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Pulmonary hypertension (PH) is a medical condition characterized by elevated pressures in the pulmonary vessels. Pulmonary arterial hypertension (PAH), or pre-capillary PH, is a subgroup of the broader PH definition. PH patients can be subdivided into the following five groups: (i) pulmonary arterial hypertension (PAH), (ii) PH due to left heart disease, (iii) PH due to lung disease, (iv) chronic thromboembolic PH (CTEPH), and (v) PH with unclear and/or multifactorial mechanisms. Pulmonary arterial hypertension (PAH) and chronic thromboembolic pulmonary hypertension (CTEPH) are two of the key subgroups of pulmonary hypertension. The diagnosis and management of pulmonary arterial hypertension (PAH) includes several advances, such as a broader recognition of extra pulmonary vascular organ system involvement, validated point-of-care clinical assessment tools, and focus on the early initiation of multiple pharmacotherapeutics in appropriate patients. Indeed, a principal goal in PAH today is an early diagnosis for prompt initiation of treatment to achieve a minimal symptom burden; optimize the patient’s biochemical, hemodynamic, and functional profile; and limit adverse events.
However, there is interest in the use of artificial intelligence approaches in medicine and the application of diagnostic algorithms to large healthcare data sets, to identify patients at risk of rare conditions. In this article, we review current approaches and challenges in screening for PAH and explore novel population-based approaches to improve detection. This review describes the epidemiology, pathology and pathobiology of PAH and introduces important concepts regarding the diagnosis and risk stratification of PAH. The management of PAH is also discussed, with a special focus on PAH specific therapy and key supportive measures.
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"Pulmonary Arterial Hypertension- A Challenge to Science", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 2, page no.155 - 162, February-2024, Available :http://www.ijrti.org/papers/IJRTI2402027.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator