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NCT05116423

Machine-learning Based Prediction Model in Primary Immune Thrombocytopenia

Status unknown Last updated 8 February 2022
What this trial tests

trial in Immune Thrombocytopenia in 100 participants. Status unknown.

Timeline
10 November 2021
Primary endpoint
1 March 2022
30 June 2022

Quick facts

Lead sponsorPeking University People's Hospital
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment100
Start date10 November 2021
Primary completion1 March 2022
Estimated completion30 June 2022
Sites1 location across China

Conditions studied

Sponsor

Peking University People's Hospital

Who can join

18 and older, any sex, with Immune Thrombocytopenia or ITP. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

  1. Abstract Book for the 27th Congress of the European Hematology Association
    · 2022
  2. P1655: PERSONALIZED MACHINE-LEARNING-BASED PREDICTION FOR CRITICAL IMMUNE THROMBOCYTOPENIA BLEEDS: A NATIONWIDE DATA STUDY
    An Z, Wu Y, Huang R, Zhou H, et al · · 2022

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Other recruiting trials for Immune Thrombocytopenia

Currently open trials in the same condition.

Other Peking University People's Hospital trials

Trials by the same sponsor.

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Data sources for this page

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