Increased plasma prothrombin time is associated with poor prognosis in patients with paraquat poisoning

Hu, Xiao; Guo, Renyong; Chen, Xing; Chen, Yu

doi:10.1002/jcla.22597

Cited by 5 publications

(6 citation statements)

References 30 publications

(47 reference statements)

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“…Laboratory profiles and their effects on the prognosis of patients with paraquat poisoning were reported in limited studies [11,16,17]. Some studies demonstrated that increased leukocyte, prothrombin rate, the blood, and urine concentration of creatinine, pancreatic enzymes, and arterial lactate had a poor prognosis in paraquat poisoning [10,11].…”

Section: Prognostic Factorsmentioning

confidence: 99%

“…Moreover, the main laboratory findings include leukocytosis, anemia, acute hepatitis with the rise of alanine transaminase and aspartate transaminase, increased serum bilirubin, and creatinine [5,14]. Significant complications of paraquat poisoning are pulmonary, cardiovascular, hepatic, renal, coagulation, and fibrinolysis dysfunctions due to cell damage [11,[15][16]. Additionally, progressive lung injury and acute renal failure are the main causes of death in paraquat poisoning [11,16].…”

Section: Clinical and Laboratory Findings And Complicationsmentioning

confidence: 99%

“…Significant complications of paraquat poisoning are pulmonary, cardiovascular, hepatic, renal, coagulation, and fibrinolysis dysfunctions due to cell damage [11,[15][16]. Additionally, progressive lung injury and acute renal failure are the main causes of death in paraquat poisoning [11,16].…”

Section: Clinical and Laboratory Findings And Complicationsmentioning

confidence: 99%

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Therapeutic Strategies in Managing Acute Paraquat Poisoning: A Review Study

Majidi

2021

IJMTFM

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Background: Paraquat is an extremely toxic herbicide that causes such severe adverse effects as acute lung injury, pulmonary fibrosis, metabolic acidosis, cardiogenic shock, acute renal failure, and even death. Regarding the high prevalence and mortality rate without a specific antidote in paraquat poisoning, we explored managing acute paraquat poisoning. Methods: In this study, required articles were searched using the following keywords: “paraquat poisoning” and “treatment” on an electronic database, such as Pubmed and Google Scholar from January 2013 to December 2020. Results: This article examined pharmacokinetic, clinical, and laboratory findings, complications, diagnosis, prognostic factors, and the treatment of paraquat poisoning. Then, the medical management and therapeutic procedures of paraquat poisoning were discussed. Conclusion: Although there exists no antidote for paraquat poisoning, numerous therapeutic methods have been suggested for treating paraquat poisoning. However, their efficacy remains undiscovered. An interesting finding in one study indicating that endotracheal intubation is an inappropriate procedure for managing paraquat poisoning; further studies are required in this regard. For these reasons, preventing poisoning and using other herbicides with less toxicity than paraquat are recommended.

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Section: Prognostic Factorsmentioning

confidence: 99%

Section: Clinical and Laboratory Findings And Complicationsmentioning

confidence: 99%

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Therapeutic Strategies in Managing Acute Paraquat Poisoning: A Review Study

Majidi

2021

IJMTFM

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“…To our knowledge, several prognostic score systems have been reported to predict the clinical outcomes of patients with PQ poisoning, the major ones being the Acute Physiology and Chronic Health Evaluation II (APACHE II) score [7], Sequential Organ Failure Assessment (SOFA) score [8], the severity index of PQ poisoning (SIPP) [9], Poisoning Severity Score (PSS) [10] and some equations and nomograms based on large cohort study [11][12][13]. Most of them are more suitable for critically ill patients instead of minimally poisoned or early-stage patients who showed mild symptoms.…”

Section: Introductionmentioning

confidence: 99%

A Novel and Simple Risk Model Predicts the Prognosis for Patients with Paraquat Poisoning

Gao

Liu

Li³

et al. 2020

SSRN Journal

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Background: Acute paraquat (PQ) poisoning is characterized by multi-organ failure and lacking effective therapies. Therefore, identifying risk factors and developing model that could predict early prognosis for patients with PQ poisoning is of great importance. Methods: This 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. Results: 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 (Cr) were identified as in dependent 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. Conclusion: Eight risk factors 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 simple and reliable risk score system could be helpful in recognizing high-risk patients and reducing in-hospital death rate due to PQ poisoning.

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“…To our knowledge, several systems have been reported to predict the prognosis of patients with PQ poisoning, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score 7 , Sequential Organ Failure Assessment (SOFA) score 8 , the Severity Index of PQ Poisoning (SIPP) 9 , Poisoning Severity Score (PSS) 10 , and several equations and nomograms based on large cohort studies [11][12][13] . Most of these models are suitable for critically ill patients rather than patients with minimal exposure or early-stage patients with mild symptoms.…”

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confidence: 99%

A novel simple risk model to predict the prognosis of patients with paraquat poisoning

Gao

Liu

et al. 2021

Sci Rep

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To identify risk factors and develop a simple model to predict early prognosis of acute paraquat (PQ) poisoning patients, we performed a retrospective cohort study of acute PQ poisoning patients (n = 1199). Patients (n = 913) with PQ poisoning from 2011 to 2018 were randomly divided into training (n = 609) and test (n = 304) samples. Another two independent cohorts were used as validation samples for a different time (n = 207) and site (n = 79). Risk factors were identified using a logistic model with Markov Chain Monte Carlo (MCMC) simulation and further evaluated using a latent class analysis. The prediction score was developed based on the training sample and was evaluated using the testing and validation samples. Eight factors, including age, ingestion volume, creatine kinase-MB [CK-MB], platelet [PLT], white blood cell [WBC], neutrophil counts [N], gamma-glutamyl transferase [GGT], and serum creatinine [Cr] were identified as independent risk indicators of in-hospital death events. The risk model had C statistics 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 predictive ranges of 4.6–98.2%, 2.3–94.9%, and 0–12.5% for the test, validation_time, and validation_site samples, respectively. In the training sample, 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. We developed and evaluated a simple risk model to predict the prognosis of patients with acute PQ poisoning. This risk scoring system could be helpful for identifying high-risk patients and reducing mortality due to PQ poisoning.

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Increased plasma prothrombin time is associated with poor prognosis in patients with paraquat poisoning

Abstract: Coagulation status in patients with PQ poisoning was closely related to prognosis. Routine monitoring of coagulation function, particularly PT in plasma, is helpful for analysis of the condition and prognosis of patients with PQ poisoning.

Cited by 5 publications

References 30 publications

Therapeutic Strategies in Managing Acute Paraquat Poisoning: A Review Study

Therapeutic Strategies in Managing Acute Paraquat Poisoning: A Review Study

A Novel and Simple Risk Model Predicts the Prognosis for Patients with Paraquat Poisoning

A novel simple risk model to predict the prognosis of patients with paraquat poisoning

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