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NCT04825301 Clinical Trial

Application of Machine Learning Based Approaches in Emergency Department to Support Clinical Decision Managing SARS-CoV-2 Infected Patients

Covid19 Clinical Trial

Official title:
Application of Machine Learning Based Approaches in Emergency Department to Support Clinical Decision Managing SARS-CoV-2 Infected Patients

Clinical Trial Details — Status: Recruiting

Administrative data
NCT number NCT04825301
Other study ID # prot. N. 28958
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date February 27, 2020
Est. completion date April 30, 2022

Study information
Verified date September 2021
Source University of L'Aquila
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The aim of the study is to develop a prognostic prediction model based on machine learning algorithms in patients affected by coronavirus disease 2019 (COVID-19), the prediction model will be capable to recognize patient with favorable prognosis or patient with poor prognosis by intelligent systems data analysis.

Recruitment information / eligibility
Status Recruiting
Enrollment 779
Est. completion date April 30, 2022
Est. primary completion date March 30, 2022
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - patients aged over 18 positive for COVID-19 by polymerase chain reaction assay for rhino-pharyngeal swab Exclusion Criteria: - Under 18 aged

Study Design

Related Conditions & MeSH terms

Locations
Country Name City State
Italy University of L'Aquila L'Aquila

Sponsors (1)
Lead Sponsor Collaborator
University of L'Aquila

Country where clinical trial is conducted

Italy, 

Outcome
Type Measure Description Time frame Safety issue
Primary COVID-19 clinical course Data about sex, age, symptoms start date, symptoms, comorbidity, vital parameters, hematochemical blood tests, therapy, oxygen support, radiology, clinical disease progression will be collected. The collected data will be analyzed through a machine learning based approach to predict the prognosis of patients affected by COVID-19. 2 months
Secondary Application of machine learning algorithms on data of patients affected by COVID-19 The collected data will be analyzed through a machine learning based approach to establish correlations between collected data and the prognosis of patients affected by COVID-19. 2 months
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