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CTRI Number  CTRI/2024/01/061013 [Registered on: 01/01/2024] Trial Registered Prospectively
Last Modified On: 25/12/2023
Post Graduate Thesis  Yes 
Type of Trial  Observational 
Type of Study   Exploratory study 
Study Design  Other 
Public Title of Study   Using Artificial Intelligence To Predict How Well Will Be The Functional Recovery After Stroke 
Scientific Title of Study   Utilizing Artificial Intelligence For Prediction Of Functional Recovery Post Stroke 
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 Raghavendrasingh Dharwadkar 
Designation  Assistant Professor 
Affiliation  KAHER Institute Of Physiotherapy 
Address  Department of Neurology Physiotherapy Room no. 2 KLE Institute of Physiotherapy JNMC Campus Nehru Nagar Belagavi

Belgaum
KARNATAKA
590010
India 
Phone  9886288225  
Fax    
Email  raghavendrasingh@klekipt.edu.in  
 
Details of Contact Person
Scientific Query  
Name  Dr Raghavendrasingh Dharwadkar 
Designation  Assistant Professor 
Affiliation  KAHER Institute Of Physiotherapy 
Address  Departement of Neurology Physiotherapy Room no. 2 KLE Institute of Physiotherapy JNMC Campus Nehru Nagar Belagavi

Belgaum
KARNATAKA
590010
India 
Phone  9886288225  
Fax    
Email  raghavendrasingh@klekipt.edu.in  
 
Details of Contact Person
Public Query  
Name  Mansi Deole 
Designation  1st Year MPT student 
Affiliation  KAHER Institute Of Physiotherapy 
Address  KLE Institute of Physiotherapy JNMC Campus Nehru Nagar Belagavi

Belgaum
KARNATAKA
590010
India 
Phone  8469039593  
Fax    
Email  mansi.deole@gmail.com  
 
Source of Monetary or Material Support  
KLE Dr Prabhakar Kore Hospital and Research Centre Nehru Nagar Belagavi 
 
Primary Sponsor  
Name  KAHER Institute of Physiotherapy 
Address  KAHER Institute Of Physiotherapy, JNMC Campus, Nehru Nagar, Belagavi 
Type of Sponsor  Research institution and hospital 
 
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 Raghavendrasingh Dharwadkar  KAHER Institute Of Physiotherapy  Advanced Physiotherapy Centre Room No. 39 Sagar Floor KLE Dr. Prabhakar Kore Hospital Belagavi Karnataka
Belgaum
KARNATAKA 		 9886288225

raghavendrasingh@klekipt.edu.in 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Research And Ethical Committee KAHER Institute Of Physiotherapy  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Healthy Human Volunteers  Adults diagnosed with stroke above the age group of 18 years 
 
Intervention / Comparator Agent  
Type  Name  Details 
Comparator Agent  Nil  Nil 
Intervention  Nil  Nil 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  99.00 Year(s)
Gender  Both 
Details  Subjects willing to participate in the study
Male and female participants above the age of 18 years diagnosed with stroke
Participant able to follow the commands
 
 
ExclusionCriteria 
Details  Participants with unstable neurological condition, orthopaedic condition, cardiac condition or mental condition
 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
the functional recovery will be assessed using the Barthel index  the Barthel index will be assessed in the initial visit i.e. at the baseline (t0) 
 
Secondary Outcome  
Outcome  TimePoints 
NIL  NIL 
 
Target Sample Size   Total Sample Size="96"
Sample Size from India="96" 
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)   03/01/2024 
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="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  
Over the previous 20 years, the mean stroke prevalence in various parts of India varied from 44.29 to 559/100,000 persons. These stroke  estimations were found to be higher than High Income Countries. In comparison to high income countries, early stroke mortality rates were also greater in India. 
•Although the functional deficits after stroke may include cognitive, speech, visual, sensory and motor deficits, the most commonly recognized deficit after stroke is motor impairment that may have negative impact on the subject’s mobility and quality of life.
•By offering predictions, appropriate rehabilitation may be targeted, and patients may be discharged earlier.
•A precise estimation of a person’s likelihood of recovery would make it possible to set reasonable goals and direct the distribution of resources for rehabilitation.
•An effective tool for clinical research, development of healthcare economics policy, and support for clinical choices is a prediction model of functional recovery trajectory.
a)it might aid in early rehabilitation planning and long-term management.
b)it might give early signals or triggers for people who don’t heal as expected
c)survivors and caretakers could make necessary plans if they were aware of the potential timing of poor health consequences.
A comprehensive knowledge of the key variables is necessary for rehabilitation techniques that enhance post-stroke recovery results, these include: age, gender, comorbidities, stroke subtype, disability adjusted life years, etc. 
•The benefit of machine learning approaches is their capacity to forecast outcomes on a single-subject stage while taking a wide range of factors into account. This capability is essential for their potential use in clinical procedures.
•Patterns and correlations that may not be obvious to human assessors can be found in the data analyzed by machine learning algorithms.
•There are many models to forecast functional outcomes after stroke, but it is challenging to use them in India due to cultural and regional variances.
•Therefore, the goal of this study is to identify the most reliable predictive model for functional recovery following stroke in the Indian population using machine learning algorithms.
 
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