Correlation Between Severity of Illness and Levels of Free Triiodothyronine, Interleukin-6, and Interleukin-10 in Patients with Acute Pancreatitis.
Correlation Between Severity of Illness and Levels of Free Triiodothyronine, Interleukin-6, and Interleukin-10 in Patients with Acute Pancreatitis.
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急性胰腺炎患者病情严重程度与游离三碘甲状腺原氨酸、白细胞介素 6 和白细胞介素 10 水平的相关性
DOI：
10.12659/msm.933230
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发表时间：
2022-01-24
期刊：
影响因子：
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通讯作者：
Pan X
中科院分区：
文献类型：
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作者：
Tian F;Tian F;Tian F;Lin T;Lin T;Lin T;Zhu Q;Zhu Q;Zhu Q;Wan Y;Wan Y;Wan Y;Wu Z;Wu Z;Wu Z;Lv S;Lv S;Lv S;Song J;Song J;Song J;Li R;Li R;Li R;Wang Y;Wang Y;Wang Y;Zhang Y;Zhang Y;Zhang Y;Yan X;Yan X;Yan X;Pan X;Pan X;Pan X
研究背景急性胰腺炎（acute pancreatitis，AP）是一种常见的急腹症.快速评估AP的严重程度对AP的预后和治疗具有重要意义。游离三碘甲状腺原氨酸（fT 3）水平与AP患者的预后有关。本研究旨在探讨急性胰腺炎患者的fT 3水平;炎症的早期预警信号，包括白细胞介素-6（IL-6）和白细胞介素-10（IL-10）;以及fT 3水平与疾病严重程度的相关性。材料/方法入选的AP患者（N=312）根据亚特兰大分类法（Revision of Atlanta）分为SAP组（N=92）和非SAP组（N=220）。记录血液或组织样本和基线临床特征。采用t检验和卡方检验评估两组之间的差异。采用多因素Logistic回归分析和受试者工作特征曲线（ROC）分析保护因素。采用单因素重复测量方差分析评价SAP患者的预后。结果与APACHII评分（AUC 0.829 [95%CI0.769 -0.889]）和兰森评分（AUC 0.629 [95%CI0.542 -0.715]）相比，我们的预测模型（AUC 0.918 [95%CI0.875 -0.961]）在预测不良患者预后方面具有更好的性能。SAP组fT 3水平变化与预后显著相关（P<0.05）。结论该预测模型可提高诊断准确率和预测疾病严重程度。FT 3水平可作为预测SAP患者死亡率的独立危险因素。
Background Acute pancreatitis (AP) is a common acute abdominal disease. Rapid evaluation of the severity is important for AP prognosis and treatment. Free triiodothyronine (fT3) level is associated with the prognosis of AP patients. This study aimed to investigate the fT3 level in patients with acute pancreatitis; early warning signs of inflammation, including interleukin-6 (IL-6) and interleukin-10 (IL-10); and the correlation of fT3 level with illness severity. Material/Methods Enrolled AP patients (N=312) were divided into an SAP group (N=92) and a non-SAP group (N=220) according to the Revision of Atlanta classification. Blood or tissue samples and baseline clinical characteristics were recorded. The t test and chi-square test were used to evaluate differences between the 2 groups. Multivariate logistic regression analysis and receiver operating characteristic (ROC) curves were used to investigate protective factors. One-way repeated measures analysis of variance was used to evaluate the prognosis of SAP patients. Results In our study, compared with APACHII score (AUC 0.829 [95% CIs 0.769–0.889]) and Ranson score (AUC 0.629 [95% CIs 0.542–0.715]), our predictive model (AUC 0.918 [95% CIs 0.875–0.961]) showed better prognostic performance in predicting poor patient outcomes. In the SAP group, changes in fT3 level were significantly associated with prognosis (P<0.05). Conclusions The predictive model can improve the diagnostic accuracy and prediction of the severity of disease. FT3 level could be used as an independent risk factor to predict the mortality of SAP patients.