RecruitingNCT07001696

Combining Chest X-Ray and Arterial Blood Gas Findings to Predict Need for Mechanical Ventilation in Critically Ill Patients

Combining Chest X-Ray Findings With Arterial Blood Gas Analysis for Generation of Machine Learning Model Assessing the Need for Mechanical Ventilation in Critically Ill Patients

Sponsor

Zagazig University

Enrollment

2,160 participants

Start Date

Jun 1, 2025

Study Type

OBSERVATIONAL

Conditions

Respiratory Failure Mechanical Ventilation Critical Illness

Summary

This prospective cross-sectional study aims to develop and validate a machine learning model that combines chest X-ray findings with arterial blood gas (ABG) analysis to assess the necessity for mechanical ventilation in critically ill adult patients. Conducted at Zagazig University Hospitals, the study seeks to improve clinical decision-making by integrating radiological and biochemical data using artificial intelligence. The model's predictive performance will be evaluated against standard clinical assessments.

Eligibility

Min Age: 18 Years

Inclusion Criteria4

Critically ill adult patients aged 18 years or older.
Patients assessed to require mechanical ventilation.
Control group: Age- and sex-matched critically ill patients not requiring mechanical ventilation.
Availability of both chest X-ray and arterial blood gas (ABG) analysis at the time of evaluation.

Exclusion Criteria3

Patients with missing or incomplete data (e.g., absent chest X-ray or ABG results).
Patients with chronic lung diseases unrelated to the current admission (e.g., COPD, pulmonary fibrosis).
Pregnant females.

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