NCT05228548

Brief Summary

This study aimed to develop and interpret a machine learning model to predict red blood cell (RBC) transfusion.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
6,121

participants targeted

Target at P75+ for all trials

Timeline
Completed

Started Jan 2022

Shorter than P25 for all trials

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

January 13, 2022

Completed
Same day until next milestone

Study Start

First participant enrolled

January 13, 2022

Completed
19 days until next milestone

Primary Completion

Last participant's last visit for primary outcome

February 1, 2022

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

February 1, 2022

Completed
7 days until next milestone

First Posted

Study publicly available on registry

February 8, 2022

Completed
Last Updated

March 8, 2022

Status Verified

January 1, 2022

Enrollment Period

19 days

First QC Date

January 13, 2022

Last Update Submit

March 7, 2022

Conditions

SurgeryBlood Transfusion

Keywords

Decision treeeXtreme garadient boostingk-nearest neighborsLogistic regressionMachine learningPrediction modelRandom forestRed blood cell transfusionSurgery

Outcome Measures

Primary Outcomes (2)

  • Number of patients received Red blood cell transfusion

    Number of patients received Red blood cell transfusion

    Perioperative period

  • The area under the curve

    The the area under the curve of the receiver operating characteristics curves

    Perioperative period

Interventions

Perioperative blood transfusionOTHER

Perioperative blood transfusion

Eligibility Criteria

Age18 Years - 100 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)
Sampling MethodNon-Probability Sample
Study Population

Patients undergoing major elective surgical procedures were considered eligible. All age groups and both genders were included. The surgical procedures were predefined according to the Classification of Diagnostic, Therapeutic, and Surgical Procedures of the National Social Insurance Institution, in which every procedure has a unique cod

You may qualify if:

  • Adult
  • Underwent major elective surgery

You may not qualify if:

  • Pediatric patients
  • Emergency cases

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Dilek D Unal

Ankara, 06110, Turkey (Türkiye)

Location

Related Publications (3)

  • Murphy GJ, Reeves BC, Rogers CA, Rizvi SI, Culliford L, Angelini GD. Increased mortality, postoperative morbidity, and cost after red blood cell transfusion in patients having cardiac surgery. Circulation. 2007 Nov 27;116(22):2544-52. doi: 10.1161/CIRCULATIONAHA.107.698977. Epub 2007 Nov 12.

    PMID: 17998460RESULT

  • Bernard AC, Davenport DL, Chang PK, Vaughan TB, Zwischenberger JB. Intraoperative transfusion of 1 U to 2 U packed red blood cells is associated with increased 30-day mortality, surgical-site infection, pneumonia, and sepsis in general surgery patients. J Am Coll Surg. 2009 May;208(5):931-7, 937.e1-2; discussion 938-9. doi: 10.1016/j.jamcollsurg.2008.11.019. Epub 2009 Mar 26.

    PMID: 19476865RESULT

  • Walczak S, Velanovich V. Prediction of perioperative transfusions using an artificial neural network. PLoS One. 2020 Feb 24;15(2):e0229450. doi: 10.1371/journal.pone.0229450. eCollection 2020.

    PMID: 32092108RESULT

Study Officials

  • Dilek D Unal, Prof

    UNIVERSITY OF HEALTH SCIENCES TURKEY DISKAPI YILDIRIM BEYAZIT TRAINING RESEARCH HOSPITAL ANKARA

    PRINCIPAL INVESTIGATOR

Study Design

Study Type
observational
Observational Model
OTHER
Time Perspective
PROSPECTIVE
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Prof. Dr. Dilek Unal

Study Record Dates

First Submitted

January 13, 2022

First Posted

February 8, 2022

Study Start

January 13, 2022

Primary Completion

February 1, 2022

Study Completion

February 1, 2022

Last Updated

March 8, 2022

Record last verified: 2022-01

Data Sharing

IPD Sharing
Will not share

Locations

TU(1)