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Validation of a Machine Learning Predictive Model to Distinguish Post-capillary Pulmonary Hypertension

NCT06405126 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2024-05-08

No results posted yet for this study

Summary

In this study the diagnostic accuracy of a diagnostic tool for the diagnosis of post-capillary pulmonary hypertension will be investigated.

The diagnostic tool was designed based on artificial intelligence, using machine learning on a database of 344 patients with group 1 or group 2 pulmonary hypertension. The tool uses 20 non-invasive parameters which are derived from laboratory results, ECG, echocardiography and spirometry. Based on these parameters, the predictive tool estimates the probability of group 2 pulmonary hypertension.

During this clinical study, patients with an intermediate or high suspicion of pulmonary hypertension, with an indication for a diagnostic right heart catheterization, will be included. Patients with risk factors for group 3, 4 or 5 pulmonary hypertension will be excluded.

The necessary parameters to run the predictive model will be extracted from the patients medical file. Patients will undergo a standard of care right heart catheterization (gold standard). Afterwards the results of the predictive model will be compared to those of the right heart catheterization, to allow the assessment of the sensitivity, specificity, positive and negative predictive value of the predictive tool.

Conditions

Interventions

DIAGNOSTIC_TEST

Optiek predictive model

Patient data will be extracted to run the predictive model, which will estimate the probability of group 2 pulmonary hypertension. However the results of the model will have no diagnostic or therapeutic implications in this phase of the investigation.

Sponsors & Collaborators

  • Research Foundation Flanders

    collaborator OTHER

  • KU Leuven

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-02-21
Primary Completion
2025-08-31
Completion
2026-02-28

Countries

  • Belgium

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06405126 on ClinicalTrials.gov