[全血细胞参数逻辑回归模型对辐射工作人员辐射伤害的诊断价值]。

Z Zhu, G K Sun, Q R He, Z Y Li, Y Ma, Y P Chen
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引用次数: 0

摘要

目的通过比较职业性放射损伤人群与职业健康检查人群全血细胞参数的差异,探讨全血细胞参数逻辑回归模型对放射工作人员放射损伤的诊断价值。方法:2023年2月,回顾性选取2021年7月至2022年7月在我院接受职业健康检查并发生染色体畸变的184名放射工作人员作为放射损伤组。另选取同期未发生染色体畸变的 184 名放射工作人员作为对照组。收集两组研究对象的全血细胞参数,进行对比分析,构建逻辑回归模型,并通过接收者操作特征曲线(ROC)和曲线下面积(AUC)评估逻辑回归模型对辐射工作人员辐射损伤的诊断价值。此外,在同一标准下,将 2022 年 8 月至 2023 年 1 月期间 60 名染色体畸变的放射工作人员和 60 名染色体未畸变的放射工作人员纳入验证队列,以验证逻辑回归模型。结果辐射损伤组Neu_X、Neu_Y、Neu_Z、Lym_X、Lym_Y、Lym_Z、Mon_X、Mon_Y、Mon_Z、Micro、MCHC显著高于对照组,差异有统计学意义(PPOR=1.08、1.02、0.99、1.06、51.32,PConclusion:辐射损伤可引起辐射工作人员全血细胞多项指标的变化。基于Lym_X、Lym_Y、Lym_Z、MCHC和Micro的逻辑回归模型显示出良好的诊断能力,可用于辐射工作人员辐射损伤的筛查。
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[Diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers].

Objective: To explore the diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers by comparing the differences of whole blood cell parameters between occupational radiation injury population and occupational health examination population. Methods: In February 2023, 184 radiation workers who received occupational health examinations in our hospital and occurrenced chromosome aberration from July 2021 to July 2022 were retrospectively selected as the radiation injury group. And other 184 radiation workers encountered in the same period without chromosome aberration occurrence were selected as the control group. Collected whole blood cell parameters from two groups of research subjects, conducted comparative analysis, constructed a logistic regression model, and evaluated the diagnostic value of the logistic regression model for radiation injury on radiation workers by receiver operating characteristic curve (ROC) and area under curve (AUC) . In addition, with the same standard, 60 radiation workers with chromosome aberration and 60 radiation workers without chromosome aberration from August 2022 to January 2023 were included in the validation queue to validate the logistic regression model. Results: Neu_X, Neu_Y, Neu_Z, Lym_X, Lym_Y, Lym_Z, Mon_X, Mon_Y, Mon_Z, Micro, MCHC in the radiation injury group were significantly higher than those in the control group, and the difference was statistically significant (P<0.05) . And MCV and Macro in the radiation injury group were lower than those in the control group, and the difference was statistically significant (P<0.05) . Moreover, logistic regression analysis showed that Lym_X, Lym_Y, Lym_Z, MCHC, Micro were all independent risk factors for diagnosing radiation injury on radiation workers (OR=1.08、1.02、0.99、1.06、51.32, P<0.05) . ROC curve analysis showed that the AUC, sensitivity, specificity, and accuracy of the logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro in diagnosing radiation injury on radiation workers were 0.80, 85.9%, 65.8% and 75.9% respectively. The validation queue verified the logistic regression model and the AUC, sensitivity, specificity, and accuracy of the logistic regression model were 0.80, 81.7%, 71.7% and 76.7% respectively, the model fitted well. Conclusion: Radiation damage can cause changes in multiple whole blood cell parameters of radiation workers. The logistic regression model based by Lym_X, Lym_Y, Lym_Z, MCHC and Micro showed good diagnosis ability and can be used for the screening of radiation injury on radiation workers.

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来源期刊
中华劳动卫生职业病杂志
中华劳动卫生职业病杂志 Medicine-Medicine (all)
CiteScore
1.00
自引率
0.00%
发文量
9764
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