Development of a Scoring and Prediction Model for Weaning Success in ARDS Patients Using Ventilation Parameters Combined with Artificial Intelligence and Deep Learning Techniques

NCT06751693 | Completed

• 1 other identifier: 2024-12-07
• Study Type: observational
• Target: 25,000
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to develop an AI-supported scoring model to optimize the weaning processes of ARDS patients from mechanical ventilation. Retrospective analysis will be conducted on the data of 25,000 patients, focusing on ventilator parameters and hemodynamic variables. The model will be designed to contribute to clinical decision support systems.

Conditions

Deep Learning; Artificial Intelegence; ARDS (Acute Respiratory Distress Syndrome)

Keywords

Deep Learning

Outcome Measures

Primary Outcomes (1)

• Successful Weaning

  The primary outcome of this study will be the successful weaning from mechanical ventilation.

  48 hours

Secondary Outcomes (1)

• Mechanical Ventilatory Parameters

  48 hours

Study Arms (2)

Weaned

Those successfully weaned from mechanical ventilation

Non-weaned

Those who not weaned from mechanical ventilation

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Intubated patients which diagnosed with ARDS and followed up in the ICU for more than 48 hours.

You may qualify if:

• ARDS diagnosis
• Aged 18 years and older
• Intubated and followed by Mechanical ventilation
• Admission on Intensive care unit
• Complete data on clinical support and desicion system

You may not qualify if:

• Missing data
• Under 18 years of age
• Followed by non-ARDS conditions
• Terminal status

Sponsors & Collaborators

• Bakirkoy Dr. Sadi Konuk Research and Training Hospital: lead

Study Sites (1)

Bakirkoy Dr Sadi Konuk Research and Training Hospital

Istanbul, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Acute Lung Injury

Condition Hierarchy (Ancestors)

Lung Injury; Lung Diseases; Respiratory Tract Diseases

Study Officials

• Zafer Cukurova, M.D

  Bakırkoy Dr. Sadi Konuk Training and Research Hospital

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 11, 2024
• First Posted: December 30, 2024
• Study Start: December 10, 2024
• Primary Completion: December 24, 2024
• Study Completion: December 24, 2024
• Last Updated: December 30, 2024

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)