The Voice Analysis as a Preoperative Prediction Method of a Difficult Airway
The Voice Analysis as a Preoperative Prediction Method of a Difficult Airway
Before an anesthetic procedure, airway management is essential to ensure adequate ventilation
 and breathing of the patient during the entire surgical process.

 The preanesthetic evaluation of the airway allows for proper planning, facilitates the
 anticipation of human resources and necessary means to face the possible challenges in a safe
 and efficient way. Orofacial mask ventilation and endotracheal intubation are a crucial step
 in general anesthesia. Most of the time, management is not complicated, but when an
 unpredicted difficult airway occurs, it is currently one of the most important challenges to
 face as an anesthesiologist. These situations are rare as the prevalence of a difficult
 airway is approximately 2.2% of the general population.

 When there is a case of a difficult airway and adequate management is not achieved, very
 serious complications may occur including brain damage, cardio-respiratory arrest, aspiration
 of gastric content, traumatic airway injuries, tooth damage, unnecessary surgical access to
 keep the airway permeable or death. For these reasons, in anesthesia, an unforeseen difficult
 airway is considered a crisis situation. Therefore, a preoperative airway assessment is
 paramount.

 Traditional predictive tests evaluate multiple anthropometric characteristics in which the
 physical presence of the patient is mandatory. However, no test can currently predict a
 difficult airway based on a single characteristic nor in the patient's absence. Nowadays, the
 optimization of resources and new technologies have increased interest in developing new
 tests or methods for preoperatively assessing the difficulty of the airway and new methods of
 airway evaluation have been proposed. As recently demonstrated, the detection of a difficult
 airway depends not only on the morphology but also on functional traits of the airway. Some
 studies propose the analysis of voice parameters as a reflection of anatomical and functional
 features of the superior airway.

 The investigators propose that the analysis of voice characteristics could reflect the
 airway's anatomy and therefore the investigators will be able to predict a difficult airway,
 and this would enable the development of a voice-based assessment method which could have an
 promising role in facilitating telematic airway evaluation.
Proper airway management is essential for safe anesthesia practice. In particular,
 ventilation with an orofacial mask and endotracheal intubation are a crucial step in general
 anesthesia. The prevalence of a difficult airway is approximately 2.2% although it can vary
 greatly according to different groups of patients. It is defined, according to the American
 Society of Anesthesiology, as the clinical situation in which an experienced anesthesiologist
 has difficulty with ventilation using a face mask, during endotracheal intubation or both.
 Although other definitions also exist and include difficulty in ventilation or placement of
 supraglottic devices, difficult laryngoscopy defined by a 3 or 4 grade on the Cormack-Lehane
 scale or multiple attempts at intubation. A case of an unexpected difficult airway can lead
 to minor complications, such as loss or damage to teeth, pharynx or entail severe injuries,
 such as aspiration of gastric content, laryngeal lesions, respiratory failure,
 cardiorespiratory arrest or even death. Furthermore, complications increase considerably when
 there are no alternative plans and multiple repeated attempts at intubation are made.

 Thus, the factors that mostly contribute to complications when an unanticipated difficult
 airway is found are due to deficiencies in identification, communication, preoperative
 planning and lack of training. An unpredicted difficult airway is a situation in which
 decision making is difficult, management is complex, and it is considered a crisis situation.

 The importance of evaluation and management of the airway is such that different study groups
 within the main scientific societies of anesthesiologists are dedicated to studying and
 implementing protocols with the aim of avoiding these risky situations. A difficult airway
 should be detected during the pre-anesthetic visit, thus allowing the anesthesiologist to
 evaluate the patient, identify risk factors, advance to possible complications, and prepare
 an appropriate anesthetic plan. This means organizing both material and personal help,
 informing the patient; changing the type of anesthesia or even postponing elective surgeries
 to schedule them when the patient is correctly optimized making sure that the means in which
 the surgical procedure is safe.

