| CTRI Number |
CTRI/2023/11/059976 [Registered on: 17/11/2023] Trial Registered Prospectively |
| Last Modified On: |
09/11/2023 |
| Post Graduate Thesis |
Yes |
| Type of Trial |
Observational |
|
Type of Study
|
Cross Sectional Study |
| Study Design |
Other |
|
Public Title of Study
|
A study on comparing the accuracy of conventional predictors vs artificial intelligence in predicting difficult intubation in anaesthesia |
|
Scientific Title of Study
|
A study on comparing the accuracy of conventional predictor model versus artificial intelligence in predicting difficult intubation in anaesthesia |
| 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
Amala institute of medical sciences
Department of Anaesthesia
Chavara block
Thrissur
Thrissur
KERALA
680555
India |
| Phone |
09562934551 |
| Fax |
|
| Email |
kukku.j@yahoo.com |
|
Details of Contact Person
Scientific Query
|
| Name |
Dr. Mithun Raju P |
| Designation |
Associate Professor |
| Affiliation |
Amala institute of medical sciences |
| Address |
Associate Professor
Department of Anaesthesia
Chavara block
Amala institute of medical sciences
Thrissur
Thrissur
KERALA
680555
India |
| Phone |
9961738780 |
| Fax |
|
| Email |
mithunraju@hotmail.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
Chavara block
Amala institute of medical sciences
Thrissur
Thrissur
KERALA
680555
India |
| Phone |
09562934551 |
| Fax |
|
| Email |
kukku.j@yahoo.com |
|
|
Source of Monetary or Material Support
|
| Amala institute of medical sciences, Thrissur, Kerala |
|
|
Primary Sponsor
|
| Name |
Shahana Muneer |
| Address |
Junior resident
Amala Institute of medical sciences
Thrissur
Kerala |
| Type of Sponsor |
Other [Self] |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| Dr Shahana Muneer |
Amala Institute of Medical Sciences |
Department of anesthesiology
Thrissur
Kerala
Thrissur
KERALA |
9562934551
kukku.j@yahoo.com |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| Ethics committee , Amala Institute of medical sciences |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: O||Medical and Surgical, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Comparator Agent |
Nil |
Nil |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
80.00 Year(s) |
| Gender |
Both |
| Details |
ASA 1,2 and 3 |
|
| ExclusionCriteria |
| Details |
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 |
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| to assess the accuracy of conventional predictor model and artificial intelligence in predicting difficult airway |
18 months |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
| To compare conventional model & artificial intelligence in prediction of difficult intubation |
18 months |
|
|
Target Sample Size
|
Total Sample Size="793"
Sample Size from India="793"
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)
|
21/11/2023 |
| 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="1"
Months="6"
Days="0" |
|
Recruitment Status of Trial (Global)
|
Not Applicable |
| 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 assess the accuracy of conventional predictor model of difficult airway prediction (including parameters like BMI , neck circumference, thyromental distance, interincisor gap, mallampatti classification, age and head and neck movements) and artificial intelligence model using random forest classifier. 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. |