全血细胞参数logistic回归模型对放射工作人员辐射损伤的诊断价值

Diagnostic value of whole blood cell parameters logistic regression model for radiation injury on radiation workers

目的通过比较辐射损伤人群与职业性健康体检人群的全血细胞参数,探讨全血细胞参数Logistic回归模型对放射工作人员辐射损伤的诊断价值。方法于2023年2月,回顾性选取2021年7月至2022年7月在我院进行职业健康检查且发生染色体畸变的放射工作人员184例作为辐射损伤组,纳入同期在我院进行职业健康检查且未发生染色体畸变的放射工作人员184例作为对照组,收集两组研究对象的全血细胞参数,进行比较分析,构建logistic回归模型,运用受试者工作特征曲线(ROC)及曲线下面积(AUC)评价logistic回归模型对放射工作人员辐射损伤的诊断价值。再以相同的评定标准,纳入2022年8月至2023年1月在我院进行职业健康检查且发生染色体畸变的放射工作人员60例和未发生染色体畸变的放射工作人员60例作为验证队列,对Logistic回归模型进行验证。结果辐射损伤组中性粒细胞(Neu)_X、Neu_Y、Neu_Z、淋巴细胞(Lym)_X、Lym_Y、Lym_Z、单核细胞(Mon)_X、Mon_Y、Mon_Z、小红细胞(Micro)、平均红细胞血红蛋白浓度(MCHC)水平均明显高于对照组(P<0.05),辐射损伤组平均红细胞体积(MCV)、大红细胞(Macro)水平均明显低于对照组(P<0.05)。logistic回归分析显示Lym_X、Lym_Y、Lym_Z、MCHC、Micro均是诊断放射工作人员辐射损伤的独立影响因素(OR=1.08、1.02、0.99、1.06、51.32,P<0.05)。ROC曲线分析显示,基于Lym_X、Lym_Y、Lym_Z、MCHC、Micro构建的logistic回归模型诊断放射工作人员辐射损伤的AUC为0.80,敏感度为85.9%,特异度为65.8%,准确度为75.9%。验证队列验证logistic回归模型,AUC为0.80,敏感度为81.7%,特异度为71.7%,准确度为76.7%,模型拟合较好。结论辐射损伤会导致放射工作人员多种全血细胞参数发生改变,基于Lym_X、Lym_Y、Lym_Z、MCHC和Micro构建的logistic回归模型对放射工作人员辐射损伤具有良好的诊断价值,可用于放射工作人员辐射损伤的筛查。

ObjectiveTo 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.MethodsIn 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.ResultsNeu_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.ConclusionRadiation 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.