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Completed

NCT Number: NCT05228548

Machine Learning Model for Perioperative Transfusion Prediction

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

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Key information

Conditions

Surgery Blood Transfusion

Age range

18 year–100 year

Sex eligibility

All sexes

Study type

Observational

Primary location

Dilek D Unal

Ankara, 06110, Turkey (Türkiye)

About this study

A dataset from a multicenter study involving 6121 patients underwent elective major surgery was analysed. Data concerning patients who received inappropriate RBC transfusion were excluded. Twenty one perioperative features were used to predict RBC transfusion. The data set was randomly split into train and validation sets (70-30). Decision tree, random forest, k-nearest neighbors, logistic regression, and eXtreme garadient boosting (XGBoost) methods were used for prediction. The area under the curves (AUC) of the receiver operating characteristics curves for the machine learning models used for RBC transfusion prediction were compared.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Adult
  • Underwent major elective surgery

Exclusion criteria

  • Pediatric patients
  • Emergency cases

Treatment and study plan

perioperative blood transfusion

Other

Perioperative blood transfusion

Primary outcomes

  1. Number of patients received Red blood cell transfusion

    Time frame: Perioperative period

    Number of patients received Red blood cell transfusion

  2. The area under the curve

    Time frame: Perioperative period

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

Sponsors and collaborators

Lead sponsor

Diskapi Teaching and Research Hospital

Other

Collaborators

  • Akdeniz University
  • Ankara University
  • Balikesir University
  • Baskent University
  • Bulent Ecevit University
  • Dokuz Eylul University
  • Erzincan University
  • Eskisehir Osmangazi University
  • Firat University
  • Gazi University
  • Hacettepe University
  • Hitit University
  • Inonu University
  • Istanbul Medeniyet University
  • Istanbul University
  • Kahramanmaras Sutcu Imam University
  • Karadeniz Technical University
  • Manisa Celal Bayar University
  • Marmara University
  • Mersin University
  • Namik Kemal University
  • Necmettin Erbakan University
  • Ondokuz Mayıs University
  • Ordu University
  • Osmaniye Government Hospital
  • Saglik Bilimleri Universitesi
  • Selcuk University
  • Suleyman Demirel University
  • TC Erciyes University
  • Tobb University of Economics and Technology
  • Trakya University
  • Ufuk University
  • Uludag University
  • Yuzuncu Yil University

Registry information

Official study title

Development and Interpretation of a Machine Learning Model for Perioperative Transfusion Prediction

Important dates

Study start
2022
Primary completion
2022
Study completion
2022
First posted
Feb 8, 2022
Registry last updated
Mar 8, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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