Airway Management
Conditions
Keywords
Airway management, Videolaryngoscope, Difficult airway
Brief summary
Background: Videolaryngoscopy has improved glottic visualization and facilitated tracheal intubation. However, difficulties-including failed intubation-still occur. At present, no prospectively derived classification system exists to assess the difficulty of videolaryngoscopic (VL) intubation across both normal and anticipated difficult airways. Additionally, current glottic view grading systems, designed for direct laryngoscopy, may not adequately capture the specific challenges of VL intubation. Objectives: This study aims to: 1. Develop a predictive model for difficult VL intubation in surgical patients with both normal and anticipated difficult airways. 2. Create a glottic view scoring system specifically tailored to videolaryngoscopy. 3. Compare the predictive accuracy of the new scoring system with existing laryngeal view grades in forecasting difficult VL intubation.
Detailed description
Background: Videolaryngoscopy has improved glottic visualization and facilitated tracheal intubation. However, difficulties-including failed intubation-still occur. At present, no prospectively derived classification system exists to assess the difficulty of videolaryngoscopic (VL) intubation across both normal and anticipated difficult airways. Additionally, current glottic view grading systems, designed for direct laryngoscopy, may not adequately capture the specific challenges of VL intubation. Objectives: This study aims to: 1. Develop a predictive model for difficult VL intubation in surgical patients with both normal and anticipated difficult airways. 2. Create a glottic view scoring system specifically tailored to videolaryngoscopy. 3. Compare the predictive accuracy of the new scoring system with existing laryngeal view grades in forecasting difficult VL intubation. Methods: A prospective cohort of 4,977 patients will be enrolled. Patient and intubation related variables-including VL findings, airway features, clinical parameters, device, and procedural details-will be analyzed. Binary logistic regression will be employed to build the initial predictive model. In parallel, machine learning techniques (Random Forest, Support Vector Machine, XGBoost, LightGBM, etc.) will be applied to evaluate predictive performance. Comparative analysis will be conducted between the machine learning models and the logistic regression baseline. Expected Impact: The development of a robust predictive tool and an associated VL-specific glottic view score could enhance clinical decision making, particularly in identifying patients at risk of difficult or failed VL intubation. This may support early consideration of awake tracheal intubation, and use of standardized terminology and reduce complications associated with difficult airway management
Interventions
None listed
Sponsors
Diskapi Teaching and Research Hospital
Study design
Observational model
OTHER
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 100 Years
Healthy volunteers
No
Inclusion criteria
* Adults * Both with normal or predicted difficult airways * Undergoing orotracheal intubation with a videolarygoscope
Exclusion criteria
* Rapid sequence intubation * Double lumen tube intubation
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Failed first intubation attempt | 2 minutes after anesthesia induction | Failed to intubate at firtst attempt |
| Failed intubation | 2 minutes after anesthesia induction | Not able to intubate the patient |
| Intubation duration | 2 minutes after anesthesia induction | Time elapsed from entring the blade between the teeth to detecting an entidal carbondioxide trace |
| Glottic view description | 2 minutes after anesthesia induction | Vocal cords are fully visible Vocal cords are partially separately Vocal cords are not visible Cords are adducted Epiglottis is visible Epiglottis is large Epiglottis is small Epiglottis is edematous Epiglottis mass is present Arytenoids are visible Arytenoid luxation or subluxation Arytenoid edema Valecula problem (edema, Coffee grounds, etc., unable to insert a blade) Aryepiglottic plica pathology (edema, Coffee grounds scar) Laryngeal structures should be formed Glottic stenosis Laryngospasm |
| Difficult intubation | 2 minutes after anesthesia induction | Failed to intubate at 1-2 attempts and/or intubation duration longer than 120 second |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Percentil of glottic opening score | 2 minutes after anesthesia induction | the percentage of glottic opening seen, defined by the linear span from the anterior commissure to the inter-arytenoid notch |
| Cormack lehanne score | 2 minutes after anesthesia induction | grade 1 being a full view of the glottis, grade 2 being a partial view, grade 3 being only a view of the epiglottis, and grade 4 being an absent view of the glottis and epiglottis |
Countries
Turkey (Türkiye)
Contacts
CONTACTDilek Yazıcıoğlu Ünal, Professor
CONTACTEmel Gündüz, assoc.
PRINCIPAL_INVESTIGATORDilek Yazıcıoğlu Ünal, professor
Ankara Etlik City Hospital
Outcome results
None listed