A study on comparing the accuracy of conventional predictors vs artificial intelligence in predicting difficult intubation in anaesthesia
Not Applicable
- Conditions
- Health Condition 1: O- Medical and Surgical
- Registration Number
- CTRI/2023/11/059976
- Lead Sponsor
- Shahana Muneer
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ot Yet Recruiting
- Sex
- Not specified
- Target Recruitment
- 0
Inclusion Criteria
ASA 1,2 and 3
Exclusion Criteria
1. Developmental anomalies which may affect airway assessment
2. Patients with airway malformations, midline neck swellings, face trauma or other gross external head and neck deformities
3. Psychiatric patients who are unable to follow commands
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method to assess the accuracy of conventional predictor model and artificial intelligence in predicting difficult airwayTimepoint: 18 months
- Secondary Outcome Measures
Name Time Method To compare conventional model & artificial intelligence in prediction of difficult intubationTimepoint: 18 months