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CTRI Number  CTRI/2025/09/094184 [Registered on: 03/09/2025] Trial Registered Prospectively
Last Modified On: 03/09/2025
Post Graduate Thesis  Yes 
Type of Trial  Observational 
Type of Study   Cohort Study 
Study Design  Single Arm Study 
Public Title of Study   Developing a tool that predicts the outcome of patients with brain bleeding after the treatment procedure 
Scientific Title of Study   Development And Validation Of Prediction Tool For Assessing Outcomes In Aneurysmal Subarachnoid Hemorrhage Patients Undergoing Clipping or Coiling 
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 Tripurari Sai Sreedhar 
Designation  PhD Research Scholar 
Affiliation  Manipal College of Pharmaceutical Sciences 
Address  Department of Pharmacy Practice, Room no 12, Manipal College of Pharmaceutical Sciences Manipal Academy of Higher Education Madhava Nagar Manipal 576 104 Udupi District Karnataka

Udupi
KARNATAKA
576104
India 
Phone  9640603983  
Fax    
Email  tripurari.mcopsmpl2024@learner.manipal.edu  
 
Details of Contact Person
Scientific Query  
Name  Dr Raghavendra Nayak 
Designation  HOD & Professor, Department of Neurosurgery 
Affiliation  Kasturba Medical College 
Address  Department of Neurosurgery, Dhanwanthri Block, Room no 1, Kasturba Medical College Manipal Academy of Higher Education Madhava Nagar Manipal 576104 Karnataka

Udupi
KARNATAKA
576104
India 
Phone  9843758637  
Fax    
Email  nayak.raghavendra@manipal.edu  
 
Details of Contact Person
Public Query  
Name  Dr Vijayanarayana k 
Designation  Associate Professor 
Affiliation  Manipal College of Pharmaceutical Sciences 
Address  Department of Pharmacy Practice, Room no 01, Manipal College of Pharmaceutical Sciences Manipal Academy of Higher Education Madhava Nagar Manipal 576 104 Udupi District Karnataka Manipal 576 104 Udupi District Karnataka

Udupi
KARNATAKA
576104
India 
Phone  8202922403  
Fax    
Email  vijayanarayana.k@manipal.edu  
 
Source of Monetary or Material Support  
Manipal Academy of Higher Education 
 
Primary Sponsor  
Name  Manipal Academy of Higher Education 
Address  Madhav Nagar, Manipal, Karnataka 576104 
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 Raghavendra Nayak  Kasturba Medical College  Room no 1 Department of Neurosurgery, Kasturba Medical College, Manipal, Karnataka, India
Udupi
KARNATAKA 		 9843758637

nayak.raghavendra@manipal.edu 
 
Details of Ethics Committee  
No of Ethics Committees= 1  
Name of Committee  Approval Status 
Kasturba Medical College and Kasturba Hospital Institutional Ethical Committee  Approved 
 
Regulatory Clearance Status from DCGI  
Status 
Not Applicable 
 
Health Condition / Problems Studied  
Health Type  Condition 
Patients  (1) ICD-10 Condition: I60||Nontraumatic subarachnoid hemorrhage,  
 
Intervention / Comparator Agent  
Type  Name  Details 
Intervention  Nil  Nil 
 
Inclusion Criteria  
Age From  18.00 Year(s)
Age To  80.00 Year(s)
Gender  Both 
Details  Patients with Different Co-morbid conditions 
 
ExclusionCriteria 
Details  Traumatic and Non-aneurysmal SAH conditions
Previous history of Stroke 
 
Method of Generating Random Sequence   Not Applicable 
Method of Concealment   Not Applicable 
Blinding/Masking   Not Applicable 
Primary Outcome  
Outcome  TimePoints 
To develop a prognostic model by identifying risk factors and other complications in different age groups with various comorbid conditions, leading to mortality during hospital stays and to identify the factors influencing the recovery outcomes such as Cognitive impairment and functional dependency in aSAH patients treated with different procedures.  At hospital admission: Demographic details, comorbidities, clinical severity, risk factors.

During hospital stay: Development of complications, neurological status, interventions, and in-hospital mortality.

At discharge: Functional status, complications, immediate recovery outcomes.

At 1 month post-discharge: Cognitive impairment, functional dependency via standardized scales. 
 
Secondary Outcome  
Outcome  TimePoints 
To assess the correlation of clinical risk factors, treatment modalities (clipping vs. coiling), and in-hospital complications such as neurological and cardiopulmonary events with outcomes.   During hospital stay until discharge: Correlation of clinical risk factors, treatment modalities (clipping vs. coiling), and in-hospital complications (neurological and cardiopulmonary) with outcomes. 
To Identify the predictors and the occurrence of rehospitalization due to severe complications or neurological deterioration.  At 30 days post-discharge: Identification of predictors of poor recovery and occurrence of rehospitalization due to severe complications or neurological deterioration. 
 
Target Sample Size   Total Sample Size="230"
Sample Size from India="230" 
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)   22/09/2025 
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="3"
Months="0"
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   Aneurysmal subarachnoid hemorrhage (aSAH) is a sudden onset life-threatening condition with a higher risk of morbidity and mortality. Predicting the patient outcomes remains challenging due to variability in radiological findings, clinical outcomes and postoperative complications. Current prognostic models for aSAH are mainly focused on mortality, length of stay, clinical risk factors, and surgical details. Most of the existing models were developed on retrospective data with a limited focus on recovery outcomes, excluding the aspects of neurological deficits, cognitive recovery and severity of functional dependency. The proposed prediction model will be developed based on a prospective cohort study and incorporates AI / ML-based algorithms to enhance accuracy by integrating various parameters of clinical, radiological, In-hospital complications, functional and cognitive outcomes in aSAH patients. 
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