ArticlemedRxiv : the preprint server for health sciences2023
Lipidomics for diagnosis and prognosis of pulmonary hypertension.
Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Artificial intelligence in pulmonary hypertension: a systematic review.European journal of medical research · 2025Pooled it
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Authors and funding
16 authors at 8 institutions in 4 countries.
Funding
Abstract
Background: Pulmonary hypertension (PH) poses a significant health threat with high morbidity and mortality, necessitating improved diagnostic tools for enhanced management. Current biomarkers for PH lack functionality and comprehensive diagnostic and prognostic capabilities. Therefore, there is a critical need to develop biomarkers that address these gaps in PH diagnostics and prognosis. Methods: To address this need, we employed a comprehensive metabolomics analysis in 233 blood based samples coupled with machine learning analysis. For functional insights, human pulmonary arteries (PA) of idiopathic pulmonary arterial hypertension (PAH) lungs were investigated and the effect of extrinsic FFAs on human PA endothelial and smooth muscle cells was tested Results: PA of idiopathic PAH lungs showed lipid accumulation and altered expression of lipid homeostasis-related genes. In PA smooth muscle cells, extrinsic FFAs caused excessive proliferation and endothelial barrier dysfunction in PA endothelial cells, both hallmarks of PAH.In the training cohort of 74 PH patients, 30 disease controls without PH, and 65 healthy controls, diagnostic and prognostic markers were identified and subsequently validated in an independent cohort. Exploratory analysis showed a highly impacted metabolome in PH patients and machine learning confirmed a high diagnostic potential. Fully explainable specific free fatty acid (FFA)/lipid-ratios were derived, providing exceptional diagnostic accuracy with an area under the curve (AUC) of 0.89 in the training and 0.90 in the validation cohort, outperforming machine learning results. These ratios were also prognostic and complemented established clinical prognostic PAH scores (FPHR4p and COMPERA2.0), significantly increasing their hazard ratios (HR) from 2.5 and 3.4 to 4.2 and 6.1, respectively. Conclusion: In conclusion, our research confirms the significance of lipidomic alterations in PH, introducing innovative diagnostic and prognostic biomarkers. These findings may have the potential to reshape PH management strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.