Difficult intubation difficult intubation airway machine learning scoring system neural network random forest XGBoost
Conditions
Interventions
any intubation that required additional technical assistance including the use of advanced airway devices such as fiber-optic device, intubating laryngeal mask, or videolaryngoscopy, assistance from a
Screening,Screening
Difficult intubation,Not difficult intubation
Sponsors
none
Eligibility
Sex/Gender
All
Age
20 Years to 99 Years
Inclusion criteria
Inclusion criteria: Adult patients aged 20 years and above who underwent general anesthesia requiring oroendotracheal intubation performed with a Macintosh laryngoscope blade
Exclusion criteria
Exclusion criteria: Patients who were intubated before surgery, those with existing tracheostomy tubes, and cases in which intubation was performed using non-conventional techniques (e.g., videolaryngoscopy or fiberoptic intubation)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Difficult intubation After intubation successfully Difficult intubation | — |
Secondary
| Measure | Time frame |
|---|---|
| Scoring system after complete collecting data Scoring system to identify patients at risk of difficult intubation | — |
Countries
Thailand
Contacts
Public ContactAradchaporn Phetsirada
Prince of Songkla University
Outcome results
None listed