Precision medicine and personalized nursing in cardiovascular disease: clinical applications and frontier developments

TL;DR

This paper explores how combining precision medicine with personalized nursing can improve cardiovascular disease management through advanced technologies and patient-centered care.

Contribution

A novel framework for personalized nursing integrating physiological, psychological, social, and cultural dimensions is proposed.

Findings

Precision medicine and AI improve diagnostic accuracy and treatment optimization for CVD.

An integrated patient-centered model enhances care efficiency and clinical outcomes.

Challenges like data privacy and ethical issues require interdisciplinary solutions.

Abstract

Cardiovascular diseases (CVDs) continue to be the leading cause of mortality worldwide, and the available treatments are not sufficiently effective. The integration of precision medicine with personalized nursing offers a promising approach for early prevention, accurate diagnosis, treatment optimization, and prognosis assessment in CVD management. This review systematically analyzes recent advancements in multi-omics analysis and artificial intelligence (AI) technologies within the cardiovascular field, focusing on how precision medicine can improve the diagnostic and therapeutic accuracy as well as care efficiency, thereby improving clinical outcomes. For personalized nursing, we propose a novel implementation framework that incorporates physiological, psychological, social, and cultural dimensions, creating an integrated patient-centered management model based on comprehensive profiling. The synergistic integration of precision medicine and personalized nursing can yield a collaborative system that allows precise identification, individualized intervention, and comprehensive management, reflecting a paradigm shift toward patient-centered healthcare. In addition, the present analysis reveals existing challenges—including data privacy, ethical considerations, and cost-effectiveness—underscoring the urgent need for interdisciplinary collaboration and technological innovation to overcome these barriers. Therefore, the insights from this study are expected to guide the formulation of future research aimed at developing optimal clinical interventions to improve the prognosis and quality of life for patients with CVD.

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