Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Gao Y

PROVIDER: S-EPMC7794476 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Gao Yanxia Y Liu Liwen L Li Tiegang T Yuan Ding D Wang Yibo Y Xu Zhigao Z Hou Linlin L Zhang Yan Y Duan Guoyu G Sun Changhua C Che Lu L Li Sujuan S Sun Pei P Li Yi Y Ren Zhigang Z

Scientific reports 20210108 1

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 mode ...[more]

PMID: 33420265

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Project description:BackgroundParaquat is a widely used nonselective and fast-acting contact herbicide worldwide. This study identified the early predictor of mortality in patients with acute paraquat poisoning.MethodsTwenty-nine patients with acute paraquat poisoning admitted at Nanjing Drum Tower Hospital from January 2018 to August 2020 were included in this study. The early predictor of mortality in patients with acute paraquat poisoning based on the blood tests was identified by correlation, logistic regression, and receiver operating characteristic (ROC) analyses.Result15 of the 29 patients died after poisoning. Compared to the survivors, the neutrophilic granulocyte ratio, leukocyte count, ALB, and Crea of the nonsurvivors were significantly higher with p value < 0.05, while the lymphocyte ratio and eGFR(MDRD) of the nonsurvivors were remarkably lower with p value < 0.01. Moreover, the neutrophil-to-lymphocyte ratio (NLR) was remarkably upregulated in the nonsurvivors. The area under the ROC curve (AUC) of the neutrophilic granulocyte ratio, lymphocyte ratio, leukocyte count, ALB, Crea, eGFR(MDRD), and NLR to predict the mortality in patients with acute paraquat poisoning was 0.8905 (95% CI: 0.7589-1.022), 0.8643 (95% CI: 0.7244-1.004), 0.8500 (95% CI: 0.7133-0.9867), 0.7286 (95% CI: 0.5338-0.9233), 0.8167 (95% CI: 0.6620-0.9713), 0.8714 (95% CI: 0.7330-1.010), and 0.8667 (95% CI: 0.7277-1.006), respectively. More interestingly, we also evaluated the diagnostic values of the different combinations of six blood test biomarkers by logistic regression analysis. According to the results of the logistic regression analysis, the AUCs for the combination of the neutrophilic granulocyte ratio, leukocyte count, and eGFR(MDRD) were the largest with 0.986 (95% CI: 0.952-1), and the sensitivity and specificity were 100% and 100%.ConclusionThis study demonstrated that the combination of the neutrophilic granulocyte ratio, leukocyte count, and eGFR(MDRD) could serve as an ideal early predictor of mortality in patients with acute paraquat poisoning. However, further research is needed to draw a clear conclusion.

Project description:ObjectiveThe chest computed tomography (CT) examination is an important clinical examination in the diagnosis and monitoring of paraquat- (PQ-) induced lung injury. The aim of this study was to explore the prognostic value of the average lung CT number acquired by quantitative CT techniques in patients with acute paraquat poisoning in the early stages of the disease.Methods46 patients who suffered from acute PQ poisoning in the emergency department of the Nanjing Drum Tower Hospital from January 2015 to June 2020 were enrolled in the present study. The patients were divided into survival group (n = 21) and nonsurvival group (n = 25). Clinical data were collected from subjects who met the inclusion criteria, including general information, personal disease history, and laboratory test indicators. The average lung CT numbers of each patient were obtained by quantitative CT techniques. Receiver operating characteristic (ROC) analysis was conducted to assess the prognostic value of average lung CT number in patients with acute paraquat poisoning.ResultsThe average CT numbers of the middle-lung, lower-lung, and whole lung fields in the nonsurvival group were significantly higher than those of the survival group (p < 0.0001). However, the upper-lung field was not significantly different between the two groups (p = 0.7765). The AUCs of different levels ranged from 0.554 to 0.977, among which the lower-lung field presented the largest AUC of 0.977 (95% CI: 0.943∼1; cut-off value: -702Hu; sensitivity 96%; specificity, 90.5%; YI: 0.865), followed by the whole lung field 0.914 (95% CI: 0.830∼0.999; cut-off value: -727Hu; sensitivity 76%; specificity, 95.2%; YI: 0.712) and the middle-lung field 0.87 (95% CI: 0.768∼0.971; cut-off value: -779Hu; sensitivity 80%; specificity, 85.7%; YI: 0.657).ConclusionThe present study indicated that the average lung CT number could be used to evaluate the relationship between the severity of PQ-induced lung injury and prognosis, especially in the lower-lung field. However, further research is needed to draw a clear conclusion.

Dataset Information

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

Publications

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

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