Author:
Liu Shuo-Lin,Feng Bao-Yu,Song Qi-Rui,Zhang Ying-Mei,Wu Shuo-Ling,Cai Jun
Abstract
Abstract
Background
This study aimed to examine whether the neutrophil to high-density lipoprotein cholesterol ratio (NHR) can predict cardiovascular outcomes in normoglycemic individuals with elevated fasting glucose levels.
Methods
A total of 130,801 participants with normal blood glucose levels were enrolled in the Kailuan study. Participants were categorized according to NHR quartiles and further divided into normal glucose regulation (NGR) and pre-diabetes (pre-DM) subgroups. The follow-up endpoint was major adverse cardiovascular events (CVE), including stroke and myocardial infarction.
Results
Over a median of 12.53 (8.95–13.08) years of follow-up, subjects with NHR levels in the highest quartile experienced more CVE than those with NHR levels in the lowest quartile. Multivariate Cox analyses showed that continuous changes in NHR (hazard ratio, 1.21; 95% confidence interval [CI], 1.15–1.28) and the highest quartile of NHR (hazard ratio, 1.30; 95% CI, 1.21–1.39) were independent predictors of CVE (all P < 0.001). Furthermore, when participants were categorized by both NHR quartile and glucose metabolism status, the NHR level in the highest quartile plus pre-DM group was associated with a 1.60-fold (95% CI, 1.38–1.86; P < 0.001] higher risk of CVE than that in the lowest quartile plus normoglycemic group. Significantly, the addition of NHR only, presence of pre-DM only, or combination of NHR and pre-DM to the prediction algorithm, including traditional risk factors, improved the C-statistic by 0.19, 0.05, and 0.23 (all P < 0.001).
Conclusions
Elevated NHR or fasting blood glucose level were independently associated with a higher risk of CVE among normoglycemic individuals. Moreover, pre-DM participants with high NHR levels tended to have worse prognosis, suggesting that NHR could provide greater risk stratification value than traditional risk factors for subjects with pre-DM.
Funder
CAMS Innovation Fund for Medical Sciences
National Natural Science Foundation of China
Beijing Outstanding Young Scientist Program
Capital Clinical Diagnosis and Treatment Technology Research and Demonstration Application Project of Beijing Science and Technology Commission
AI+ Health Collaborative Innovation Cultivation Project of Beijing Science and Technology Commission
Publisher
Springer Science and Business Media LLC
Subject
Biochemistry (medical),Clinical Biochemistry,Endocrinology,Endocrinology, Diabetes and Metabolism
Cited by
6 articles.
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