Pulmonary HypertensionOptiek 2-0NCT06405126
Validation of a Machine Learning Predictive Model to Distinguish Post-capillary Pulmonary Hypertension
An observational study of Pulmonary Hypertension and Pulmonary Arterial Hypertension, run by KU Leuven at 4 sites in Belgium.
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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pulmonary Hypertension, Pulmonary Arterial Hypertension, HFpEF - Heart Failure With Preserved Ejection Fraction
- What is being tested?
- Optiek predictive model
- How many people
- 100 participants
- Where
- 4 sitesBelgium
- Study dates
- 21 Feb 2024to Feb 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients with an intermediate to high probability of pulmonary hypertension based on an echocardiography. Patients with a probability of group 3, 4 or 5 pulmonary hypertension will be excluded.
Who may be able to join
- Voluntary written informed consent of the participant or their legally authorized representative has been obtained prior to any screening procedures
- Male or female patients of at least 18 years old.
- Availability of the results of a basic work-up:
- Medical history, demographic information and clinical information (including BMI)
- Laboratory tests including hemoglobin, hematocrit and uric acid
- ECG
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- Pulmonary function tests
- Echocardiography
- Intermediate to high probability of PH based on echocardiography according to the 2022 ESC/ERS guidelines (see Figure 2 and Table 2). (1)
- Indication for RHC according to ESC/ERS 2022 guidelines. (1)
Who cannot join
- Evidence of significant pulmonary comorbidity based on abnormal pulmonary function tests (FEV1 below 60%) or aberrant lung parenchyma more than mild on radiological imaging.
- Perfusion defects and ventilation mismatch on a recent V/Q scan.
- Arterial perfusion defects on a recent thoracic CT angiography.
- The following comorbidities associated with group 1 PH:
- Connective tissue disease
- HIV infection
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- Portal hypertension
- Congenital heart disease
- The following comorbidities associated with group 5 PH:
- Hematological disorders such as chronic hemolytic anemia or myeloproliferative disorders.
- Systemic and metabolic disorders such as pulmonary Langerhans cell histiocytosis, Gaucher disease, glycogen storage diseases, neurofibromatosis or sarcoidosis.
- Chronic renal failure (eGFR below 30 ml/min) with or without hemodialysis
- Fibrosing mediastinitis
Trial locations and contacts
4 sites in 1 country.
Belgium4 sites, 4 recruiting
- Recruiting
Ziekenhuis Oost-Limburg
Genk, Limburg, 3600
David Ruttens, MD, PhD, +32477827441, david.ruttens@zol.be
- Recruiting
Jessa Hospital
Hasselt, Limburg, 3500
Guido Claessens, MD, PhD, 0032 494690168, guido.claessen@jessazh.be
- Recruiting
AZ Groeninge
Kortrijk, West-Vlaanderen, 8500
Mathias Leys, MD, +32486421591, mathias.leys@azgroeninge.be
Mathias Leys, MD
- Recruiting
UZ Leuven
Leuven, Vlaams Brabant, 3000
Marion Delcroix, MD, PhD, +3216346833, marion.delcroix@uzleuven.be
Laura Hardy, MD, +3216338917, laura.hardy@uzleuven.be
About this study
Official title: Optimizing the Pulmonary Hypertension Diagnostic Network in Belgium: Validation of a Machine Learning Predictive Model to Distinguish Post-capillary Pulmonary Hypertension
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.
Read more
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
- Pulmonary Hypertension, Pulmonary Arterial Hypertension, HFpEF - Heart Failure With Preserved Ejection Fraction
- Being tested
- Optiek predictive model
- Keywords
- pulmonary hypertension, pulmonary arterial hypertension, post-capillary pulmonary hypertension, HFpEF, artificial intelligence, diagnostic tool, machine learning, non-invasive diagnosis
- Medical subject headings
- Hypertension, Pulmonary, Pulmonary Arterial Hypertension
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Optiek predictive modelDiagnostic test
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.
