Predictive Value of Glycemic Variability and HDL-C for Secondary Persistent Inflammatory Immunosuppressed Catabolic Syndrome in Patients with Sepsis

血糖变异性和高密度脂蛋白胆固醇对脓毒症患者继发性持续性炎症免疫抑制分解代谢综合征的预测价值

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Abstract

PURPOSE: Sepsis patients with persistent inflammation, immunosuppression, and catabolism syndrome (PICS) have a poor prognosis, and early detection of biomarkers to predict its prognosis is particularly important. The purpose of this study is to investigate the predictive value of glycemic variability (GV) and high density lipid-cholesterol (HDL-C) for secondary PICS in patients with sepsis. PATIENTS AND METHODS: One hundred and sixty-five patients with sepsis were enrolled in the retrospective study and divided into sepsis secondary PICS and non-PICS group. The daily blood glucose levels from 1 to 7 days after the diagnosis of sepsis were recorded, and GV was calculated. Logistic regression was used to analyze the risk factors of sepsis with PICS, receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of GV, and HDL-C for the prognosis of sepsis with PICS. RESULTS: In a study of 165 patients, PICS group tended to have higher GV and lower HDL-C levels than those in the non-PICS group. Logistic regression analysis identified GV and HDL-C as independent risk factors for the secondary PICS of sepsis. The results of ROC curve showed that GV and HDL-C had a certain predictive value for the secondary PICS of sepsis, the sensitivity of GV was 77.5%, specificity of 81.8%, the sensitivity of HDL-C was 76.6%, and specificity of 74.8%. CONCLUSION: GV and HDL are risk factors for PICS secondary to sepsis and have predictive value for patients' prognosis.

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