The relationship between the lipid profiles and inflammation in patients with sepsis
10.3760/cma.j.cn121430-20211105-01646
- VernacularTitle:脓毒症患者血脂与炎症因子水平的相关性研究
- Author:
Ya'nan XU
1
;
Dong WANG
;
Huan LIU
;
Xianfei DING
;
Xiaojuan ZHANG
;
Shaohua LIU
;
Tongwen SUN
Author Information
1. 郑州大学第一附属医院综合 ICU，河南省重症医学重点实验室，郑州市脓毒症重点实验室，河南省重症医学工程研究中心，郑州 450052
- Keywords:
Sepsis;
Blood lipid;
Inflammatory factor;
Prognosis
- From:
Chinese Critical Care Medicine
2022;34(2):127-132
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the relationship between the changes in the lipid profiles and the intensity of inflammatory response and disease severity in patients with sepsis, in order to find a biomarker that can quickly evaluate the condition and prognosis of sepsis.Methods:A retrospective analysis was performed on 449 patients with sepsis admitted to department of critical care medicine of the First Affiliated Hospital of Zhengzhou University from October 2019 to May 2021, and 355 patients without sepsis hospitalized in the same period served as the control. The general demographic data, blood lipid and other clinical indicators within 24 hours after admission were collected and compared between the two groups. Bivariate correlation study was used to analyze the relationship between blood lipid levels and inflammation indicators and severity of illness in patients with sepsis. The receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of each blood lipid component on the 28-day mortality of patients with sepsis. According to the results of ROC curve analysis, the blood lipids were divided into two groups with different levels, and the Kaplan-Meier survival curve was used to compare the cumulative survival rates of the two groups without end-point event (the 28-day mortality was the end-point event).Results:Compared with non-septic patients, the levels of plasma total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were significantly lower in patients with sepsis [TC (mmol/L): 2.93±1.33 vs. 4.01±1.14, HDL-C (mmol/L): 0.78±0.47 vs. 1.16±0.40, LDL-C (mmol/L): 1.53±1.00 vs. 2.71±0.98, all P < 0.05]. In patients with sepsis, plasma cholesterol levels were correlated with the degree of inflammation and severity of the disease to varying degrees, but the HDL-C had the strongest correlation with interleukin-6 (IL-6; r = -0.551, P = 0.000), procalcitonin (PCT, r = -0.598, P = 0.000), sequential organ failure assessment (SOFA; r = -0.285, P = 0.000). The ROC curve analysis showed that among all blood lipid components, HDL-C had the highest predictive value for 28-day mortality of sepsis patients, and the area under the ROC curve (AUC) was 0.718, when the best cut-off value was 0.69 mmol/L, the sensitivity and specificity were 67.3% and 65.2% respectively, and the positive predictive value and negative predictive value were 60.6% and 71.5% respectively. According to Kaplan-Meier survival curve analysis, the mortality of sepsis patients with HDL-C ≤ 0.69 mmol/L was significantly higher than the patients with HDL-C > 0.69 mmol/L, and the difference was statistically significant ( P < 0.000 1). In addition, the 28-day mortality [59.73% (135/226) vs. 28.70% (64/223)], the incidence of multiple organ dysfunction [41.15% (93/226) vs. 31.84% (71/223)], the probability of requiring mechanical ventilation and vasoactive drugs [mechanical ventilation: 56.64% (128/226) vs. 46.18% (103/223); vasoactive drugs: 54.42% (123/226) vs. 38.57% (86/223)], the positive rate of microbial culture [45.58% (103/226) vs. 35.43% (79/223)], and the probability of drug-resistant bacteria [19.91% (45/226) vs. 10.31% (23/223)] in the low HDL-C group of sepsis patients were all higher than the high HDL-C group, the differences were statistically significant (all P < 0.05). Conclusions:Plasma cholesterol levels, especially the HDL-C levels, can well reflect the intensity of inflammation and the severity of the disease in patients with sepsis. And the HDL-C levels can be used as a good biomarker for predicting the short-term prognosis of sepsis.
