CTRI Number	CTRI/2021/09/036609 [Registered on: 17/09/2021] Trial Registered Prospectively
Last Modified On:	09/03/2022
Post Graduate Thesis	No
Type of Trial	Observational
Type of Study	Cross Sectional Study
Study Design	Other
Public Title of Study	Device validation study for detecting likely presnce of Pulmonary Tuberculosis
Scientific Title of Study Modification(s)	Swaasa Artificial Intelligence Platform for detecting likely presence of Pulmonary Tuberculosis
Secondary IDs if Any	Secondary ID  Registry  NIL  NIL
Details of Principal Investigator or overall Trial Coordinator (multi-center study)	Name  Dr P V Sudhakar  Address  Andhra Medical College, Visakhapatnam Visakhapatnam ANDHRA PRADESH 530002 India  Phone  08912561157   Fax     Email  amc_vsp@nic.in
Details Contact Person Scientific Query	Name  Dr Gayatri Devi  Address  Government Chest Hospital, Andhra Medical college, Visakhapatnam Andhra Medical College Visakhapatnam ANDHRA PRADESH 530002 India  Phone  8688546233   Fax     Email  gayatriyellapu@gmail.com
Details Contact Person Public Query Modification(s)	Name  Narayana Rao Sripada  Address  FLAT NO 408,DREAM CASTLE NIZAMPET ROAD, KUKATPALLY Medchal TELANGANA 500090 India  Phone  9945399533   Fax     Email  svn@salcit.in
Source of Monetary or Material Support	Cellular and Molecular Platforms
Primary Sponsor	Name  Cellular and Molecular Platforms   Address  GKVK Post, Bellary Road, Bengaluru, Karnataka 560 065   Type of Sponsor  Research institution
Details of Secondary Sponsor	Name  Address  NIL  NIL
Countries of Recruitment	India
Sites of Study Modification(s)	No of Sites = 1   Contact Person  Name of Site  Site Address  Phone/Fax/Email  Dr Gayatri Devi  King George Hospital  NTEP Center, KGH, Andhra Medical College, Visakhapatnam Visakhapatnam   8688546233 gayatriyellapu@gmail.com
Details of Ethics Committee	No of Ethics Committees= 1   Name of Committee  Approval Status  Institutional Ethics Committe, King George Hospital, Visakhapatname,   Approved
Regulatory Clearance Status from DCGI	Status  Not Applicable
Health Condition / Problems Studied	Health Type  Condition  Patients  Respiratory tuberculosis unspecified  Healthy Human Volunteers  Subjects not having any respiratory symptoms
Intervention / Comparator Agent	Type  Name  Details
Inclusion Criteria Modification(s)	Age From  18.00 Year(s) Age To  99.00 Year(s) Gender  Both  Details  Male or female patients, 18 years of age and over Patients who are willing to participate in the study. Able to read understand and sign the Informed Consent Form
ExclusionCriteria	Details  Patients less than 18 years of age Pregnant females. Presumptive PTB patients with coexisting other respiratory diseases like COPD, Bronchiectasis, ILDs Who are not willing to participate in the study
Method of Generating Random Sequence	Not Applicable
Method of Concealment	Not Applicable
Blinding/Masking	Not Applicable
Primary Outcome	Outcome  TimePoints  Validation of the SWAASA AI Platform in detecting likely presence of PTB by comparing with the final clinical diagnosis based on test results of a standard reference test or tests.  5 months
Secondary Outcome	Outcome  TimePoints  Evaluate the effectiveness of Swaasa AI platform in detecting PTB in a primary health care setting  2 months
Target Sample Size	Total Sample Size="200" Sample Size from India="200"
Phase of Trial	N/A
Date of First Enrollment (India)	22/09/2021
Date of First Enrollment (Global)	No Date Specified
Estimated Duration of Trial	Years="0" Months="7" Days="0"
Recruitment Status of Trial (Global) Modification(s)	Not Applicable
Recruitment Status of Trial (India)	Completed
Publication Details	Not applicable yet
Brief Summary	Artificial intelligent techniques such as Bayesian networks, artificial neural networks, and hybrid intelligent systems were used in different clinical settings in health care. In 2016, the biggest chunk of investments in AI research were in healthcare applications compared with other sectors. AI in medical field has wider applications like diagnosis of diseases, clinical decision support tools ,drug developments, precision medicine, robotic surgeries and improve gene editing by Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) system.  In AI Computers learn the art of diagnosing a patient via two broad techniques - flowcharts and database approach. The database approach utilizes the principle of deep learning or pattern recognition (images, data etc) that involves teaching a computer via repetitive algorithms in recognizing with certain groups of symptoms or certain clinical/radiological images look like.  In the field of respiratory medicine also exploratory research is going on using AI-ML like bronchoscopic Image analysis for early diagnosis of cancers. Convolutional neural networks (CNNs) are specialized ML methods, excelling at imaging analysis, which may support assessment of respiratory disease on chest X-ray or CT scan.  Literature search also revealed work on audiometric analysis of cough sounds to differentiate pattern/type of respiratory disease. Recently using AI platform called SWAASA, SALICIT company in collaboration with Apollo hospital Hyderabad did clinical validation work on “Cough sound analysis and objective correlation with spirometry and clinical diagnosis” with the main objective of distinguishing cough patterns in different respiratory diseases. Cough is the most common symptom of several respiratory diseases. Cough may be dry or associated with sputum production. We have certain cough patterns like bovine cough, brassy cough depending on the cough characteristics. Though the mechanism of cough generation is same, the origin and the underlying pathological process give the cough different characteristics. Based on this rationale audiometric analysis of cough may give a clue to the type of or sometimes etiology of the respiratory disease. Now we are trying to develop cough signature for the most common and endemic respiratory disease PTB by audiometric analysis using, SWAASA AI platform.