Patients aged 18 years or older who undergoing elective surgery requiring endotracheal anesthesia and no definite risk of difficult intubation characteristic Intubation, Intratracheal, Difficult Intubation, Airway Management Head / Neck / Neck Anatomy, Regional Laryngoscopy, Artificial Intelligence, Machine Learning, Deep Learning, Predictive Value of Tests Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted
Conditions
Interventions
Sponsors
Sujaree Poopipatpab
Eligibility
Sex/Gender
All
Age
18 Years to No maximum
Inclusion criteria
Inclusion criteria: 1. Patients aged 18 years or older 2. Patients undergoing elective surgery requiring endotracheal anesthesia
Exclusion criteria
Exclusion criteria: 1. Patients who are uncooperative 2. Patients who decline to participate in the study 3. Patients with characteristics that inherently make endotracheal intubation difficult, such as absence of upper incisors, inability to fully open the mouth, a history of cervical spine or facial surgery, or deformities of the head, face, or neck 4. Patients with a history of cervical spine surgery or facial surgery 5. Patients who have undergone open-heart surgery 6. Pregnant patients 7. Patients with a BMI > 40 (morbid obesity)
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Predicted Laryngeal view from AI study At surgical day Grade of Laryngeal view | — |
Secondary
| Measure | Time frame |
|---|---|
| Accuracy of conventional method airway evaluation At surgical day Conventional airway parameter | — |
Countries
Thailand
Contacts
Public ContactPoramed Amorntodsapornpong
FACULTY OF MEDICINE VAJIRA HOSPITAL
Outcome results
None listed