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CTRI Number  CTRI/2025/12/098910 [Registered on: 11/12/2025] Trial Registered Prospectively
Last Modified On: 10/12/2025
Post Graduate Thesis  No 
Type of Trial  Observational 
Type of Study   Multi-Center Prospective Validation Study 
Study Design  Other 
Public Title of Study   Evaluation of ECG-AI Device Performance Using Multiple ECG Devices 
Scientific Title of Study   A multicenter study to demonstrate compatibility of ECG-AI acress 12-Lead ECG devices 
Trial Acronym  Nil 
Secondary IDs if Any  
Secondary ID  Identifier 
DOC-3295, Version 00, Date 20 Nov 2025  Protocol Number 
 
Details of Principal Investigator or overall Trial Coordinator (multi-center study)  
Name  Dr Santosh Saklecha 
Designation  Consultant Doctor 
Affiliation  Santosh Hospital 
Address  Department of Internal Medicine, Room No.4, 6/1, Near Coals Park, Promenade Road, Pulikeshi Nagar, Frazer Town

Bangalore
KARNATAKA
560005
India 
Phone  8040848888  
Fax    
Email  sh@santoshhealthcare.com   
 
Details of Contact Person
Scientific Query  
Name  Dr Bhargav Bhongiri 
Designation  Head Medical Writer 
Affiliation  Syncorp Health Pvt. Ltd.  
Address  Room No.6,3rd Floor, second Main Road, sarvobhaogam Nagar, Arekere.

Bangalore
KARNATAKA
560076
India 
Phone  9000518175  
Fax    
Email  bhargav.b@syncorphealth.com  
 
Details of Contact Person
Public Query  
Name  Dr Bhargav Bhongiri 
Designation  Head Medical Writer 
Affiliation  Syncorp Health Pvt. Ltd.  
Address  Room No.6,3rd Floor, second Main Road, sarvobhaogam Nagar, Arekere.

Bangalore
KARNATAKA
560076
India 
Phone  9000518175  
Fax    
Email  bhargav.b@syncorphealth.com  
 
Source of Monetary or Material Support  
Anumana Inc.One Main Street, Suite 400 East Arcade, 4th Floor Cambridge, MA 02142,United States 
 
Primary Sponsor  
Name  Anumana Inc. 
Address  One Main Street, Suite 400 East Arcade, 4th Floor Cambridge, MA 02142,United States 
Type of Sponsor  Other [Health-technology company] 
 
Details of Secondary Sponsor  
Name  Address 
NIL  NIL 
 
Countries of Recruitment     India  
Sites of Study  
No of Sites = 2  
Name of Principal Investigator  Name of Site  Site Address  Phone/Fax/Email 
Dr Meghana Murthy  Narayana Super Speciality Hospital  Department of General Medicine, Room No-7, 6-8,18th Cross,4th main,Malleswaram west.
Bangalore
KARNATAKA 		 81519 94080

meggydoc@gmail.com  
Dr Santosh Saklecha  Santosh Hospital  Department of Internal Medicine, Room No.4, 6/1, Near Coals Park, Promenade Road, Pulikeshi Nagar, Frazer Town
Bangalore
KARNATAKA 		 9014308214

ssaklecha@gmail.com 
 
Details of Ethics Committee  
No of Ethics Committees= 2  
Name of Committee  Approval Status 
Santosh Hospital-Institutional Ethics Committee   Approved 
Vagus Institutional Ethics Committee  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Healthy Human Volunteers  Adult subjects (age 18 or older) undergoing standard clinical care will be recruited 
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  Nil  Nil 
Intervention  Nil  Nil 
Intervention  Nil  Nil 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  75.00 Year(s)
Gender  Both 
Details  1. Adult subjects (age 18 or older)  
 
ExclusionCriteria 
Details  1. No subject consent obtained
2. Open chest wounds or recent surgery to the chest or abdomen (less than 30 days)
3. Absence of any limb that would require modification of standard lead placement  
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
1. Mean absolute error in AI scores (continuous) between pairs of native ECGs.
2. Mean absolute error in AI scores (continuous) between native and transformed ECGs.  		 Baseline Vist 1 
 
Secondary Outcome  
Outcome  TimePoints 
MAE & cross-correlation between pairs of native ECGs  Baseline visit 1 
MAE & cross-correlation between native ECGs & transformed ECGs.  Baseline visit 1 
Concordance of AI binary outputs (sensitivity, specificity) between pairs of native ECGs
against Echo-derived or clinical history labels.  		 Baseline visit 1 
Concordance of AI binary outputs (sensitivity, specificity) between native & transformed
ECGs against Echo-derived or clinical history labels. 		 Baseline visit 1 
 
Target Sample Size   Total Sample Size="1000"
Sample Size from India="1000" 
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)   19/01/2026 
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="4"
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   Electrocardiograms (ECGs) are among the most widely performed diagnostic tests in medicine due to their affordability, accessibility, and utility in detecting cardiovascular disease. However, the diversity of ECG hardware across manufacturers introduces the potential for device-specific variability in signal characteristics, which could affect the performance of downstream ECG-based artificial intelligence (ECG-AI) algorithms. Despite the high sensitivity and specificity of some ECG-AI tools, their clinical applicability may be limited by lack of generalizability across devices. To study the extent of this limitation, we aim to compare the output of multiple ECG-AI models across a range of ECG machines.  
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