{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T10:08:12Z","timestamp":1789380492101,"version":"build-2803163510"},"reference-count":59,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"<jats:p>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 \u201cdynamic navigation\u201d 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.<\/jats:p>","DOI":"10.3389\/fcvm.2026.1805494","type":"journal-article","created":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T05:38:53Z","timestamp":1783316333000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic navigation-based precision cardiac rehabilitation via blood metabolomics: from risk stratification to real-time intervention optimization"],"prefix":"10.3389","volume":"13","author":[{"given":"Hejuan","family":"Hua","sequence":"first","affiliation":[{"name":"Department of Cardiology, First People's Hospital of Xiaoshan District","place":["Hangzhou, Zhejiang, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanbing","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Clinical 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