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ACTIVE NOT RECRUITING
NCT06815523

Prediction of Duration of Mechanical Ventilation in Acute Hypoxemic Respiratoty Failure

Sponsor: Jesus Villar

View on ClinicalTrials.gov

Summary

Acute hypoxemic respiratory failure (AHRF) is a common cause of admission in intensive care units (ICUs) worldwide. We will assess machine learning (ML) techniques for prediction of prolonged duration (\> or = to 7 days) of mechanical ventilation (MV) in 1,241 patients enrolled in the PANDORA study in Spain. The study was registered with ClinalTrials.gov (NCT03145974). Our aim is to identify a model with the minimum number of variables that predict duration of prolonged ventilation in AHRF patients using data as early as from the first 48 hours with machine learning algorithms.

Official title: Prediction of Duration of Mechanical Venylation in Patients Wit Acute Hypoxemic Respiratory Failure Usinf Machine Learning Approaches

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

1241

Start Date

2025-02-02

Completion Date

2026-06-01

Last Updated

2025-03-11

Healthy Volunteers

No

Interventions

OTHER

Machine learning and logistic regression for the training/testing cohort and validation cohort

Machine learning and logistic regression for the validation cohort

Locations (2)

Hospital Dr. Negrin

Las Palmas de Gran Canaria, Las Palmas, Spain

Hospital Universitario La Paz

Madrid, Spain