Synchrony of biomarker variability indicates a critical transition: Application to mortality prediction in hemodialysis.

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. Ou

SUBMITTER: Cohen AA 

PROVIDER: S-EPMC9127602 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature