Detection of difficult airway using deep learning
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ORIGINAL ARTICLE
Detection of difficult airway using deep learning Kevin Aguilar1 · Germán H. Alférez1
· Christian Aguilar2
Received: 30 May 2019 / Revised: 24 September 2019 / Accepted: 6 December 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Whenever a patient needs to enter the operating room, in case the surgery requires general anesthesia, he/she must be intubated, and an anesthesiologist has to make a previous check to the patient in order to evaluate his/her airway. This process should be done to the patient to anticipate any problem, such as a difficult airway at the time of being anesthetized. In fact, the inadequate detection of a difficult airway can cause serious complications, even death. This research work proposes a mobile app that uses a convolutional neural network to detect a difficult airway. This model classifies two classes of the Mallampati score, namely Mallampati 1–2 (with low risk of difficult airway) and Mallampati 3–4 (with higher risk of difficult airway). The average accuracy of the predictive model is 88.5% for classifying pictures. A total of 240 pictures were used for training the model. The results of sensitivity and specificity were 90% in average. Keywords Difficult airway · Deep learning · Convolutional neural networks
1 Introduction One of the biggest fears that anesthesiologists have is to confront a patient with a difficult airway, whether previously diagnosed or in the worst case, unexpectedly. A difficult airway is defined as the need for three or more attempts to intubate the trachea or more than 10 minutes to achieve it [1]. Approximately, it occurs in 1.5–8% of procedures where general anesthesia is used. The incidence of the “non-intubable patient” or “non-ventilatory patient” situation is present in 1/50,000 patients. Likewise, the failure of orotracheal intubation occurs in 1/2000 programmed cases, increasing to 1/200 cases in emergency rooms. In pregnant women, the difficult intubation is 7.9%, and in cases of very difficult intubation, it is 2% [2]. This is why the anesthesiologist must evaluate the
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Germán H. Alférez [email protected] Kevin Aguilar [email protected] Christian Aguilar [email protected], [email protected]
1
Facultad de Ingeniería y Tecnología, Universidad de Montemorelos, Av. Libertad 1300 Poniente, Barrio Matamoros, 67530 Montemorelos, N.L., Mexico
2
Escuela de Medicina, Universidad de Montemorelos, Av. Libertad 1300 Poniente, Barrio Matamoros, 67530 Montemorelos, N.L., Mexico
patient airway before anesthesia to develop an appropriate plan of anesthetic management [3–5]. Since 1993, the American Society of Anesthesiology (ASA) has published its management guidelines in difficult airway. These guidelines give very specific guidance to the anesthesiologist for the management of these cases. Specifically, these guidelines focus on maintaining good ventilation and oxygenation since a failed intubation can cause an increase in morbidity and mortality [1,6]. Based on this concern for patien
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