Evidence map›Paper›PMID 40210921›Full record

ArticleScientific reports2025

Combined glycated hemoglobin index and red cell distribution width predict in-hospital mortality in critically ill sepsis patients based on MIMIC-IV analysis.

Huan Xu, Jiaojian Lv, Feifei Lin, Luxiang Liu

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Huan XuDepartment of Infectious Diseases, Lishui People's Hospital, The First Affiliated Hospital of Lishui University, No. 1188 Liyang Street, Lishui, 323000, Zhejiang, China.
Jiaojian LvDepartment of Infectious Diseases, Lishui People's Hospital, The First Affiliated Hospital of Lishui University, No. 1188 Liyang Street, Lishui, 323000, Zhejiang, China.
Feifei LinDepartment of Laboratory Medicine, Lishui People'S Hospital, The First Affiliated Hospital of Lishui University, Lishui, 323000, Zhejiang, China.
Luxiang LiuDepartment of Infectious Diseases, Lishui People's Hospital, The First Affiliated Hospital of Lishui University, No. 1188 Liyang Street, Lishui, 323000, Zhejiang, China. llx_241110@163.com.

Funding

Zhejiang Provincial Health Science and Technology Program Project 2022KY1442
6 · The paper itself

Abstract

Red cell distribution width (RDW) and glycated hemoglobin index (HGI) is considered an important tool for assessing the prognosis of sepsis patients, closely related to the risk of mortality associated with sepsis. This study investigates the association between the HGI combined with RDW and the risk of in-hospital mortality in patients with sepsis. We analyzed data from 13,726 sepsis patients who were admitted to the intensive care unit (ICU) for more than 24 h, sourced from the American Medical Information Mart for Intensive Care (MIMIC-IV) database. Kaplan-Meier survival curves and multivariable Cox regression analyses were employed to assess the impact of various variables on patient outcomes, stratified by quartiles of HGI and RDW. Additionally, restricted cubic spline (RCS) analysis was utilized to explore how changes in HGI and RDW might influence the studied outcomes. The results indicated that the highest quartile (Q4) of the combined metrics significantly increased in-hospital mortality compared to the lowest quartile (Q1) (p < 0.0001). Multivariable Cox regression analysis revealed that patients in Q4 faced the highest risk of in-hospital mortality (hazard ratio: 1.22, 95% confidence interval: [1.10-1.36], p < 0.001). RCS analysis demonstrated a nonlinear relationship between HGI-RDW and the risk of adverse outcomes. Further analysis identified significantly elevated risks in patients over 65 years old, those who were widowed, those receiving macrolide antibiotics, and those with congestive heart failure or severe liver disease. In conclusion, elevated levels of the combined HGI and RDW metrics are independent risk factors for adverse outcomes in critically ill patients with sepsis, associated with increased mortality.

Indexed as

Erythrocyte IndicesGlycated HemoglobinHospital MortalitySepsisAgedCritical IllnessFemaleHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsGlycated HemoglobinGlycated hemoglobin indexMIMIC-IVRed cell distribution widthSepsis

Identifiers

PMID40210921
PMCPMC11986117

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.