Nature·3 min read·hard

Stress hyperglycemia ratio and glycemic variability for predicting mortality and new-onset rhythm related events in severe heart failure: a multicenter machine-learning cohort study

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Xie, Xun
Stress hyperglycemia ratio and glycemic variability for predicting mortality and new-onset rhythm related events in severe heart failure: a multicenter machine-learning cohort study
AI Summary

A multicenter study using machine learning analyzed the impact of stress hyperglycemia and glycemic variability on mortality and heart rhythm events in elderly heart failure patients. The research suggests that combining these two glucose-related markers provides better prognostic data than using either marker individually.

Why it matters

Improved prognostic tools for heart failure patients can lead to more personalized clinical interventions and better outcomes in intensive care settings.

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Scientific Reports ( 2026 ) Cite this article

We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.

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