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A retrospective analysis reveals a predictor of survival for the patient with paraquat intoxication
Ya-Xiang Song1, Shu-Ling Fan1, Ai Peng1
1Division 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.
Abstract:
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 (R2 = 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.
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