Prediction of difficult tracheal intubation

Abstract

Objectives: To find the best predicting test for difficult intubation in patients planned for general anesthesia with intubation. Material and Methods: It was Analytical study of cross sectional comparative type and was conducted in Anesthesia Department, Khyber Teaching Hospital, Peshawar from July 2008 to June 2009. A total of 100 patients were selected who were to undergo General Anesthesia (GA) with intubation. They were divided into two groups A & B of 50 patients each. Group A patients were assessed by Mallampati, Thyromental and Sternomental Distances. Group B patients were assessed by Wilson Risk Sum. Results: Data was analyzed in Statistical Package for Social Sciences(SPSS) version 10.0. Frequency and percentage were computed for all parameters in both groups. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were computed for both techniques taking Cormac and Lehane classification as gold standard. Mallampati Classification, Thyromental Distance and Sternomental Distance evaluative methods proved to be more sensitive and specific and also showed high PPV and NPV than Wilson Risk Sum alone. Conclusion: By combining Mallampati Classification with Thyromental and Sternomental Distances, the result of prediction of difficult intubation is more accurate and seems to be a better choice than Wilson Risk Sum alone.