Clinical validation of a machine-learned, point-of-care system to IDENTIFY pulmonary hypertension
Date
2025-09-01
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Citation Stats
Attention Stats
Abstract
Background Pulmonary hypertension (PH) is a collection of diverse disorders, defined by mean pulmonary artery pressure (mPAP) ⩾21 mmHg (most recent guidelines) or ⩾25 mmHg (previous guidelines, that underpins the field’s past work) measured by right heart catheterisation (RHC). Considering the difficulties in diagnosing PH and the subsequent treatment delays, there is a need for novel diagnostics to enable prompt detection. Methods An algorithm to assess mPAP elevation was validated using subjects with elevated mPAP from RHC (positive cohort) and subjects with low probability of PH by stringent screening of transthoracic echocardiography (TTE) PH indicators (negative cohort). 25 mmHg and 21 mmHg were pre-specified as the co-primary and secondary sensitivity end-points, respectively, at 0.70. Specificity was the co-primary end-point at 0.60. The algorithm cut-point was pre-defined. The area under the receiver operator characteristic curve (ROC-AUC) was assessed at both mPAP thresholds. Findings 462 subjects were consecutively enrolled across 18 US clinical sites between August 2019 and September 2022. Sensitivity at 25 mmHg and 21 mmHg was 0.82 (95% CI 0.78–0.87) and 0.78 (95% CI 0.73–0.82), respectively, with specificity of 0.92 (95% CI 0.87–0.96), passing the study end-points. The ROC-AUC values at 25 mmHg and 21 mmHg were 0.95 (95% CI 0.93–0.96) and 0.93 (95% CI 0.91–0.95), respectively. Further, performance was similar across PH subgroups (pre-capillary, combined pre-and post-capillary, and isolated post-capillary), as well as between men and women. Interpretation The algorithm’s performance is comparable, or possibly superior to, TTE, given that the tricuspid regurgitant velocity is not measurable in up to 41% of TTE cases. The test is a stress-free, noninvasive front-line test, presenting advantages to patients, physicians and healthcare systems.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Published Version (Please cite this version)
Publication Info
McLean, D, J Rommel, JA Steuter, WS Carroll, M Rabbat, S Rajagopal, V Srinivasan, DJ Kereiakes, et al. (2025). Clinical validation of a machine-learned, point-of-care system to IDENTIFY pulmonary hypertension. Erj Open Research, 11(5). pp. 01287–2024. 10.1183/23120541.01287-2024 Retrieved from https://hdl.handle.net/10161/34347.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
Collections
Scholars@Duke
Sudarshan Rajagopal
I am a physician-scientist with a research focus on G protein-coupled receptor signaling in inflammation and vascular disease and a clinical focus on pulmonary vascular disease, as I serve as Co-Director of the Duke Pulmonary Vascular Disease Center. My research spans the spectrum from clinical research in pulmonary vascular disease, to translational research in cardiovascular disease, to the basic science of receptor signaling.
Our basic science research focuses on understanding and untapping the signaling potential of G protein-coupled receptors (GPCRs) to regulate inflammation in vascular disease. GPCRs are the most common transmembrane receptors in the human genome (over 800 members) and are some of the most successful targets for drug therapies. While it has been known for some time that these receptors signal through multiple downstream effectors (such as heterotrimeric G proteins and multifunctional beta arrestin adapter proteins), over the past decade it has been better appreciated that these receptors are capable of signaling with different efficacies to these effectors, a phenomenon referred to as “biased agonism”. Ligands can be biased, by activating different pathways from one another, and receptors can be biased, by signaling to a limited number of pathways that are normally available to them. Moreover, this phenomenon also appears to be common to other transmembrane and nuclear receptors. While a growing number of biased agonists acting at multiple receptors have been identified, there is still little known regarding the mechanisms underlying biased signaling and its physiologic impact. We use multiple approaches to probe these signaling mechanisms, including in-house pharmacological assays, advanced phosphoproteomics and single cell RNA sequencing.
Our translational research is focused on studying signaling in different forms of pulmonary hypertension (PH), a disease of the pulmonary vasculature that results in right heart failure. We have identified novel molecular mechanisms that contribute to the development of pulmonary arterial hypertension (PAH), a disease of the pulmonary arterioles. We have also used single cell RNA sequencing to identify the cell types and signaling pathways that contribute to chronic thromboembolic pulmonary hypertension (CTEPH).
Lastly, our clinical research program focuses on the application of novel imaging technologies for diagnosis, prognosis and management of PH. Most notably, this includes the application of hyperpolarized Xenon MRI, in collaboration with Dr. Bastiaan Driehuys in the Department of Radiology, to characterizing the physiological basis of gas exchange and hemodynamic abnormalities across all forms of PH. In collaboration with Dr. Fawaz Alenezi, we have applied advanced echo approaches for the management of PH.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.