Song Ya-Xiang, Fan Shu-Ling, Peng Ai, Shen Shijun, Cheng Jia-Fen, Chen Guang-Qi, Li Chang-Bin, Jiang Cizhong, Li Xin-Hua, Liu Jun-Yan
Division of Nephrology and Rheumatology, Shanghai Tenth People's Hospital, Shanghai 200072, China; Center for Nephrology and Metabolomics, Tongji University School of Medicine, Shanghai, 200072, China.
The School of Life Sciences and Technology, Shanghai Key Laboratory of Signaling and Disease Research, Tongji University, Shanghai 200092, China.
Clin Chim Acta. 2020 Dec;511:269-277. doi: 10.1016/j.cca.2020.10.027. Epub 2020 Oct 22.
Feasible and accurate predictors are urgently needed to evaluate the survival for patients with paraquat poisoning since the high mortality of paraquat poisoning always resulted in the loss of both life and money. Multiple predictors have been developed to predict prognosis of the patients with PQ poisoning, which however heavily depend on the time of admission to hospitals. Here we reported a feasible and accurate prognosis predictor for patients with paraquat poisoning that is independent of the time of admission to hospitals. Patients with paraquat poisoning were enrolled in this study according to the inclusion and exclusion criteria, which were grouped into survivors and non-survivors based on the 90-days follow-up investigation. The concentration of paraquat in serum and urine, and the baseline clinical parameters associated with the injuries of the liver, kidney, and lung were evaluated to predict the survival of these patients by using receiver operating characteristic curve (ROC) analysis, univariate and multivariate cox regression analyses. A total of 114 patients was included in this study with a survival rate of 54.4%. The median survival days of non-survivors were 6.0 (95%Cl: 4.0-7.8). A new predictor, namely paraquat concentration-associated multiorgan injury index (PCAMII), was established by integrating serum and urine paraquat concentration, serum creatinine, alanine aminotransferase, aspartate transaminase, total and direct bilirubin, at different weighting coefficients, with the accuracy of about 90%. The model to predict the survival probability by PCAMII was established with good fitness (R = 0.9325), providing the simulated survival rates comparable to the clinical data. PCAMII, which is independent of hospital admission time, is a feasible and accurate marker to predict the survival rate of patients with PQ poisoning.
由于百草枯中毒死亡率高，常导致生命和金钱损失，因此迫切需要可行且准确的预测指标来评估百草枯中毒患者的生存率。已经开发了多种预测指标来预测百草枯中毒患者的预后，但这些指标很大程度上依赖于入院时间。在此，我们报告了一种可行且准确的百草枯中毒患者预后预测指标，该指标与入院时间无关。根据纳入和排除标准，将百草枯中毒患者纳入本研究，并根据90天随访调查将其分为幸存者和非幸存者。通过使用受试者工作特征曲线（ROC）分析、单因素和多因素Cox回归分析，评估血清和尿液中百草枯的浓度以及与肝、肾和肺损伤相关的基线临床参数，以预测这些患者的生存情况。本研究共纳入114例患者，生存率为54.4%。非幸存者的中位生存天数为6.0（95%CI：4.0-7.8）。通过将血清和尿液中百草枯浓度、血清肌酐、丙氨酸氨基转移酶、天冬氨酸氨基转移酶、总胆红素和直接胆红素以不同加权系数整合，建立了一种新的预测指标，即百草枯浓度相关多器官损伤指数（PCAMII），其准确率约为90%。建立了用PCAMII预测生存概率的模型，拟合良好（R = 0.9325），提供的模拟生存率与临床数据相当。PCAMII与入院时间无关，是预测百草枯中毒患者生存率的可行且准确的标志物。
