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CTRI Number  CTRI/2025/03/081842 [Registered on: 06/03/2025] Trial Registered Prospectively
Last Modified On: 05/03/2025
Post Graduate Thesis  No 
Type of Trial  Observational 
Type of Study   Cross Sectional Study 
Study Design  Single Arm Study 
Public Title of Study   Testing an AI System to Detect Tuberculosis Using Cough Sounds and Symptoms 
Scientific Title of Study   Diagnostic accuracy of an AI based screening system for detection of pulmonary tuberculosis using cough sounds and symptoms 
Trial Acronym  NIL 
Secondary IDs if Any  
Secondary ID  Identifier 
NIL  NIL 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Dr Neeraj Nischal 
Designation  Additional Professor 
Affiliation  Dept. of Medicine, AIIMS, New Delhi 
Address  Room No. 3092A, 3rd floor, Teaching Block Dept. of Medicine, AIIMS, Ansari Nagar, Ansari Nagar East, New Delhi

South West
DELHI
110029
India 
Phone  9811484060  
Fax    
Email  neerajnischal@gmail.com  
 
Details of Contact Person
Scientific Query  
Name  Dr Neeraj Nischal 
Designation  Additional Professor, Dept. of Medicine, AIIMS, New Delhi 
Affiliation  Dept. of Medicine, AIIMS, New Delhi 
Address  Room No. 3092A, 3rd floor, Teaching Block Dept. of Medicine, AIIMS, New Delhi Sri Aurobindo Marg, Ansari Nagar, Ansari Nagar East, New Delhi

South West
DELHI
110029
India 
Phone  9811484060  
Fax    
Email  neerajnischal@gmail.com  
 
Details of Contact Person
Public Query  
Name  Harsh Shukla 
Designation  Associate ML Scientist - II 
Affiliation  Wadhwani Institute for Artificial Intelligence 
Address  Wadhwani AI office, Okhla NSIC Metro Station building, Shambhu Dayal Bagh, Okhla.

South
DELHI
110020
India 
Phone  917895971030  
Fax    
Email  harsh@wadhwaniai.org  
 
Source of Monetary or Material Support  
AIIMS Delhi Ansari Nagar East New Delhi Delhi India 110016 AND Lords Education & Health Society 70 Ring Road 2nd floor Lajpat Nagar III New Delhi Delhi India 110024 
 
Primary Sponsor  
Name  AIIMS Delhi /Lords Education & Health Society 
Address  All India Institute of Medical Sciences, ANSARI NAGAR, NEW DELHI-110029, India  
Type of Sponsor  Government medical college 
 
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 
Dr Neeraj Nischal  All India Institute of Medical Sciences NEW DELHI, India  All India Institute of Medical Sciences ANSARI NAGAR, NEW DELHI-110029, India
South
DELHI 		 9811484060

neerajnischal@gmail.com 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Institute Ethics Committee, AIIMS New Delhi  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Patients  (1) ICD-10 Condition: A159||Respiratory tuberculosis unspecified,  
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  NIL  NIL 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  99.00 Year(s)
Gender  Both 
Details  Age greater than 18 years
Cough of any duration
Willing to give consent
 
 
ExclusionCriteria 
Details  Individuals less than 18 years of age
Patients unwilling to give consent
Patients requiring emergency management (clinically unstable)
Pregnant women, patients with pacemakers etc. among whom X-ray is prohibited
Patients currently on antitubercular therapy
 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
To evaluate the sensitivity, specificity, and accuracy of the AI solution in the detection of patients with TB, using cough sounds, comorbidity and symptom history  at 6 months and at 12 months (or till 126 confirmed TB positive patients are found; whichever is earlier) 
 
Secondary Outcome  
Outcome  TimePoints 
NIL  NIL 
 
Target Sample Size   Total Sample Size="1260"
Sample Size from India="1260" 
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)   18/03/2025 
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="1"
Months="0"
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 evaluate the diagnostic accuracy of an artificial intelligence (AI)-based screening system designed for the detection of pulmonary tuberculosis (TB) using cough sounds and related symptoms. TB remains a significant global health challenge, with 10.6 million new cases and 1.3 million deaths annually. Traditional diagnostic methods like microbiological tests and chest X-rays, though effective, are resource-intensive and often inaccessible in low-resource settings. This has led to significant gaps in the detection and treatment of TB, particularly in rural areas.

The AI model developed in this study uses cough sounds—a prominent symptom of TB—and additional symptoms such as fever, weight loss, and night sweats to provide a cost-effective and non-invasive diagnostic tool. The AI-powered mobile application offers rapid, point-of-care screening and can be utilized by frontline healthcare workers, enabling early diagnosis even in resource-limited environments. This technology addresses the need for accessible TB screening, aiming to bridge the gap between diagnosed and undiagnosed cases.
 
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