Dataset Information

Development and Validation of a Radiomics Nomogram for Prognosis Prediction of Patients with Acute Paraquat Poisoning: A Retrospective Cohort Study.

ABSTRACT:

Objective

To evaluate the efficiency of a radiomics model in predicting the prognosis of patients with acute paraquat poisoning (APP).

Materials and methods

Chest computed tomography images and clinical data of 80 patients with APP were obtained from November 2014 to October 2017, which were randomly assigned to a primary group and a validation group by a ratio of 7?:?3, and then the radiomics features were extracted from the whole lung. Principal component analysis (PCA) and least absolute shrinkage and selection operator (LASSO) regression were used to select the features and establish the radiomics signature (Rad-score). Multivariate logistic regression analysis was used to establish a radiomics prediction model incorporating the Rad-score and clinical risk factors; the model was represented by nomogram. The performance of the nomogram was confirmed by its discrimination and calibration.

Result

The area under the ROC curve of operation was 0.942 and 0.865, respectively, in the primary and validation datasets. The sensitivity and specificity were 0.864 and 0.914 and 0.778 and 0.929, and the prediction accuracy rates were 89.5% and 87%, respectively. Predictors included in the individualized predictive nomograms include the Rad-score, blood paraquat concentration, creatine kinase, and serum creatinine. The AUC of the nomogram was 0.973 and 0.944 in the primary and validation datasets, and the sensitivity and specificity were 0.943 and 0.955, respectively, in the primary dataset and 0.889 and 0.929 in the validation dataset, and the prediction accuracy was 94.7% and 91.3%, respectively.

Conclusion

The radiomics nomogram incorporates the radiomics signature and hematological laboratory data, which can be conveniently used to facilitate the individualized prediction of the prognosis of APP patients.

SUBMITTER: Lu S

PROVIDER: S-EPMC7872759 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Development and Validation of a Radiomics Nomogram for Prognosis Prediction of Patients with Acute Paraquat Poisoning: A Retrospective Cohort Study.

Lu Shan S Gao Duo D Wang Yanling Y Feng Xuran X Zhang Yongzhi Y Li Ling L Geng Zuojun Z

BioMed research international 20210202

<h4>Objective</h4>To evaluate the efficiency of a radiomics model in predicting the prognosis of patients with acute paraquat poisoning (APP).<h4>Materials and methods</h4>Chest computed tomography images and clinical data of 80 patients with APP were obtained from November 2014 to October 2017, which were randomly assigned to a primary group and a validation group by a ratio of 7 : 3, and then the radiomics features were extracted from the whole lung. Principal component analysis (PCA) and leas ...[more]

PMID: 33604379

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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.

Dataset Information

Development and Validation of a Radiomics Nomogram for Prognosis Prediction of Patients with Acute Paraquat Poisoning: A Retrospective Cohort Study.

Objective

Materials and methods

Result

Conclusion

Publications

Development and Validation of a Radiomics Nomogram for Prognosis Prediction of Patients with Acute Paraquat Poisoning: A Retrospective Cohort Study.

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