The Voice Analysis as a Preoperative Prediction Method of a Difficult Airway

NCT04259021 | Completed

• 1 other identifier: DEX-ANE-2019-001
• Study Type: observational
• Target: 722
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Difficult or Failed Intubation; Voice; Laryngoscopy

Keywords

difficult air way, pre-anesthetic evaluation, voice analysis

Outcome Measures

Primary Outcomes (11)

• Difficult Airway Criteria (through Arne Test)

  Arne Test assessment evaluates different parameters giving a punctuation depending on the selected level. If the total score is higher than 11 points, the airway is predicted to be a difficult tracheal intubation. Parameters of the scale: Distance between incisors (\> 5cm, 3.5-5cm, ≤ 3.5cm), Mandibular subluxation (Normal, moderate restriction, severe restriction), Thyromental distance (\> 6.5cm ≤ 6.5cm), Neck movement range (\> 100º, 90º, \<80º), Mallampati (I, II, III, IV), Total Arné Test score (if greater than 11, considered difficult airway).

  Baseline

• Voice power spectrum

  Power description of the different vocals within the voice record of the patient. Power is calculated using the spectrogram that uses the Fourier transformation. Spectrogram shows the power in decibel of the signal within a time-window and through different frequency intervals.

  Baseline

• Voice pitch frequency

  Pitch frequency is defined as the number of oscillations of the vocal cords per second. Calculation is made using the glottic pulses. Pitch frequency is the mean of all the pulses from the analysed signal.

  Baseline

• Voice formants

  Formants constitute the transference function of the vocal tract. Voice formant are a group of frequencies characterized by its central frequency, bandwidth and energy. They are extracted from the Fourier Transform.

  Baseline

• Voice harmonics

  Parameters that depend on the pronounced vocal and the vocal tract morphology. Vocal harmonics are the resonances produced by the vocal tract. They are calculated detecting the peaks of the Fourier Transformation.

  Baseline

• Jitter measurements

  Jitter measures the increase of perturbations of the voice frequency cycle per cycle. There are four variants, depending on the number of analysed cycles.

  Baseline

• Shimmer measurements

  Shimmer measures the increase of perturbations of the voice amplitude cycle per cycle. There are four variants, depending on the number of analysed cycles.

  Baseline

• Harmonic to noise ratio

  Harmonic to noise ratio is the relation of the energy of harmonics compared to the energy considered noise. It is a parameter to determine the voice purity.

  Baseline

• Voice Turbulence Index

  Voice turbulence index measures the relation of the high-frequency energy (2.5kHz-5.8kHz) to the low-frequency energy (50Hz-2.5kHz) within the voice signal.

  Baseline

• Normalized Noise Energy

  Normalized Noise energy measures the noise in the voice signal caused by incomplete closure of the glottis due to the presence of pathologies in the phonation apparatus. It is the relation between the noise power and the total signal power .

  Baseline

• Intubation process

  To analyse the intubation process the next categorical variables are collected: Cormack-Lehane scale grade (I, II, III, IV) that determines the visible structures of the larynx when direct intubation. Type of maneuver (single, repeated or imposible) to determine the number of times intubation is performed. Device used to determine if the intubation is performed through direct laryngoscopy or a device has been used.

  Baseline

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Patients who will undergo general anesthesia by orotracheal or nasotracheal intubation

You may qualify if:

• 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

You may not qualify if:

• American Society of Anesthesiologists classification \> III
• Minors
• Emergency procedures
• Patients who refuse to participate in the study.

Sponsors & Collaborators

• Fundacion Dexeus: lead

Study Sites (1)

Hospital Universitario Dexeus

Barcelona, 08028, Spain

Location

Related Publications (4)

• de Carvalho CC, da Silva DM, de Carvalho Junior AD, Santos Neto JM, Rio BR, Neto CN, de Orange FA. Pre-operative voice evaluation as a hypothetical predictor of difficult laryngoscopy. Anaesthesia. 2019 Sep;74(9):1147-1152. doi: 10.1111/anae.14732. Epub 2019 Jun 11.

  PMID: 31183861 RESULT

• Apfelbaum JL, Hagberg CA, Caplan RA, Blitt CD, Connis RT, Nickinovich DG, Hagberg CA, Caplan RA, Benumof JL, Berry FA, Blitt CD, Bode RH, Cheney FW, Connis RT, Guidry OF, Nickinovich DG, Ovassapian A; American Society of Anesthesiologists Task Force on Management of the Difficult Airway. Practice guidelines for management of the difficult airway: an updated report by the American Society of Anesthesiologists Task Force on Management of the Difficult Airway. Anesthesiology. 2013 Feb;118(2):251-70. doi: 10.1097/ALN.0b013e31827773b2. No abstract available.

  PMID: 23364566 RESULT

• Lebacq J, Schoentgen J, Cantarella G, Bruss FT, Manfredi C, DeJonckere P. Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research. J Voice. 2017 Sep;31(5):550-556. doi: 10.1016/j.jvoice.2017.02.017. Epub 2017 Mar 18.

  PMID: 28320627 RESULT

• Tsanas A, Little MA, McSharry PE, Spielman J, Ramig LO. Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease. IEEE Trans Biomed Eng. 2012 May;59(5):1264-71. doi: 10.1109/TBME.2012.2183367. Epub 2012 Jan 9.

  PMID: 22249592 RESULT

Study Officials

• Claudia Rodiera, M.D.

  Fundacion Dexeus

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 17, 2019
• First Posted: February 6, 2020
• Study Start: March 1, 2020
• Primary Completion: September 1, 2022
• Study Completion: September 1, 2022
• Last Updated: September 28, 2023

Record last verified: 2023-09

Locations

ES (1)