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

Pulmonary Hypertension Clinical Trial

— Optiek 2-0  

Official title:

Optimizing the Pulmonary Hypertension Diagnostic Network in Belgium: Validation of a Machine Learning Predictive Model to Distinguish Post-capillary Pulmonary Hypertension

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06405126
• Other study ID #: S68038
• Secondary ID: CIV-23-11-044814
• Status: Recruiting
• Start date: February 21, 2024
• Est. completion date: February 2026

Study information

• Verified date: May 2024
• Source: KU Leuven
• Contact: Laura Hardy, MD
• Phone: +3216338917
• Email: laura.hardy[@]uzleuven.be
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100
• Est. completion date: February 2026
• Est. primary completion date: August 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Voluntary written informed consent of the participant or their legally authorized representative has been obtained prior to any screening procedures

2. Male or female patients of at least 18 years old.

3. Availability of the results of a basic work-up:

1. Medical history, demographic information and clinical information (including BMI)

2. Laboratory tests including hemoglobin, hematocrit and uric acid

3. ECG

4. Pulmonary function tests

5. Echocardiography

4. Intermediate to high probability of PH based on echocardiography according to the 2022 ESC/ERS guidelines (see Figure 2 and Table 2). (1)

5. Indication for RHC according to ESC/ERS 2022 guidelines. (1)

Exclusion Criteria:

1. Evidence of significant pulmonary comorbidity based on abnormal pulmonary function tests (FEV1 below 60%) or aberrant lung parenchyma more than mild on radiological imaging.

2. Perfusion defects and ventilation mismatch on a recent V/Q scan.

3. Arterial perfusion defects on a recent thoracic CT angiography.

4. The following comorbidities associated with group 1 PH:

1. Connective tissue disease

2. HIV infection

3. Portal hypertension

4. Congenital heart disease

5. The following comorbidities associated with group 5 PH:

1. Hematological disorders such as chronic hemolytic anemia or myeloproliferative disorders.

2. Systemic and metabolic disorders such as pulmonary Langerhans cell histiocytosis, Gaucher disease, glycogen storage diseases, neurofibromatosis or sarcoidosis.

3. Chronic renal failure (eGFR below 30 ml/min) with or without hemodialysis

4. Fibrosing mediastinitis

Related Conditions & MeSH terms

• Hypertension
• Hypertension, Pulmonary
• Pulmonary Arterial Hypertension
• Pulmonary Hypertension

Intervention

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.

Locations

Country	Name	City	State
Belgium	Ziekenhuis Oost-Limburg	Genk	Limburg
Belgium	Jessa Hospital	Hasselt	Limburg
Belgium	AZ Groeninge	Kortrijk	West-Vlaanderen
Belgium	UZ Leuven	Leuven	Vlaams Brabant

Sponsors (2)

Lead Sponsor	Collaborator
KU Leuven	Research Foundation Flanders

Country where clinical trial is conducted

Belgium, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Diagnostic accuracy of the Optiek model	sensitivity, specificity, positive and negative predictive value of the model compared to a right heart catheterization (gold standard)	18 months
Secondary	Number of right heart catheterizations which could have been avoided	The number of avoidable rght heart catheterizations will be derived from the sensitivity of the model.	18 months
Secondary	Right heart catheterization related adverse events	All subsequent adverse events will be registered in the eCRF.	18 months
Secondary	Feasibility of the implementation of the Optiek model in clinical practice	The feasibility will be assessed using a questionnaire adressed to the physicians using the model.	18 months