Stress hyperglycemia ratio improves machine learning-based mortality risk prediction in critically ill COVID-19 patients: a multicenter retrospective study

Abstract Background The stress hyperglycemia ratio (SHR), which quantifies the degree of acute hyperglycemia relative to a patient’s chronic glycemic background, serves as a biomarker reflecting acute metabolic dysregulation, yet its association with mortality among critical ill COVID-19 patients re...

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मुख्य लेखकों:	Jiaxing Du, Keze Ma, Zhiwei Ye, Juanli Song, Sujun Chen, Jie Yu, Bing Liu, Zixuan Jiang, Fen Zhang
स्वरूप:	Artigo
भाषा:	Inglês
प्रकाशित:	BMC 2026-01-01
श्रृंखला:	BMC Infectious Diseases
विषय:	Stress hyperglycemia ratio COVID-19 Critical ill Mortality Machine learning
ऑनलाइन पहुंच:	https://doi.org/10.1186/s12879-025-12376-2
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