ArticleiScience2022
Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis.
Article in iScience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Aortic dissection as a disease of vascular wall homeostasis: integrating vasa vasorum-inflammation-metabolism axis for mechanistic insight and clinical translation.Frontiers in immunology · 2026Review
- Examining saliva proteomic dynamics in mitochondrial diseases from a perspective of intrinsic health.Scientific reports · 2025Article
- Intrinsic health as a foundation for a science of health.Science advances · 2025Review
- Stress tests and biomarkers of resilience: Proceedings of the second state of resilience science conference.Journal of the American Geriatrics Society · 2025Article
- Article
- BMI variability and cardiovascular outcomes within clinical trial and real-world environments in type 2 diabetes: an IMI2 SOPHIA study.Cardiovascular diabetology · 2024Observational
- Tryptophan degradation as a systems phenomenon in inflammation - an analysis across 13 chronic inflammatory diseases.EBioMedicine · 2024Article
- Application of early warning signs to physiological contexts: a comparison of multivariate indices in patients on long-term hemodialysis.Frontiers in network physiology · 2024Article
- Systematic analysis and optimization of early warning signals for critical transitions using distribution data.iScience · 2023Article
- Intercorrelated variability in blood and hemodynamic biomarkers reveals physiological network in hemodialysis patients.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Critical transition theory suggests that complex systems should experience increased temporal variability just before abrupt state changes. We tested this hypothesis in 763 patients on long-term hemodialysis, using 11 biomarkers collected every two weeks and all-cause mortality as a proxy for critical transitions. We find that variability-measured by coefficients of variation (CVs)-increases before death for all 11 clinical biomarkers, and is strikingly synchronized across all biomarkers: the first axis of a principal component analysis on all CVs explains 49% of the variance. This axis then generates powerful predictions of mortality (HR95 = 9.7, p < 0.0001, where HR95 is a scale-invariant metric of hazard ratio; AUC up to 0.82) and starts to increase markedly ∼3 months prior to death. Our results provide an early warning sign of physiological collapse and, more broadly, a quantification of joint system dynamics that opens questions of how system modularity may break down before critical transitions.
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