ReviewFrontiers in cardiovascular medicine2026
Dynamic navigation-based precision cardiac rehabilitation via blood metabolomics: from risk stratification to real-time intervention optimization.
Review in Frontiers in cardiovascular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.
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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.
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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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0 citing papers in PubMed.
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Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precision cardiac rehabilitation represents a pivotal approach in the secondary prevention of cardiovascular diseases, yet conventional assessment and intervention models are limited by their static and homogeneous nature. Blood metabolomics, through comprehensive analysis of endogenous small-molecule metabolites, provides a panoramic view of an individual's metabolic status and its dynamic evolution, offering a revolutionary tool for truly personalized and dynamic rehabilitation management. This review introduces the innovative concept of a "dynamic navigation" paradigm, systematically summarizing the application of blood metabolomics in constructing individualized metabolic fingerprints, achieving precise risk stratification, dynamically evaluating rehabilitation responses, and optimizing intervention strategies in real time. We explore the paradigm shift from static biomarkers to dynamic metabolic navigation, addressing the necessary technological integrations and clinical translation challenges inherent in this transition. Furthermore, we discuss future directions toward developing data-driven closed-loop rehabilitation systems that leverage continuous metabolic monitoring to enhance therapeutic efficacy. By bridging metabolomic insights with clinical practice, this dynamic navigation framework promises to transform precision cardiac rehabilitation and improve patient outcomes.
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