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

Launched by KU LEUVEN · May 7, 2024

Keywords

ClinConnect Summary

This clinical trial is exploring a new diagnostic tool that uses artificial intelligence to help identify a specific type of lung condition called post-capillary pulmonary hypertension. This condition is often linked to heart failure and can be challenging to diagnose accurately. The tool analyzes data from 344 patients, looking at 20 simple tests that don’t require invasive procedures, like blood tests and heart scans, to predict the likelihood of someone having this condition.

To participate in the trial, patients must be at least 18 years old and show signs of having pulmonary hypertension based on their medical history and initial tests. They will also need to undergo a standard procedure called right heart catheterization, which is considered the best way to confirm the diagnosis. This study aims to compare the results from the new diagnostic tool with those from the catheterization to see how well it works. Participants will help researchers understand if this tool can improve the way doctors diagnose and treat pulmonary hypertension in the future.

Gender

ALL

Eligibility criteria

• 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