult mask ventilation (DMV) in obese patients (BMI >30 kg/m2).
Methods: In 309 consecutive obese patients undergoing general surgery, the modified Mallampati test, patient’s Height/Thyromental distance ratio, Inter-Incisor Distance, Protruding Mandible (PM), history of Obstructive Sleep Apnea and Neck Circumference (NC) were recorded preoperatively. DMV was defined as Grade 3 mask ventilation (MV) by the Han’s scale (MV inadequate, unstable or requiring two practitioners). Data are shown as means±SD or number and proportions. Independent DMV predictors were identified by multivariate analysis. The discriminating capacity of the model (ROC curve area) and adjusted weights for the risk factors (odds ratios) were also determined.
Results: BMI averaged 42.5±8.3 kg/m2. DMV was reported in 27 out of 309 patients (8.8%; 95%CI 5.6-11.9%). The multivariate analysis retained NC (OR 1.17; P<0.0001), limited PM (1.99; P=0.046) and Mallampati test (OR 2.12; P=0.009) as risk predictors for DMV. Male gender was also included in the final model (OR 1.87; P=0.06) as biologically important variable albeit the borderline statistical significance. The model yielded a good discriminating capacity (ROC curve 0.85). The four parameters were used to create an unweighted prediction score (ROC curve 0.84) with >2 associated factors as the best discriminating point for DMV.
Conclusion: Obese patients show increased incidence of DMV with respect to the undifferentiated surgical population. Limited PM, Mallampati test and NC are important DMV predictors.