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic accuracy of the Optiek model
sensitivity, specificity, positive and negative predictive value of the model compared to a right heart catheterization (gold standard)
Measured: 18 months
Secondary outcomes (3)
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.
Measured: 18 months
Right heart catheterization related adverse events
All subsequent adverse events will be registered in the eCRF.
Measured: 18 months
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.
Measured: 18 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 May 2024
- Study start21 Feb 2024
- Primary completionAug 2025 (estimated)
- Study completionFeb 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary HypertensionStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 100 participants (estimated)
Sponsor and investigators
- Lead sponsor
- KU Leuven
- Sponsor type
- University, hospital or other
- Collaborators
- Research Foundation Flanders
- Responsible party
- Principal investigator, Marion DELCROIX, KU Leuven
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06405126
- Sponsor's protocol ID
- S68038
- Other IDs
- CIV-23-11-044814
- Acronym
- Optiek 2-0
- Status last verified
- May 2024
- First submitted
- 16 Apr 2024
- Last updated
- 8 May 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 8 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Optimizing the Pulmonary Hypertension Diagnostic Network in Belgium: Validation of a Machine Learning Predictive Model to Distinguish Post-capillary Pulmonary Hypertension
- ClinicalTrials.gov ID
- NCT06405126
- Acronym / sponsor ID
- Optiek 2-0 / S68038
- Conditions
- Pulmonary Hypertension, Pulmonary Arterial Hypertension, HFpEF - Heart Failure With Preserved Ejection Fraction
- Keywords
- pulmonary hypertension, pulmonary arterial hypertension, post-capillary pulmonary hypertension, HFpEF, artificial intelligence, diagnostic tool, machine learning, non-invasive diagnosis
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 100 participants (estimated)
- Lead sponsor
- KU LeuvenUniversity, hospital or other
- Collaborators
- Research Foundation Flanders
- Study start
- 21 Feb 2024 (actual)
- Primary completion
- Aug 2025 (estimated)
- Study completion
- Feb 2026 (estimated)
- First posted
- 8 May 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with an intermediate to high probability of pulmonary hypertension based on an echocardiography. Patients with a probability of group 3, 4 or 5 pulmonary hypertension will be excluded.
Key inclusion criteria (10 listed)
- Voluntary written informed consent of the participant or their legally authorized representative has been obtained prior to any screening procedures
- Male or female patients of at least 18 years old.
- Availability of the results of a basic work-up:
- Intermediate to high probability of PH based on echocardiography according to the 2022 ESC/ERS guidelines (see Figure 2 and Table 2). (1)
- Indication for RHC according to ESC/ERS 2022 guidelines. (1)
Key exclusion criteria (13 listed)
- Evidence of significant pulmonary comorbidity based on abnormal pulmonary function tests (FEV1 below 60%) or aberrant lung parenchyma more than mild on radiological imaging.
- Perfusion defects and ventilation mismatch on a recent V/Q scan.
- Arterial perfusion defects on a recent thoracic CT angiography.
- The following comorbidities associated with group 1 PH:
- The following comorbidities associated with group 5 PH:
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Optiek predictive modelPatient 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. | Diagnostic test | – |
Primary outcome
Diagnostic accuracy of the Optiek model
Time frame: 18 months
sensitivity, specificity, positive and negative predictive value of the model compared to a right heart catheterization (gold standard)
3 secondary outcomes
Number of right heart catheterizations which could have been avoided
Time frame: 18 months
Right heart catheterization related adverse events
Time frame: 18 months
Feasibility of the implementation of the Optiek model in clinical practice
Time frame: 18 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 8 May 2024.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
4 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Pulmonary Hypertension and Pulmonary Arterial Hypertension, run by KU Leuven at 4 sites in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 10 inclusion and 13 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 8 May 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Laura Hardy, MD (+3216338917, laura.hardy@uzleuven.be), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic accuracy of the Optiek model (time frame: 18 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 8 May 2024.