RecruitingNot Applicable

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

Egypt2,160 participantsStarted 2025-06-01

Plain-language 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.

Who can participate

Age range

18 Years

Sex

ALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: 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 Criteria: 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.

Questions worth asking your doctor

Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.

1Based on my diagnosis and history, is this trial worth exploring for me — or is there a standard treatment we should try first?
2What does this trial's phase tell us about how much is already known about its safety and benefit?
3What would taking part actually involve for me — visits, tests, time, and travel?
4What are the known and possible risks or side effects I should weigh, and how would they be monitored?
5If this trial isn't the right fit, what other options or trials would you suggest I look into?

Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.

Questions for the trial coordinator

The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.

1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?

A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.

What they're measuring

Accuracy of Machine Learning Model in Predicting the Need for Mechanical Ventilation

Timeframe: Within 24 hours of patient presentation

Trial details

NCT IDNCT07001696

SponsorZagazig University

Sponsor typeOTHER_GOV

Study typeOBSERVATIONAL

Primary completion2025-12-31

Contact for this trial

Omaima Ibrahim Prof

+201001664310 OIAbdelhamid@medicine.zu.edu.eg

View on ClinicalTrials.gov More Respiratory Failure trials