 Regardless of the surgical procedure and the initial anesthetic plan, the evaluation of the
 airway should always be performed with all patients since any sedation or regional anesthesia
 can be converted into a general anesthesia and require control of the airway.

 In recent years, an increase in the efficiency of health procedures without the loss of
 safety or quality is expected. An attempt to protocolize a remote preoperative evaluation
 (telephone call) has been made which patients undergoing low complexity procedures. However,
 the most important limiting factor in remote pre-anesthetic evaluation is the inability to
 perform the airway assessment properly. Although there are risk factors that can be detected
 with a medical history such as a previous record of a difficult airway, obstructive sleep
 apnea syndrome, hoarseness, dysphonia or obesity, the traditional evaluative predictive tests
 require the physical presence of the patient and are based on the physical examination of the
 patient such as thyroid-chin distance, cervical mobility, mouth opening and subluxation
 capacity, or the assessment of pharyngeal structures by the Mallampati test consisting of the
 direct visualization of the upper airway. However, no test can predict a difficult airway
 based on a single characteristic in the patient's absence.

 The combined evaluation of several risk factors obtains greater sensitivity than when
 analyzed in isolation. This is the case of the Arné Test, which consists of a multifactorial
 index that offers a sensitivity and specificity greater than 90% to predict a difficult
 airway when a score greater than or equal to 11 is obtained. In this context, new evaluation
 methods have appeared, such as ultrasound or other imaging tests, which intend to correlate
 the anatomical images of the airway with the presence of a difficult airway. But, the
 detection of a difficult airway depends not only on the morphology, but also on its
 functional characteristics. With the introduction of new technologies many attempts to
 develop other methods to predict a difficult airway such as facial recognition based on image
 processing have been made, however they have not succeeded yet. Other investigators propose
 the analysis of voice parameters as a reflection of anatomical and functional characteristics
 of the superior airway. Specifically, studies carried out in the field of maxillofacial
 surgery describe how the expansion of the maxilla affects the widening of the upper airway
 and, consequently, in the formation of the vowels and how this translates into a variation in
 the properties of the voice, such as frequency or amplitude. Accordingly, the investigators
 propose that voice characteristic analysis could reflect the airway's anatomy and be able to
 predict a difficult airway.

 Building on this, the investigators aim to develop a voice airway assessment method that
 replaces anthropometric parameters evaluated in traditional tests to predict a difficult
 airway, facilitating a remote airway evaluation.

 Voice recording will be made through a smart phone application to patients who are going to
 undergo general anesthesia and require orotracheal or nasotracheal intubation, by direct
 laryngoscopy, at the pre-anesthetic visit. The day of the surgical procedure, the result of
 the intubation - whether or not a difficult airway exists- will be registered.

 The records of the mobile application database will be downloaded, the voice signal will be
 processed, and parameters related to frequency, morphology and perturbation will be extracted
 employing Matlab® as these are considered continuous variables, to determine the statistical
 significance of the differences within parameters. The non-parametric test of
 Kolmogorov-Smirnov will be used for an easy and a difficult independent airway groups. Thus,
 these variables will be introduced into several classification algorithms obtained by
 combined methods using machine learning in order to predict the classification of patients
 according to the Cormack scale grade and sensitivity and specificity will be determined to
 assess their ability to predict a difficult airway. The area under the receiver operating
 characteristic curve will be used to assess the ability of the method to predict difficulty.

 The recruitment period will take place over a period of 12 months or until the estimated
 sample size is reached. The total duration of the study will be approximately 6 months years,
 ending with a total of 800 patients.
Inclusion Criteria:

 -  American Society of Anesthesiologists classification I-III

 -  Adults over 18 years

 -  Scheduled for intervention or surgical procedure in need of orotracheal or
 nasotracheal intubation by direct laryngoscopy

 -  Patients who have given their informed consent

 Exclusion Criteria:

 -  American Society of Anesthesiologists classification > III

 -  Minors

 -  Emergency procedures

 -  Patients who refuse to participate in the study.