Videolaryngoscopic Difficult ıntubation and Glottic View Score: A Multicentre Prospective Study (VIDIGLOV)

Prediction of Difficult Videolaryngoscopic Intubation and Development of a Dedicated Glottic View Score: A Multicentre Prospective Study

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Airway Management

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

• Study Type: Observational
• Enrollment (Estimated): 4977

Contacts and Locations

• Study Contact: Name: Dilek Yazıcıoğlu Ünal, Professor; Phone Number: +90 5336957855; Email: dilekunalmd@gmail.com
• Study Contact Backup: Name: Emel Gündüz, assoc.; Phone Number: +905444341719; Email: dregunduz@hotmail.com,

Study Locations

• Turkey (Türkiye)
  • Ankara, Turkey (Türkiye), 06170
    • Etlik City Hospital
    • Contact: Dilek Unal yazıcıoğlu, Professor; Phone Number: +905336957855; Email: dilekunalmd@gmail.com
    • Contact: Emel Gündüz; Phone Number: +905444341719; Email: drgunduz@hotmai.com
  • Antalya, Turkey (Türkiye)
    • Akdeniz University Medical Faculty

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Probability Sample

Study Population

Adults, both with normal or predicted difficult airways, undergoing orotracheal intubation with a videolarygoscope, for a case mix of surgeries

Description

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

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Glottic view description	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	2 minutes after anesthesia induction
Failed first intubation attempt	Failed to intubate at firtst attempt	2 minutes after anesthesia induction
Difficult intubation	Failed to intubate at 1-2 attempts and/or intubation duration longer than 120 second	2 minutes after anesthesia induction
Failed intubation	Not able to intubate the patient	2 minutes after anesthesia induction
Intubation duration	Time elapsed from entring the blade between the teeth to detecting an entidal carbondioxide trace	2 minutes after anesthesia induction

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Percentil of glottic opening score	the percentage of glottic opening seen, defined by the linear span from the anterior commissure to the inter-arytenoid notch	2 minutes after anesthesia induction
Cormack lehanne score	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	2 minutes after anesthesia induction

Collaborators and Investigators

• Sponsor: Diskapi Teaching and Research Hospital
• Investigators: Principal Investigator: Dilek Yazıcıoğlu Ünal, professor, Ankara Etlik City Hospital

Publications and helpful links

General 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Estimated): February 1, 2026
• Primary Completion (Estimated): February 1, 2027
• Study Completion (Estimated): February 1, 2027

Study Registration Dates

• First Submitted: December 2, 2025
• First Submitted That Met QC Criteria: January 14, 2026
• First Posted (Actual): January 21, 2026

Study Record Updates

• Last Update Posted (Actual): February 5, 2026
• Last Update Submitted That Met QC Criteria: February 3, 2026
• Last Verified: January 1, 2026

More Information

Terms related to this study

• Keywords: Airway management; Videolaryngoscope; Difficult airway
• Other Study ID Numbers: Etlik City Hospital

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No