A Prospective Study to Compare Predictive Value of Five Parameters for Difficult Intubation
DOI:
https://doi.org/10.25751/rspa.40606Keywords:
Airway Management, Intubation, Intratracheal, LaryngoscopyAbstract
Introduction: Patients undergoing surgery under general anesthesia must have their airways secured and proper breathing and oxygenation. Complications from poor airway control might include aspiration, hypoxemia, airway damage, and even mortality. Therefore, it is crucial to anticipate a challenging airway and intubation to prevent complications. The study aims to develop a simple, easy-to-use predictor with high specificity and sensitivity for predicting difficult intubation. The five parameters being looked at are thyromental height test (TMHT), thyromental distance (TMD), modified Mallampati classification (MPC), neck circumference (NC), and Wilson’s score (WS).
Methods: Five parameters were used to evaluate patients preoperatively for difficult intubation, and an intubation difficulty score was calculated. We calculated and compared the specificity, sensitivity, positive predictive value, negative predictive value, and area under the curve for these five parameters.
Results: The PPV of TMHT was 80%, TMD was 40%, MPC was 34.37%, NC was 26.83%, and MPC was 26.09% respectively. The TMHT showed a specificity of 97.75%, sensitivity of 71.43%, NPV OF 96.44%, and accuracy of 94.80% with an area under the curve was 0.946.
Conclusion: The study found that thyromental height (TMHT) was the best predictor out of all the factors that were looked at. It had the highest sensitivity, PPV, NPV, accuracy, and AUC. Mallampati score (MPC), neck circumference (NC), and Wilson score (WS) demonstrated similar statistical values, but these were of limited diagnostic value. Thyromental distance (TMD) was the least reliable parameter for predicting difficult intubation due to its limited sensitivity.
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Copyright (c) 2025 Abhinav S Chetty, Naina Dalvi, Suchita Kosare, Pallavi Kharat, Mahesh B. Shinde, Aparna Nerurkar, Chhavi Kowe, Natanshi Kumar, Yash Nav Singh, Yash Jain, Vaishali Jha, Kunal Shah
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