Diagnostic and prognostic value of diquat plasma concentration and complete blood count in patients with acute diquat poisoning based on random forest algorithms.
Currently, the incidence of diquat (DQ) poisoning is increasing, and quickly predicting the prognosis of poisoned patients is crucial for clinical treatment. In this study, a total of 84 DQ poisoning patients were included, with 38 surviving and 46 deceased. The plasma DQ concentration of DQ poisone...
| Publicado en: | Human & Experimental Toxicology Vol. 43; pp. 1 - 10 |
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| Autores principales: | , , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
Nov2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=190862394&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 190862394 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09603271 DZA jtl: Human & Experimental Toxicology issn: 09603271 maglogo: Y pubinfo: dt: Nov2024 vid: 43 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 190862394 190862394 190862394 10.1177/09603271241276981 190862394 ppf: 1 ppct: 9 formats: tig: atl: Diagnostic and prognostic value of diquat plasma concentration and complete blood count in patients with acute diquat poisoning based on random forest algorithms. aug: au: Hu, Hui Ke, Xiaofang Zheng, Fangfang You, Minjie Zhou, Tao Xu, Yanwen Wu, Jiaiying Tong, Shuhua Hu, Lufeng affil: Department of Pharmacy, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China sug: subj: Herbicides Blood Herbicides Poisoning Poisoning Diagnosis Poisoning Prognosis Blood Cell Count Early Diagnosis Random Forest Prediction Algorithms China Funding Source Human Male Female Adolescence Adult Middle Age Aged Aged, 80 and Over Retrospective Design Record Review Liquid Chromatography-Mass Spectrometry Autoanalyzers Predictive Value of Tests Leukocyte Count Neutrophils Spearman's Rank Correlation Coefficient Support Vector Machine Decision Trees ROC Curve T-Tests Descriptive Statistics Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Aged, 80 & over Male Female ab: Currently, the incidence of diquat (DQ) poisoning is increasing, and quickly predicting the prognosis of poisoned patients is crucial for clinical treatment. In this study, a total of 84 DQ poisoning patients were included, with 38 surviving and 46 deceased. The plasma DQ concentration of DQ poisoned patients, determined by liquid chromatography-mass spectrometry (LC-MS) were collected and analyzed with their complete blood count (CBC) indicators. Based on DQ concentration and CBC dataset, the random forest of diagnostic and prognostic models were established. The results showed that the initial DQ plasma concentration was highly correlated with patient prognosis. There was data redundancy in the CBC dataset, continuous measurement of CBC tests could improve the model's predictive accuracy. After feature selection, the predictive accuracy of the CBC dataset significantly increased to 0.81 ± 0.17, with the most important features being white blood cells and neutrophils. The constructed CBC random forest prediction model achieved a high predictive accuracy of 0.95 ± 0.06 when diagnosing DQ poisoning. In conclusion, both DQ concentration and CBC dataset can be used to predict the prognosis of DQ treatment. In the absence of DQ concentration, the random forest model using CBC data can effectively diagnose DQ poisoning and patient's prognosis. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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