Deep Biological Clocks in Critical Care Medicine: A Scoping Review Toward Translational Precision Care

TL;DR

This paper reviews how biological aging clocks could improve personalized care in intensive care units by predicting patient outcomes more accurately than traditional methods.

Contribution

The study is the first scoping review to systematically evaluate biological aging biomarkers in ICU settings, highlighting their potential for precision medicine.

Findings

Accelerated biological aging is consistently linked to higher mortality and organ dysfunction in ICU patients.

Inflammation-weighted and stress-responsive biological clocks show clinically meaningful associations with critical illness outcomes.

Despite methodological differences, a convergent signal supports the use of these biomarkers for personalized prognostication.

Abstract

Background: Outcomes after critical illness vary markedly despite similar diagnoses and severity scores, underscoring the limitations of chronological age and conventional Intensive Care Unit (ICU) prognostic tools. Personalization of critical care is increasingly essential to improve not only short-term survival but also long-term post-discharge outcomes. Biological aging clocks provide a quantitative framework to capture physiological reserve, immune competence, and vulnerability to stress. Methods: We conducted a scoping review of original human studies published between January 2015 and October 2025 that evaluated biological aging biomarkers in adult ICU populations. PubMed/MEDLINE, Scopus, Web of Science, and Embase were searched, with backward citation screening. Results: Across epigenetic, telomere-based, cfDNA, proteomic, metabolomic, and phenotypic aging measures, accelerated biological aging was consistently associated with increased mortality, organ dysfunction, and post-ICU vulnerability. Despite substantial methodological heterogeneity, a convergent signal emerged linking inflammation-weighted and stress-responsive deep biological clocks to clinically meaningful outcomes in critically ill patients. Conclusions: Biological aging biomarkers represent a mechanistically grounded approach to personalized prognostication in critical care. From a translational perspective, deep biological clocks hold promise for personalized risk stratification, prognostication, and the identification of high-risk recovery phenotypes, although prospective validation and implementation studies are required.

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