To Establish a Blood Transfusion Prediction Model for Liver Transplantation Patients Based on PBM
To Establish a Prediction Model of Massive Blood Transfusion for Liver Transplantation Patients Based on Patient Blood Management
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
- Preoperative variables and statistical analysis of a large number of intraoperative blood transfusions in allogeneic liver transplantation patients were performed to screen preoperative variables.
- Models were established by machine learning algorithms to predict a large number of blood transfusions during surgery, providing a reference for preoperative blood preparation and postoperative outcome.
Study Type
Study Type
Enrollment (Anticipated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Rong Gui, doctor
- Phone Number: +8615200828442
- Email: aguirong@163.com
Study Locations
-
-
Hunan
-
Changsha, Hunan, China, 410006
- Recruiting
- The Third XIANGYA Hospital of Central South University
-
Contact:
- Rong Gui
- Phone Number: +8615200828442
- Email: aguirong@163.com
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
Description
Inclusion Criteria:
- 48h preoperative biochemical indicators, blood general indicators, coagulation test complete
Exclusion Criteria:
- 1. Inspection information is not detailed 2. Blood transfusion information is not detailed 3.Postoperative medical record information is not detailed
Study Plan
How is the study designed?
Design Details
- Observational Models: Cohort
- Time Perspectives: Cross-Sectional
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Liver transplant
|
blood transfusion
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
one year mortality
Time Frame: 2019-2021
|
All-cause mortality
|
2019-2021
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Intraoperative blood transfusion
Time Frame: 2019-2021
|
Intraoperative blood component input
|
2019-2021
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (Anticipated)
Study Start
Primary Completion (Anticipated)
Primary Completion
Study Completion (Anticipated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- ThirdXiangyaLTP
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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