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Blood Transfusion Management in Patients With Mitral Valve Replacement in China

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ClinicalTrials.gov Identifier: NCT03885570
Recruitment Status : Recruiting
First Posted : March 21, 2019
Last Update Posted : September 19, 2019
Sponsor:
Collaborators:
Second Xiangya Hospital of Central South University
Chinese Academy of Medical Sciences, Fuwai Hospital
The Affiliated Hospital Of Southwest Medical University
Qilu Hospital of Shandong University
Zhejiang Provincial People's Hospital
Beijing Aerospace General Hospital
Information provided by (Responsible Party):
The Third Xiangya Hospital of Central South University

Brief Summary:
The evaluation uses ΔHb as an independent factor combined with artificial intelligence (AI) to predict its impact on the prognosis and blood transfusion of patients undergoing cardiac surgery, thereby guiding perioperative clinical blood use and improving patient prognosis.

Condition or disease Intervention/treatment
Mitral Valve Replacement Transfusion Reaction Blood Transfusion Complication Procedure: Mitral valve replacement

Detailed Description:
  1. Select 8 hospitals to form a multi-center team, and enter the keyword "mitral valve replacement" in the case system of 8 hospitals to collect information on 2000 heart surgery patients.
  2. Mainly collect information on preoperative, intraoperative and postoperative test indexes (blood routine, liver and kidney function, coagulation function, blood gas), cardiac color Doppler, blood transfusion and prognosis of patients undergoing cardiac surgery, using statistical methods for analysis. Identify key observations.
  3. Gradually incorporate and exclude data, and use statistical methods to conduct preliminary analysis on the collected data.

The AI prediction model was established by machine learning algorithm to predict intraoperative blood transfusion, verify the specificity and sensitivity of the blood transfusion prediction model, and scientifically guide clinical blood use.

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Study Type : Observational
Estimated Enrollment : 2000 participants
Observational Model: Other
Time Perspective: Cross-Sectional
Official Title: Establishment of AI Prediction Model of Blood Transfusion Management in Patients With Mitral Valve Replacement
Estimated Study Start Date : September 16, 2019
Estimated Primary Completion Date : December 2, 2019
Estimated Study Completion Date : December 31, 2021

Resource links provided by the National Library of Medicine


Group/Cohort Intervention/treatment
Groups/Cohorts
1) Patients undergoing "mitral valve replacement" surgery;2) Age 18-75 years old;3) 48h preoperative biochemical indicators, blood general indicators, coagulation indicators are complete.
Procedure: Mitral valve replacement
Blood transfusion




Primary Outcome Measures :
  1. Mortality [ Time Frame: through study completion, an average of 2 year ]
    The mortality during and after hospitalization

  2. Intraoperative blood transfusion [ Time Frame: through study completion, an average of 1 year ]
    The amount of intraoperative blood component input



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 75 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Patients with "mitral valve replacement" surgery who meet the standard in China, 18<Age<75.
Criteria

Inclusion Criteria:

  1. Patients undergoing "mitral valve replacement" surgery;
  2. Age 18-75 years old;
  3. 48h biochemical indicators before surgery, blood general indicators, coagulation indicators are complete.

Exclusion Criteria:

  1. Lack of necessary tests and patient test information is not detailed, blood transfusion information is not detailed;
  2. The blood transfusion information is not detailed in the same period as other cardiac operations (such as aortic valve surgery, coronary artery bypass grafting, etc.), but the tricuspid valvuloplasty is not ruled out at the same time;
  3. Heart surgery or emergency surgery again.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03885570


Contacts
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Contact: Rong Gui, Ph.D 13975199279 aguirong@163.com
Contact: Haiye Jiang, M.Med. 13974873361 1972692495@qq.com

Locations
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China, Hunan
Third Xiangya Hospital Recruiting
Changsha, Hunan, China, 410013
Contact: Rong Gui, Ph.D    13975199279    aguirong@163.com   
Contact: Haiye Jiang, M.Med.    13974873361    1972692495@qq.com   
Sponsors and Collaborators
The Third Xiangya Hospital of Central South University
Second Xiangya Hospital of Central South University
Chinese Academy of Medical Sciences, Fuwai Hospital
The Affiliated Hospital Of Southwest Medical University
Qilu Hospital of Shandong University
Zhejiang Provincial People's Hospital
Beijing Aerospace General Hospital
Investigators
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Principal Investigator: Rong Gui The Third Xiangya Hospital of Central South University
Publications:
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Responsible Party: The Third Xiangya Hospital of Central South University
ClinicalTrials.gov Identifier: NCT03885570    
Other Study ID Numbers: ThirdXiangyaHCSUJF
First Posted: March 21, 2019    Key Record Dates
Last Update Posted: September 19, 2019
Last Verified: March 2019
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by The Third Xiangya Hospital of Central South University:
mitral valve replacement
Predictive Model
Blood Transfusion
Perioperative period
Additional relevant MeSH terms:
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Transfusion Reaction
Hematologic Diseases
Immune System Diseases