Evidence map›Paper›PMID 41309783›Full record

ArticleScientific reports2025

The additive effect of hemoglobin glycation index and glycemic variability to predict mortality in cardiac intensive care patients with and without diabetes.

Jinhui Zhang, Zhenkui Hu, Chao Song

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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. Not yet cited in PubMed.

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5 · Who and what money

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3 authors.

Jinhui ZhangDepartment of Critical Care Medicine, The Affiliated Hospital, Jiangsu University, No.438 Jiefang Road, Zhenjiang, 212001, Jiangsu, China. 1000012402@ujs.edu.cn.
Zhenkui HuDepartment of Emergency Medicine, The Affiliated Hospital, Jiangsu University, No.438 Jiefang Road, Zhenjiang, 212001, Jiangsu, China.
Chao SongDepartment of Emergency Medicine, The Affiliated Hospital, Jiangsu University, No.438 Jiefang Road, Zhenjiang, 212001, Jiangsu, China. songchao2002@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The hemoglobin glycation index (HGI) and glycemic variability (GV) are important metabolic markers associated with cardiovascular diseases and their prognoses. However, the potential additive effect of these biomarkers on mortality risk remains unclear. This study aimed to investigate the independent and combined effects of HGI and GV on mortality in cardiac ICU patients, both with and without diabetes. We conducted a retrospective cohort analysis of 1636 individuals admitted to the cardiac ICU. The primary outcome was 28-day mortality, with 365-day mortality as a secondary endpoint. Kaplan-Meier survival curves, Cox proportional hazards models, restricted cubic splines, receiver operating characteristic (ROC) curve, and subgroup analyses were used to evaluate the relationship between the HGI and adverse outcomes. During the follow-up period, 163 patients (10.0%) died within 28 days, and 322 patients (19.7%) died within 365 days. ROC analysis showed that the combination of HGI and GV had better predictive accuracy for mortality compared to HGI alone (28-day mortality: 0.658 vs. 0.621, P = 0.025; 365-day mortality: 0.644 vs. 0.562, P < 0.001) and GV alone (28-day mortality: 0.658 vs. 0.622, P = 0.036; 365-day mortality: 0.644 vs. 0.618, P = 0.031). Among non-diabetic patients, low HGI combined with high GV was linked to the highest mortality risk at both 28 days (HR = 4.223, 95% CI: 2.336-7.634) and 365 days (HR = 2.504, 95% CI: 1.550-4.045). However, diabetic patients with low HGI and low GV had the greatest risk of death at 28 days (HR = 3.729, 95% CI: 1.747-7.959) and 365 days (HR = 2.287, 95% CI: 1.324-3.951). The results suggested a potential additive effect of HGI and GV on mortality risk at both 28-day and 365-day in cardiac ICU patients, regardless of diabetes status. This combined biomarker approach may guide personalized glycemic management and improve clinical outcomes.

Indexed as

Blood GlucoseCardiovascular DiseasesDiabetes MellitusGlycated HemoglobinAgedBiomarkersCritical CareFemaleHumansIntensive Care UnitsKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsRetrospective StudiesBiomarkersBlood GlucoseGlycated HemoglobinCardiac ICUGlycemic variabilityHemoglobin glycation indexMIMIC-IV databaseMortality

Identifiers

PMID41309783
PMCPMC12660922

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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.