Machine Learning Model to Predict Outcome in Acute Hypoxemic Respiratory Failure (MEMORIAL)

February 7, 2025 updated by: Jesus Villar, Dr. Negrin University Hospital

Developing an Optimal Machine Learning Model to Predict ICU Outcome in Patients With Acute Hypoxemic Respiratory Failure

Acute hypoxemic respiratory failure (AHRF) is the most common cause of admission in the intensive care units (UCIs) worldwide. We will assess the value of machine learning (ML) techniques for early prediction of ICU death in 1,241 patients enrolled in the PANDORA (Prevalence AND Outcome of acute Respiratory fAilure) Study in Spain. The study was registered with ClinicalTrials.gov (NCT03145974). Our aim is to evaluate the minimum number of variables models using logistic regression and four supervised ML algorithms: Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Active, not recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

Acute hypoxemic respiratory failure (AHRF) is the most common cause of admission in the intensive care units (UCIs) worldwide. We will assess the value of machine learning (ML) techniques for early prediction of ICU death in AHRF patients on mechanical ventilation (MV). Few studies have investigated the prediction of mortality in patients with AHRF.

For model development, the investigators will extract data for the first 2 days after diagnosis of AHRF from patients included in the de-identified database of the PANDORA cohort. We had a database with 2,000,000 anonymized and dissociated demographics and clinical, data from 1,241 patients with AHRF enrolled in our PANDORA cohort (Prevalence AND Outcome of acute Respiratory fAilure) from 22 Spanish hospitals and coordinated by the principal investigator (JV). The investigators will follow the Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines for model prediction. We will screen collected variables employing a genetic algorithm variable selection method to achieve parsimony. We evaluated the minimum number of variables models using logistic regression and 4 supervised ML algorithms: Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron. We will use a 5-fold cross-validation in the dataset of 1,000 patients selected randomly in training data (80%) and testing data (20%). For external validation, we will use the remaining 241 patients.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
1241

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Spain
      • Ciudad Real, Spain, 13005
        • Hospital General Universitario de Ciudad Real
      • Cuenca, Spain, 16002
        • Hospital Virgen de la Luz
      • Madrid, Spain, 28046
        • Hospital Universitario La Paz
      • Madrid, Spain, 28222
        • Hospital Universitario Puerta de Hierro
      • Murcia, Spain, 3012
        • Hospital Universitario Virgen de Arrixaca
      • Santa Cruz De Tenerife, Spain, 38010
        • Hospital Universitario NS de Candelaria
      • Valencia, Spain, 46010
        • Hospital Cinico de Valencia
      • Valladolid, Spain, 47012
        • Hospital Universitario Rio Hortega

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

De-identified dataset inclusing 1,241 mechanically ventilated patients with acute hypoxemic respiratory failure admitted consecutively in a network of Spanish ICUs.

Description

Inclusion Criteria:

  • endotracheal intubation plus mechanical ventilation (MV)
  • PaO2/FiO2 ratio ≤300 mmHg under MV with positive end-expiratory pressure (PEEP) ≥5 cmH2O and FiO2 ≥0.3.

Exclusion Criteria:

  • Post-operative patients ventilated <24 h
  • Brain death patients.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.
Validation cohort
It will contain 200 patients randomly selected (20% of 1000 patients with AHRF
Other: machine learning analysis
We will use robust machine learning approaches, such as Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron.
Other Names:
  • Logistic regression, cross validation, and area under the ROC curves
Confirmatory cohort
It will contain the remaining 241 patients randomply selected (por external validation)
Other: machine learning analysis
We will use robust machine learning approaches, such as Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron.
Other Names:
  • Logistic regression, cross validation, and area under the ROC curves
Derivation cohort
It will contain 800 patients randomly selected (1,000 patients with AHRF)
Other: machine learning analysis
We will use robust machine learning approaches, such as Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron.
Other Names:
  • Logistic regression, cross validation, and area under the ROC curves

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
ICU mortality
Time Frame: up to 100 weeks (from inclusion to death or diascharge from intensive care unit
death in the intensive care unit
up to 100 weeks (from inclusion to death or diascharge from intensive care unit

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
MV duration
Time Frame: up to 100 weeks (from inclusion to extubation)
duration of mechanical ventilation
up to 100 weeks (from inclusion to extubation)

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Dr. Negrin University Hospital

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Jesus Villar, MD, PhD, Fundación Canaria Instituto de Investigación Sanitaria de Canarias

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
March 19, 2024

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
May 30, 2026

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
May 30, 2026

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
March 19, 2024

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 26, 2024

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
March 27, 2024

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
March 25, 2025

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
February 7, 2025

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
February 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • PI24/00325

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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