Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning

Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning

Abstract Background The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourable prognosis, and abnormal GV is prevalent...

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Bibliographic Details
Main Authors: Yang Chen, Zhengkun Yang, Yang Liu, Ying Gue, Ziyi Zhong, Tao Chen, Feifan Wang, Garry McDowell, Bi Huang, Gregory Y. H. Lip
Format: Article
Language:English
Published: BMC 2024-11-01
Series:Cardiovascular Diabetology
Subjects:
Glycaemic variability
Atrial fibrillation
Intensive care unit
Mortality
Machine learning
Online Access:https://doi.org/10.1186/s12933-024-02521-7
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https://doi.org/10.1186/s12933-024-02521-7

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