Diagnostic and prognostic value of diquat plasma concentration and complete blood count in patients with acute diquat poisoning based on random forest algorithms.

Hui Hu, Xiaofang Ke, Fangfang Zheng, Minjie You, Tao Zhou, Yanwen Xu, Jiaiying Wu, Shuhua Tong, Lufeng Hu
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Abstract

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.

基于随机森林算法的急性敌草快中毒患者敌草快血浆浓度和全血细胞计数的诊断和预后价值。
目前,敌草快(DQ)中毒的发病率不断上升,快速预测中毒患者的预后对临床治疗至关重要。本研究共纳入 84 例 DQ 中毒患者,其中 38 例存活,46 例死亡。通过液相色谱-质谱法(LC-MS)测定DQ中毒患者的血浆DQ浓度,并结合患者的全血细胞计数(CBC)指标进行分析。根据 DQ 浓度和全血细胞计数数据集,建立了诊断和预后模型的随机森林。结果显示,初始 DQ 血浆浓度与患者预后高度相关。CBC 数据集存在数据冗余,连续测量 CBC 检测可提高模型的预测准确性。经过特征选择后,CBC 数据集的预测准确率显著提高至 0.81 ± 0.17,其中最重要的特征是白细胞和中性粒细胞。所构建的 CBC 随机森林预测模型在诊断 DQ 中毒时的预测准确率高达 0.95 ± 0.06。总之,DQ 浓度和 CBC 数据集均可用于预测 DQ 治疗的预后。在没有 DQ 浓度的情况下,使用 CBC 数据的随机森林模型可以有效诊断 DQ 中毒和患者的预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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