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联合血清中性粒细胞明胶酶相关脂质运载蛋白和胎球蛋白A预测脓毒症患者28天死亡率及风险预测模型构建

Combined Serum NGAL and Fetuin A to Predict 28-Day Mortality in Patients with Sepsis and Risk Prediction Model Construction.

作者信息

Liu Yutong, Bu Lin, Chao Yali, Wang Houqing

机构信息

Department of Intensive Care Unit, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221000, Jiangsu Province, China.

Department of Emergency, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, Jiangsu Province, China.

出版信息

Cell Mol Biol (Noisy-le-grand). 2022 Nov 30;68(11):47-52. doi: 10.14715/cmb/2022.68.11.9.

Abstract

It was to investigate the predictive value of NGAL and Fetuin-A for 28-day mortality in patients with sepsis, and to construct a mortality risk prediction model. 120 patients admitted to The Affiliated Hospital of Xuzhou Medical University Hospital were grouped. Serum biochemical parameters were measured and scale scores were performed. The patient data were divided into a training set and test set in a ratio of 7:3, and the logistic regression model and random forest model were included to evaluate the 28-day mortality prediction efficacy of each index and model. The results showed that WBC, PLT, RBCV, and PLR decreased, SCr, Lac, PCT, D-dimer, NPR, NGAL, and Fetuin-A increased, APACHE II scale, SOFA scale, and OASIS scale scores increased in the death group (P < 0.05). SCr ≥ 408 μmol/L, Lac ≥ 2.3 mmol/L, PCT ≥ 30 ng/mL, D-dimer ≥ 2.33 mg/L, PLR ≥ 190, APACHE II ≥ 18 points, SOFA ≥ 2, OASIS ≥ 30, NGAL ≥ 352 mg/L, and Fetuin-A ≥ 0.32 g/L were found to be risk factors for 28-day death, while WBC ≥ 12 × 109/L, PLT ≥ 172 × 103/μL, and RBCV ≥ 30% were found to be protective factors for 28-day mortality. The predicted AUCs of APACHE II, SOFA, OASIS, NGAL, Fetuin-A, NGAL & Fetuin-A, logistic regression model, and random forest model were 0.80, 0.71, 0.77, 0.69, 0.86, 0.92, 0.83, and 0.81. NGAL combined with Fetuin-A has good prediction efficacy in 28-day mortality in septic patients.

摘要

旨在探讨中性粒细胞明胶酶相关脂质运载蛋白(NGAL)和胎球蛋白A对脓毒症患者28天死亡率的预测价值,并构建死亡风险预测模型。将徐州医科大学附属医院收治的120例患者进行分组。检测血清生化参数并进行量表评分。将患者数据按7:3的比例分为训练集和测试集,纳入逻辑回归模型和随机森林模型以评估各指标及模型对28天死亡率的预测效能。结果显示,死亡组患者的白细胞(WBC)、血小板(PLT)、红细胞体积(RBCV)、血小板与淋巴细胞比值(PLR)降低,血肌酐(SCr)、乳酸(Lac)、降钙素原(PCT)、D-二聚体、中性粒细胞与淋巴细胞比值(NPR)、NGAL、胎球蛋白A升高,急性生理与慢性健康状况评分系统Ⅱ(APACHE II)量表、序贯器官衰竭评估(SOFA)量表、脓毒症器官功能障碍评估(OASIS)量表评分升高(P<0.05)。发现SCr≥408μmol/L、Lac≥2.3mmol/L、PCT≥30ng/mL、D-二聚体≥2.33mg/L、PLR≥190、APACHE II≥18分、SOFA≥2、OASIS≥30、NGAL≥352mg/L、胎球蛋白A≥0.32g/L为28天死亡的危险因素,而WBC≥12×10⁹/L、PLT≥172×10³/μL、RBCV≥30%为28天死亡率的保护因素。APACHE II、SOFA、OASIS、NGAL、胎球蛋白A、NGAL与胎球蛋白A联合、逻辑回归模型、随机森林模型的预测受试者工作特征曲线下面积(AUC)分别为0.80、0.71、0.77、0.69、0.86、0.92、0.83、0.81。NGAL联合胎球蛋白A对脓毒症患者28天死亡率具有良好的预测效能。

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