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Machine-learning Based Prediction Model in Primary Immune Thrombocytopenia

NCT05116423 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2022-02-08

No results posted yet for this study

Summary

This study developed the first prediction model for risk of critical ITP bleeds for ITP inpatients using a novel machine learning algorithm. This model has been implemented as a web-based model so that clinicians can obtain the estimated probability of critical ITP bleeds for ITP inpatients. The objective of this study is to prospectively and externally validate the risk of critical ITP bleeds in newly admitted ITP patients.

Conditions

Sponsors & Collaborators

  • Affiliated Zhongshan Hospital of Dalian University

    collaborator OTHER

  • Jiangsu Provincial People's Hospital

    collaborator OTHER

  • Qilu Hospital of Shandong University

    collaborator OTHER

  • Shanghai Zhongshan Hospital

    collaborator OTHER

  • Peking University People's Hospital

    lead OTHER

Principal Investigators

  • Xiao-Hui Zhang, MD · Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Collaborative Innovation Center of Hematology

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-11-10
Primary Completion
2022-03-01
Completion
2022-06-30

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05116423 on ClinicalTrials.gov