Abstract
The prognosis of paraquat (PQ) poisoning is highly correlated to plasma PQ concentration, which has been identified as the most important index in PQ poisoning. This study investigated the predictive value of coagulation, liver, and kidney indices in prognosticating PQ-poisoning patients, when aligned with plasma PQ concentrations. Coagulation, liver, and kidney indices were first analyzed by variance analysis, receiver operating characteristic curves, and Fisher discriminant analysis. Then, a new, intelligent, machine learning-based system was established to effectively provide prognostic analysis of PQ-poisoning patients based on a combination of the aforementioned indices. In the proposed system, an enhanced extreme learning machine wrapped with a grey wolf-optimization strategy was developed to predict the risk status from a pool of 103 patients (56 males and 47 females); of these, 52 subjects were deceased and 51 alive. The proposed method was rigorously evaluated against this real-life dataset, in terms of accuracy, Matthews correlation coefficients, sensitivity, and specificity. Additionally, the feature selection was investigated to identify correlating factors for risk status. The results demonstrated that there were significant differences in the coagulation, liver, and kidney indices between deceased and surviving subjects (p<0.05). Aspartate aminotransferase, prothrombin time, prothrombin activity, total bilirubin, direct bilirubin, indirect bilirubin, alanine aminotransferase, urea nitrogen, and creatinine were the most highly correlated indices in PQ poisoning and showed statistical significance (p<0.05) in predicting PQ-poisoning prognoses. According to the feature selection, the most important correlated indices were found to be associated with aspartate aminotransferase, the aspartate aminotransferase to alanine ratio, creatinine, prothrombin time, and prothrombin activity. The method proposed here showed excellent results that were better than that produced based on blood-PQ concentration alone. These promising results indicated that the combination of these indices can provide a new avenue for prognosticating the outcome of PQ poisoning.
Highlights
Paraquat (1,10-dimethyl-4,40-bipyridium dichloride, PQ) has been one of the most widely used, nonselective, contact herbicides since it was first manufactured in 1962 [1]
The input was a combination of coagulation, liver, and kidney indices, and the data were split into a training set and testing set via a 10-fold cross-validation strategy
Coagulation factors I, II, V, VII, and X are synthesized in liver and, liver function was damaged in PQ-poisoned patients
Summary
Paraquat (1,10-dimethyl-4,40-bipyridium dichloride, PQ) has been one of the most widely used, nonselective, contact herbicides since it was first manufactured in 1962 [1] It is safe in agricultural activities, PQ is more toxic to humans than any other herbicidal agent and has caused numerous deaths worldwide [2].After ingestion, PQ is rapidly absorbed and distributed to lung, liver, kidney, and muscle, with a volume of distribution at1.2–1.6 L/kg [3]. Other laboratory examinations, such as coagulation function, hepatic and kidney function tests have been recommended as useful in evaluating PQ poisoning, their prognostic significance has remained unclear. These laboratory examinations have included many indices whose clinical significance resists identification
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