Difficult Airway and Difficult Intubation Incidence in Patients Undergoing Cardiovascular Surgery and a Prediction Model Development

Not yet recruiting

• Conditions: Difficult Airway Intubation; Difficult Airway; Difficult Intubation; Cardiac Surgery; Cardiac Surgery in Adult Patient

• Registration Number: NCT06986187
• Lead Sponsor: Diskapi Teaching and Research Hospital

Brief Summary

A difficult airway is a clinical condition that occurs when one or more of the components of difficult mask ventilation, difficult laryngoscopy, difficult endotracheal intubation, difficult supraglottic airway device (SGA) placement, and inability to intubate-oxygenate are present. Data concerning incidence of difficult airway in patients undergoing cardiovascular surgery is controversial. Unwanted hemodynamic changes that may occur in patients undergoing cardiovascular surgery, combined with hemodynamic changes caused by underlying cardiac pathologies, may also lead to a physiologically difficult airway situation. Since all these interactions, combined with the hemodynamic changes caused by difficult airway interventions, may lead to catastrophic outcomes, it is vital to predict difficult airway in this patient population.

Detailed Description

Difficult airway is a clinical condition that occurs when one or more of the components of difficult mask ventilation, difficult laryngoscopy, difficult endotracheal intubation, difficult supraglottic airway device (SGA) placement, and inability to intubate-oxygenate are present.

Different diagnostic criteria for all components of difficult airway and similarly different predictive criteria for the risk of occurrence in a patient have been defined. The LEMON Score, El-Ganzouri Risk Index, and Arne Score, which are evaluated by physical examination of the upper airway structures during the pre-anesthetic examination, and the Cormack-Lehane Classification (CL) used to evaluate the laryngoscopic image during intubation, can be counted among the difficult airway prediction tests.

Difficult airway situations that occur during anesthesia application can be defined by the Han Score for mask ventilation, the Intubation Difficulty Scale (IDS) for endotracheal entubation, the videolaryngoscopic intubation and difficult airway classification (VIDIAC) in patients using videolaryngoscopy, and the difficult SGA placement score.

Previous studies have reported that the incidence of difficult airway is higher in patients undergoing cardiovascular surgery compared to other patient groups. Borde et al. reported the rate of difficult intubation in patients undergoing cardiac surgery as 24%. The rate of difficult laryngoscopy in patients undergoing coronary artery surgery was reported as 10% by Ezri et al. and 7% by Heinrich et al. However, it is seen that the predictive criteria and diagnostic criteria for the components of the difficult airway are used interchangeably and incorrectly in these studies. Therefore, the current information on the incidence of difficult airways in patients undergoing cardiovascular surgery is contradictory and open to debate.

Accurate information on the incidence of difficult airway in this patient population can contribute to anesthesiology education, equipment and personnel planning, and most importantly, patient safety. Unwanted hemodynamic changes that may occur following anesthesia induction in patients undergoing cardiovascular surgery, combined with hemodynamic changes caused by underlying cardiac pathologies, may lead to the emergence of a physiological difficult airway condition. Since all these interactions, when combined with hemodynamic changes caused by difficult airway interventions, may lead to catastrophic outcomes, predicting difficult airway in this patient population is of vital importance.

Despite its clinical importance, to our knowledge, this subject has not yet been investigated in the literature with artificial intelligence algorithms.

The aim of this study is to investigate the incidence of difficult airway and difficult intubation in patients undergoing cardiovascular surgery and the associated factors and to develop a machine learning model that can predict difficult airway using artificial intelligence algorithms.

Study Timeline

• Status Verified: 2025-05
• Study First Submitted: 2025-05-15
• Study First Submitted QC: 2025-05-15
• Last Update Submitted: 2025-05-15
• Study First Posted: 2025-05-22
• Last Update Posted: 2025-05-22
• Study Start: 2025-06-01
• Primary Completion: 2027-06-01
• Study Completion: 2027-12-01

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 2000

Inclusion Criteria

• Undergoing cardiovascular surgery
• ASA I-IV physical status
• Over 18 years of age

Exclusion Criteria

• Known difficult airway
• Head-neck and upper airway pathology
• Patients at risk of aspiration

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Intubation difficulty	5 minutes after anesthesia induction	Intubation difficulty is defined with the intubation difficulty scale score (IDS) and a score greater or equal to 5 is difficult intubation

Secondary Outcome Measures

Name	Time	Method
Dificult mask ventilation	5 minutes after anesthesia induction	Difficult mask ventilation is defined by Han scale score, a grade greater or equal to 1 is difficult mask ventilation
Laringeal view score	5 minutes after anesthesia induction	Cormack lehanne score will be used , a score greater or equal to 2b is considered predictive of difficult airway
LEMON score	preoperative day	LEMON score: external assessment; mouth opening \<5 cm; thyromental distance \<6 cm; Mallampati class; obstruction; neck movement: 1 point each and \>10 points at risk of difficult airway

Trial Locations

Locations (1)

Etlik City Hospital; 🇹🇷 Ankara, Turkey