Abstract

ARTIFICIAL INTELLIGENCE IN PULMONARY HYPERTENSION AND ANESTHESIA: INNOVATIONS IN RISK STRATIFICATION, PERIOPERATIVE MANAGEMENT, AND PROGNOSTIC MODELING

V. Prathima, S. D. Divyaprakash, G. Keerthana, K. Naga Tejaswini, C. Charan Kumar Reddy and Yamini Kosaraju*, Tirumerlla Karuna

Abstract

Pulmonary hypertension (PH) presents a significant challenge in perioperative management due to its complex hemodynamic alterations and increased perioperative risks, necessitating precise anesthetic and therapeutic strategies. This review explores the pathophysiological mechanisms underlying PH, emphasizing the critical role of vascular remodeling, hemodynamic perturbations, and right ventricular dysfunction. Advanced monitoring techniques, including echocardiography and biomarker analysis, are essential for perioperative risk assessment and optimization. Artificial intelligence (AI) has emerged as a transformative tool in PH management, enabling predictive analytics, patient-specific anesthetic planning, and continuous postoperative surveillance. AI-driven algorithms integrate multi-omics data, hemodynamic parameters, and clinical biomarkers to enhance early diagnosis, prognostication, and individualized therapeutic interventions. Moreover, AI-facilitated pharmacotherapy and drug repurposing strategies offer promising avenues for optimizing PH treatment. This review highlights the evolving role of AI in anesthetic precision, perioperative decisionmaking, and long-term management, underscoring the necessity for multidisciplinary collaboration and AI enabled innovations to improve outcomes in PH patients undergoing surgical procedures.

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