Applications of machine learning model for prediction of outcomes in primary pontine hemorrhage

Completed

• Conditions: Pontine; Pontine hemorrhage; hemorrhage

• Registration Number: TCTR20210919002
• Lead Sponsor: Faculty of Medicine, Thammasat University

Brief Summary

Machine learning can predict 1-month mortality rate in accuracy of 74-91% Also, ML can predict 1-month functional outcome in accuracy of 69.6-82.6%

Detailed Description

Not available

Study Timeline

• Study Completion: 2021-08-31
• Study Start: 2021-09-19
• Last Update Posted: 19 August 2024

Recruitment & Eligibility

• Status: Completed
• Sex: All
• Target Recruitment: 63

Inclusion Criteria

Pontine hemorrhage patients diagnosed in Thammasat University Hospital since January 2012 - December 2021

Exclusion Criteria

- Etiology from abnormal vascular lesion ex. AVM, aneurysm
- Etiology from tumor
- Pontine hemorrhage with other sites hemorrhage
- Loss follow-up data or incomplete data

Study & Design

• Study Type: Observational
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
30d Mortality 1 month 30d Mortality prediction

Secondary Outcome Measures

Name	Time	Method
30d functional outcome 1 month 30d functional outcome prediction,90d mortality 3 months 90d mortality prediction,90d functional outcome 3 months 90d functional outcome prediction