Establishment Of Risk Scoring Model For Acute Paraquat Poisoning And Cross-region Validation

ObjectiveThe mortality of acute paraquat poisoning is high and the prognosis is poor.It is of great clinical significance to screen the independent risk factors that can predict the risk of in-hospital death of acute paraquat poisoning and establish a simple and practical risk scoring model of acute paraquat poisoning for the prognosis evaluation of acute paraquat poisoning patients.MethodsThis was a retrospective cohort study employed with patients suffered from acute PQ poisoning(n=1199).Patients(n=913)with PQ poisoning from 2011 to 2018 were randomly divided into 2 mutually exclusive groups:training(609 patients)and test(304 patients).Another 2 external cohorts containing 207 cases from Zhengzhou 2019 were used as validation from different time and 79 from Shenyang as validation from different site.Risk factors were identified by a logistic model with Markov Chain Monte Carlo(MCMC)simulation and further evaluated by a latent class analysis.The prediction score of this model was developed based on the training sample and was further evaluated using the testing and validation samples.ResultsA total of 1199(609 training,304 test,207 validation by time,and 79 validation by site)participants were enrolled.The mean(SD)age was 35.1(16.4)years old and 599 patients(50.0%)were female.The rates of in-hospital death were 40.6%(95%CI,36.6%-44.6%)and 38.5%(95%CI,33.0%-44.2%)respectively for the training and test samples.The average in-hospital death was 37.9%.Eight risk factors including age,ingestion volume,CK-MB,platelet(PLT),white blood cell(WBC),neutrophil-counts(N),gamma-glutamyl transferase(GGT)and serum creatinine(sCr)were identified as independent risk indicators of in-hospital death events.The risk model had a C statistic of 0.895(95%CI 0.855-0.928),0.891(95%CI 0.848-0.932)and 0.829(95%CI 0.455-1.000)and a predictive range of 4.6%-98.2%,2.3%-94.9%and 0%-12.5%for the test,validation_time and validation_site group,respectively.In the training group,the risk model classified 18.4%,59.9%and 21.7%of patients into the high,average and low-risk groups,with corresponding probabilities of 0.985,0.365,and 0.03 for in-hospital death events.In the validation_time group,27.1%,59.4%and 13.5%were classified into the low-,average-and high-risk groups,respectively,with corresponding probabilities of 0.03,0.38and 0.98 for in-hospital death events.In the validation site group,36.7%,60.8%and 2.5%were classified into low-,average-and high-risk groups,with a correspondence probability of 0.03,0.33 and 0.97 respectively.The probabilities for in-hospital death events were identical to the training group.ConclusionsEight independent risk factors that can predict the risk of in-hospital death of acute paraquat poisoning were identified in this study.And we developed and evaluated a simple risk model to predict the prognosis of patients with acute PQ poisoning.This risk scoring model has realized cross-time validation and cross-region validation,which shows the universality of the model.This simple and reliable risk score system could be helpful in recognizing high-risk patients and reducing in-hospital death rate due to PQ poisoning.