Glucose concentration predicting mortality in patients with COVID-19: A propensity score-matched study.

Xing Wang, Yue Li, Qiao Wang, Fan Xia, Wuqian Chen, Chao You, Lu Ma
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Abstract

Background: Patients with coronavirus disease-19 (COVID-19) often develop systemic inflammation, which is associated with increased mortality. Elevated blood glucose levels can exacerbate the cytokine storm, further worsening disease severity and accelerating patient death. Therefore, this study aims to investigate the association between glucose levels and mortality in hospitalized patients, providing insights into the importance of optimizing glucose management in hospitalized COVID-19 patients.

Methods: A retrospective cohort study was conducted, involving adult COVID-19 patients in a university hospital. The primary outcome was in-hospital mortality. Propensity score matching (PSM) was utilized to match patients' baseline characteristics. Discrimination capacity of different models was assessed using C-statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Trends in blood glucose over time were detected using the ordinary least squares model.

Results: Among the 4583 COVID-19 patients during the study period, 2147 (46.8%) exhibited normal glycemia, while 2436 (53.2%) had admission hyperglycemia. After adjusting for confounding factors through multivariate regression analysis, patients with hyperglycemia showed significantly higher odds of in-hospital mortality (adjusted odds ratio [aOR]: 3.10, 95% CI: 2.25 to 4.28; P < 0.001). PSM analysis yielded similar results (aOR: 2.66, 95% CI: 2.09 to 3.41; P < 0.001). The incorporation of admission glucose significantly improved C-statistics (P < 0.001), IDI (P < 0.001), and NRI (P < 0.001) for predicting mortality.

Conclusion: This study concludes that blood glucose levels ≥ 6.1 mmol/L can independently predict all-cause mortality and clinical sequelae in COVID-19 patients. Furthermore, even a mild increase in blood glucose was associated with a significantly higher risk of mortality in these patients. These findings underscore the importance of managing hyperglycemia and monitoring blood glucose in individuals with COVID-19.

葡萄糖浓度预测COVID-19患者死亡率:一项倾向评分匹配研究
背景:冠状病毒病-19 (COVID-19)患者经常出现全身性炎症,这与死亡率增加有关。血糖水平升高会加剧细胞因子风暴,进一步恶化疾病严重程度,加速患者死亡。因此,本研究旨在探讨住院患者血糖水平与死亡率之间的关系,为优化住院COVID-19患者血糖管理的重要性提供见解。方法:采用回顾性队列研究,纳入某大学医院的成年COVID-19患者。主要终点是住院死亡率。使用倾向评分匹配(PSM)来匹配患者的基线特征。采用c统计、净重分类改善(NRI)和综合判别改善(IDI)对不同模型的判别能力进行评价。使用普通最小二乘模型检测血糖随时间的变化趋势。结果:研究期间4583例新冠肺炎患者中,血糖正常2147例(46.8%),入院高血糖2436例(53.2%)。通过多因素回归分析调整混杂因素后,高血糖患者的住院死亡率明显高于其他患者(校正优势比[aOR]: 3.10, 95% CI: 2.25 ~ 4.28;P < 0.001)。PSM分析结果相似(aOR: 2.66, 95% CI: 2.09 ~ 3.41;P < 0.001)。纳入入院血糖显著改善了预测死亡率的c统计(P < 0.001)、IDI (P < 0.001)和NRI (P < 0.001)。结论:血糖水平≥6.1 mmol/L可独立预测COVID-19患者的全因死亡率和临床后遗症。此外,在这些患者中,即使是轻微的血糖升高也与死亡风险的显著增加有关。这些发现强调了COVID-19患者控制高血糖和监测血糖的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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