Binhai County People's Hospital, Kangda College of Nanjing Medical University, Yancheng, Jiangsu Province, People's Republic of China.
Clin Exp Med. 2024 Aug 7;24(1):183. doi: 10.1007/s10238-024-01450-9.
An increasing number of studies have reported the close relation of the hemoglobin glycation index (HGI) with metabolism, inflammation, and disease prognosis. However, the prognostic relationship between the HGI and patients with sepsis remains unclear. Thus, this study aimed to analyze the association between the HGI and all-cause mortality in patients with sepsis using data from the MIMIC-IV database. In this study, 2605 patients with sepsis were retrospectively analyzed. The linear regression equation was established by incorporating glycated hemoglobin (HbA1c) and fasting plasma glucose levels. Subsequently, the HGI was calculated based on the difference between the predicted and observed HbA1c levels. Furthermore, the HGI was divided into the following three groups using X-tile software: Q1 (HGI ≤ - 0.50%), Q2 (- 0.49% ≤ HGI ≤ 1.18%), and Q3 (HGI ≥ 1.19%). Kaplan-Meier survival curves were further plotted to analyze the differences in 28-day and 365-day mortality among patients with sepsis patients in these HGI groups. Multivariate corrected Cox proportional risk model and restricted cubic spline (RCS) were used. Lastly, mediation analysis was performed to assess the factors through which HGI affects sepsis prognosis. This study included 2605 patients with sepsis, and the 28-day and 365-day mortality rates were 19.7% and 38.9%, respectively. The Q3 group had the highest mortality risk at 28 days (HR = 2.55, 95% CI: 1.89-3.44, p < 0.001) and 365 days (HR = 1.59, 95% CI: 1.29-1.97, p < 0.001). In the fully adjusted multivariate Cox proportional hazards model, patients in the Q3 group still displayed the highest mortality rates at 28 days (HR = 2.02, 95% CI: 1.45-2.80, p < 0.001) and 365 days (HR = 1.28, 95% CI: 1.08-1.56, p < 0.001). The RCS analysis revealed that HGI was positively associated with adverse clinical outcomes. Finally, the mediation effect analysis demonstrated that the HGI might influence patient survival prognosis via multiple indicators related to the SOFA and SAPS II scores. There was a significant association between HGI and all-cause mortality in patients with sepsis, and patients with higher HGI values had a higher risk of death. Therefore, HGI can be used as a potential indicator to assess the prognostic risk of death in patients with sepsis.
越来越多的研究报告血红蛋白糖化指数 (HGI) 与代谢、炎症和疾病预后密切相关。然而，HGI 与脓毒症患者的预后关系尚不清楚。因此，本研究旨在使用 MIMIC-IV 数据库中的数据分析 HGI 与脓毒症患者全因死亡率之间的关系。在这项研究中，回顾性分析了 2605 例脓毒症患者。通过纳入糖化血红蛋白 (HbA1c) 和空腹血糖水平建立线性回归方程。随后，根据预测和观察到的 HbA1c 水平之间的差异计算 HGI。此外，使用 X-tile 软件将 HGI 分为以下三组：Q1（HGI≤-0.50%）、Q2（-0.49%≤HGI≤1.18%）和 Q3（HGI≥1.19%）。进一步绘制 Kaplan-Meier 生存曲线，分析这些 HGI 组中脓毒症患者 28 天和 365 天死亡率的差异。使用多变量校正 Cox 比例风险模型和限制性立方样条 (RCS)。最后，进行中介分析以评估 HGI 通过哪些因素影响脓毒症的预后。本研究纳入了 2605 例脓毒症患者，28 天和 365 天的死亡率分别为 19.7%和 38.9%。Q3 组在 28 天（HR=2.55，95%CI：1.89-3.44，p<0.001）和 365 天（HR=1.59，95%CI：1.29-1.97，p<0.001）的死亡率最高。在完全调整的多变量 Cox 比例风险模型中，Q3 组患者在 28 天（HR=2.02，95%CI：1.45-2.80，p<0.001）和 365 天（HR=1.28，95%CI：1.08-1.56，p<0.001）的死亡率仍然最高。RCS 分析显示 HGI 与不良临床结局呈正相关。最后，中介效应分析表明，HGI 可能通过与 SOFA 和 SAPS II 评分相关的多个指标影响患者的生存预后。HGI 与脓毒症患者的全因死亡率之间存在显著关联，HGI 值较高的患者死亡风险更高。因此，HGI 可作为评估脓毒症患者死亡预后风险的潜在指标。
