Active clinical trials for "Hypertension, Pulmonary"

To study the effect of relocation from 2840m (Quito) to sea level (Pedernales) in patients with pulmonary vascular diseases (PVD) defined as pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension (PH) who permanently live >2500m on sleep disordered breathing

To study the effect of relocation from 2840m (Quito) to sea level (Pedernales) in patients with pulmonary vascular diseases (PVD) defined as pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension (PH) who permanently live >2500m on 6-minute walk distance (6MWD)

To study the effect of relocation from 2840m (Quito) to sea level (Pedernales) in patients with pulmonary vascular diseases (PVD) defined as pulmonary arterial hypertension or chronic thromboembolic pulmonary hypertension (PH) who permanently live >2500m on pulmonary artery pressure (PAP) and other hemodynamics.

Potential outcomes after PE occur on a spectrum: complete recovery, exercise intolerance from deconditioning/anxiety, dyspnea from concomitant cardiopulmonary conditions, dyspnea from residual pulmonary vascular occlusion, chronic thromboembolic disease and chronic thromboembolic pulmonary hypertension. Although a battery of advanced diagnostic tests could distinguish each of those conditions, the yield of individual tests among all post- PE patients is low enough that routine testing of all PE patients is not typically performed. Although the various possible post-PE outcomes have enormous implications for patient care, they are rarely distinguished clinically. Perhaps for this reason, chronic conditions after PE are rarely (if ever) used as endpoints in randomized clinical trials of acute PE treatment. The proposed project will validate a clinical decision tree to distinguish among the various discrete outcomes cost-effectively through a hierarchical series of tests with the acronym SEARCH (for symptom screen, exercise function, arterial perfusion, resting heart function, confirmatory imaging and hemodynamics). Each step of the algorithm sorts a subset of patients into a diagnostic category unequivocally in a cost-effective manner. The categories are mutually exclusive and collectively exhaustive, so that each case falls into one, and only one, category. Each individual test used in the algorithm has been clinically validated in pulmonary embolism patients, including the cardiopulmonary exercise test (CPET) technique that the investigators developed and validated. However, the decision tree approach to deploying the tests has not yet been validated. Aim 1 will determine whether the SEARCH algorithm will yield concordant post-PE diagnoses when multiple reviewers independently evaluate multiple cases (reliability). Aim 2 will determine whether the post-PE diagnoses are stable, according to the SEARCH algorithm, between the first evaluation and the subsequent one six months later (validity).

Despite the developments in recent years, pulmonary arterial hypertension (PAH) is still a disease with high mortality and morbidity. Although studies on genetic background have increased, the pathogenesis of PAH remains complex and unresolved. The most comprehensive data are related to bone morphogenetic protein receptor type 2 (BMPR2), and in recent years, new responsible or candidate genes have been identified, especially by new generation DNA sequencing In this study, it was aimed to determine the genetic background of patients with PAH and to investigate the genetics of secondary PAH not only HPAH.

The goal of this observational study is to apply Artificial Intelligence (AI) and machine learning technology to the resting 12-lead electrocardiogram (ECG) and assess whether it can assist doctors in the early diagnosis of Pulmonary Hypertension (PH). Early and accurate diagnosis is an important step for patients with PH. It helps provide effective treatments early which improve prognosis and quality of life. The main questions our study aims to answer are: Can AI technology in the 12-lead ECG accurately predict the presence of PH? Can AI technology in the 12-lead ECG identify specific sub-types of PH? Can AI technology in the 12-lead ECG predict mortality in patients with PH? In this study, the investigators will recruit 12-lead ECGs from consenting participants who have undergone Right heart Catheterisation (RHC) as part of their routine clinical care. AI technology will be applied to these ECGs to assess whether automated technology can predict the presence of PH and it's associated sub-types.

The main aim of this project is to elucidate the incidence of acute kidney injury (AKI) in newborns with congenital diaphragmatic hernia during stay in the Pediatric intensive care unit. (PICU). This patient group often presents with severe circulatory and respiratory dysfunction requiring intensive care treatment. Characterization of risk factors to AKI will also be performed.

The goal of this observational patient registry is to learn how expert centers treat patients with chronic thromboembolic pulmonary hypertension (CTEPH). CTEPH is a condition in which blood clots block the blood vessels in the lungs. There are currently three treatment options for patients with CTEPH: surgery to remove blood clots from large vessels in the lungs (pulmonary endarterectomy (PEA)) the use of a small balloon to unblock smaller blood vessels (balloon pulmonary angioplasty (BPA)) drugs Patients can also receive a combination of these treatments. The main question this registry aims to answer are: How many patients receive a given kind of treatment? How do expert centers combine the different treatments? Are patients doing better after they receive a given kind of treatment? How many patients are alive 1, 3 and 5 years after they receive a given kind of treatment? Participants will receive the same treatments that they would receive if they did not participate in the study. During the study, patients will visit their doctors as they would do normally. The doctors will collect information on the patients' health and enter it into the study database. The follow-up time will be at least 3 years for all patients.

The findings from this innovative, first-in-man, prospective pilot study will elucidate the role of PIMR and RV-IMR in pre-capillary PH. The study cohort will consist of patients with pulmonary pressures ranging from normal (advanced lung disease patients undergoing lung transplant evaluation) to severe PH (PAH and CTEPH patients), and thus will allow for identification of a PIMR cutoff. Participants will include: 1) advanced lung disease patients undergoing bilateral heart catheterization as part of their pre-lung transplant work-up, and 2) newly referred patients to PAH and CTEPH clinics undergoing bilateral heart catheterization as part of standard of care work-up. All participants will undergo PIMR testing, and those with pre-capillary PH will also undergo pulmonary OCT and measurement of RV-IMR. The study seeks to define the relationship between PIMR and PH and to establish the PIMR threshold that identifies pulmonary microvascular dysfunction as well as to evaluate the association of PIMR and pulmonary vascular remodeling on OCT in patients with pre-capillary PH. In addition, the study will assess the relationship between RV-IMR and RV pressure overload among patients with pre-capillary PH.

PVRI-GoDeep is a PH Meta-Registry, run under the umbrella of the Pulmonary Vascular Research Institute (PVRI). It merges anonymized PH patient related data from various local registries around the world run under the responsibility of PVRI members. It will be operated under the auspices of the University of Giessen/Giessen PH center. Combining deep phenotyping with worldwide outreach, PVRI-GoDeep aims to offer insights into specific geographical and ethnical profiles of PH, to deepen the epidemiological, clinical and molecular understanding of this disease and to promote strategies for improved individualized treatment of PH patients.