艾滋病不同进展类型猴模型平台期指标的判别分析

Discriminant Analysis of Platform Parameters of Rhesus at Different Stages of SIV/SAIDS

【目的】探讨运用判别分析预测健康恒河猴(Normal)和已感染猴免疫缺陷病毒(SIV)的长期不进展(LTNP)、普通进展(NP)、快速进展(RP)4种不同类型恒河猴模型的疾病进展风险。【方法】将实验观察5年的未加干预的艾滋病恒河猴模型,按照生存时间的不同,挑选出符合LTNP、NP、RP特点的3种类型恒河猴各10只,与同期5只健康恒河猴比较,分析比较不同类型间T细胞亚群、中医证候指标的差异,找出不同类型进展风险的影响因素,并建立判别方程对其风险进行预测。【结果】感染前白细胞(WBC)计数和淋巴细胞(LYM)比例进入判别方程,平台期为甲状腺素(T4)水平和平台期Log10RNA进入判别方程。对所建立的判别函数的一致率进行检验,感染前和平台期理论判别与实际资料的总吻合率分别为57.1%和91.2%。【结论】感染前的WBC计数和LYM比例可作为评价不同进展类型的一个参考,而平台期的Log10RNA和T4水平可用于预测不同类型进展的风险。

Objective To predict the disease progression risks of healthy rhesus （ normal） and rhesus infected with simian immunodeficiency virus （ SIV） in the stages of long-term nonprogressor （ LTNP） , normal progressor （ NP） , rapid progressor （ RP） by discriminant analysis. Methods Five-year observation was carried out in SIV infected rhesus model without any intervention. The SIV infected rhesus model at the stages of LTNP, NP, RP were selected, 10 in each group, and T lymphocyte subsets and serum parameters for spleen-deficiency syndrome and kidney-deficiency syndrome in SIV infected rhesus were compared with 5 healthy monkey having the same survival time. The influence factors of different types of disease progression were screened from T cell subsets and Chinese medical syndrome indexes, and then the discriminant equation was established to predict the risks. Results White blood cell （ WBC） count and lymphocyte （ LYM） ratio were enrolled into the discriminant equation before infection, and T4 level and Log10RNA of set point were enrolled into the discriminant equation in the platform period. The test results for the uniform rate of the established discriminant function showed that the total coincidence rate of theoretic distinguish to the actual data was 57.1% , 91.2%respectively before infection and in the platform period. Conclusion The pre-infection WBC count and LYM ratio can be used as a reference for the evaluation of different types of disease progresson, and Log10RNA and T4 level at platform phase can be used as the predicting factors of different types of disease progression risk prediction.