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CTRI Number  CTRI/2025/12/098666 [Registered on: 08/12/2025] Trial Registered Prospectively
Last Modified On: 27/11/2025
Post Graduate Thesis  No 
Type of Trial  Observational 
Type of Study   Cross Sectional Study 
Study Design  Other 
Public Title of Study   A Comparative Study of Machine-Learning Tools for Difficult Airway Prediction in anesthesia 
Scientific Title of Study   A study on comparative evaluation of machine learning algorithms for predicting difficult airways 
Trial Acronym  NIL 
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Shahana Muneer 
Designation  Junior Resident  
Affiliation  Amala institute of medical sciences  
Address  Junior resident Department of Anaesthesia Amala institute of medical sciences Thrissur Kerala

Thrissur
KERALA
680555
India 
Phone  09562934551  
Fax    
Email  kukku.j@yahoo.com  
 
Details of Contact Person
Scientific Query  
Name  Shahana Muneer 
Designation  Junior Resident  
Affiliation  Amala institute of medical sciences  
Address  Junior resident Department of Anaesthesia Amala institute of medical sciences Thrissur Kerala

Thrissur
KERALA
680555
India 
Phone  09562934551  
Fax    
Email  kukku.j@yahoo.com  
 
Details of Contact Person
Public Query  
Name  Shahana Muneer 
Designation  Junior Resident  
Affiliation  Amala institute of medical sciences  
Address  Junior resident Department of Anaesthesia Amala institute of medical sciences Thrissur Kerala

Thrissur
KERALA
680555
India 
Phone  09562934551  
Fax    
Email  kukku.j@yahoo.com  
 
Source of Monetary or Material Support  
nil 
 
Primary Sponsor  
Name  Shahana Muneer  
Address  Junior resident Department of Anaesthesia Amala institute of medical sciences Thrissur  
Type of Sponsor  Other [Self] 
 
Details of Secondary Sponsor  
Name  Address 
NIL  NIL 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 1  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Shahana Muneer   Amala institute of medical sciences   Department of anesthesiology Amala nagar Thrissur Kerala
Thrissur
KERALA 		 09562934551

kukku.j@yahoo.com 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
IEC AMALA INSTITUTE OF MEDICAL SCIENCES  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Patients  (1) ICD-10 Condition: O||Medical and Surgical,  
 
Intervention / Comparator Agent  
Type  Name  Details 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  80.00 Year(s)
Gender  Both 
Details  1. Surgical procedures requiring endotracheal intubation using the Macintosh blade
2. Age : 18-80years
3. ASA I,II, III
 
 
ExclusionCriteria 
Details  1. Developmental anomalies which may affect airway assessment
2. Patients with airway malformations, midline neck swelling, face trauma or other gross external head and neck deformities
3. Psychiatric patients or patients who are unable to follow commands
 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
1. To compare the predictive performance of various machine learning algorithms in identifying difficult airway cases.  3months 
 
Secondary Outcome  
Outcome  TimePoints 
2. To determine the most clinically useful machine learning model for potential integration into preoperative airway assessment workflows.  3 months 
3. To identify the optimal subset or combination of predictors that yields the highest predictive accuracy for each machine learning algorithm.  3 months 
 
Target Sample Size   Total Sample Size="697"
Sample Size from India="697" 
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" 
Phase of Trial   N/A 
Date of First Enrollment (India)   10/12/2025 
Date of Study Completion (India) Applicable only for Completed/Terminated trials 
Date of First Enrollment (Global)  Date Missing 
Date of Study Completion (Global) Applicable only for Completed/Terminated trials 
Estimated Duration of Trial   Years="0"
Months="3"
Days="0" 
Recruitment Status of Trial (Global)   Not Yet Recruiting 
Recruitment Status of Trial (India)  Not Yet Recruiting 
Publication Details   N/A 
Individual Participant Data (IPD) Sharing Statement

Will individual participant data (IPD) be shared publicly (including data dictionaries)?  

Response - NO
Brief Summary   This study aims to compare different machine learning algorithms in difficult airway prediction (including parameters like BMI , neck circumference, thyromental distance, interincisor gap, mallampatti classification, age  and head and neck movements). Using a Macintosh blade of size 3 or 4 , laryngoscopy will be done and vocal cord is graded according to cormack lehane grading. Grades 1 and 2 are considered as easy and 3 and 4 as difficult airways. Five algorithms are systematically compared: Random Forest (RF), Gradient Boosting (GB),  XGBoost , Deep Learning (DL) neural network and a Stacking Ensemble combining base models’ predictions.  
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