Videolaryngoscopic Difficult ıntubation and Glottic View Score: A Multicentre Prospective Study
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In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Airway Management. Basic parameters: 18 years — 100 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Turkey (Türkiye)
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Prediction of Difficult Videolaryngoscopic Intubation and Development of a Dedicated Glottic View Score: A Multicentre Prospective Study
Overview
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
Primary outcome measures
- Failed first intubation attempt [Time frame: 2 minutes after anesthesia induction]
- Difficult intubation [Time frame: 2 minutes after anesthesia induction]
- Failed intubation [Time frame: 2 minutes after anesthesia induction]
- Intubation duration [Time frame: 2 minutes after anesthesia induction]
- Glottic view description [Time frame: 2 minutes after anesthesia induction]
Secondary outcome measures (2)
- Percentil of glottic opening score [Time frame: 2 minutes after anesthesia induction]
- Cormack lehanne score [Time frame: 2 minutes after anesthesia induction]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
Turkey (Türkiye) · 2 centers
- Etlik City Hospital — Ankara
- Akdeniz University Medical Faculty — Antalya
Publications
- Xia M, Jin C, Zheng Y, Wang J, Zhao M, Cao S, Xu T, Pei B, Irwin MG, Lin Z, Jiang H. Deep learning-based facial analysis for predicting difficult videolaryngoscopy: a feasibility study. Anaesthesia. 2024 Apr;79(4):399-409. doi: 10.1111/anae.16194. Epub 2023 Dec 13. PMID 38093485
- O'Loughlin EJ, Swann AD, English JD, Ramadas R. Accuracy, intra- and inter-rater reliability of three scoring systems for the glottic view at videolaryngoscopy. Anaesthesia. 2017 Jul;72(7):835-839. doi: 10.1111/anae.13837. Epub 2017 Mar 24. PMID 28337769
Identifiers
NCT: NCT07355608 · Etlik City Hospital