从集合理论和概率理论预测hiv / aids患者外周血中CD4 T淋巴细胞数量

Javier Rodríguez , Signed Prieto , Martha Melo , Darío Domínguez , Catalina Correa , Yolanda Soracipa , Marcela Mejía , Laura Valero , Alejandro Salamanca
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引用次数: 6

摘要

此前,一种基于集合理论和概率的方法得到了改进,目的是从白细胞和淋巴细胞的总数中提高CD4 T细胞(LT-CD4)对艾滋病毒/艾滋病的预测能力。在这项工作中,该方法的临床适用性通过对150个样本的细化预测得到了证明。取每个患者的白细胞/mm3、淋巴细胞/mm3和LT-CD4细胞/mm3的数据,称为三组,根据白细胞的数量从高到低进行组织,以评估1000个白细胞的范围。建立了这两个三元组对集合A∪C, B∪D的隶属关系,以及这两个集合(A∪B)∩(B∪D)之间的交集,从而建立了CD4的数量与白细胞和淋巴细胞的特定值相关的预测。计算属于每个集合的元素数量,并确定属于每个测试范围的概率。在所测量的9个白细胞范围中,共有7个显示成功概率等于或大于0.76,在低于4.000/mm3和3.000/mm3的级别中分别获得1的概率。证明了该方法确定LT-CD4值的能力,比未改进的方法具有更高的预测能力。证据表明,应用的方法是有效的临床应用,从而导致成本和资源的减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicción del número de linfocitos T CD4 en sangre periférica a partir de teoría de conjuntos y probabilidad en pacientes con VIH/SIDA

Previously a refinement of a methodology was developed based on set theory and probability, with the aim of improving the predictive ability of CD4 T cells (LT-CD4) for HIV/AIDS from the total number of leukocytes and lymphocytes. In this work the clinical applicability of the method was shown by refining prediction in 150 samples. Taking data of leukocytes/mm3, lymphocytes/mm3, and LT-CD4 cells/mm3 of each patient, called triples, they were organized from highest to lowest based on the number of leukocytes, to evaluate ranges of 1,000 leukocytes. The membership of the triples to the set A∪C, B∪D was established, as well as the intersection between the two sets (A∪B)∩(B∪D), in which a prediction of the number of CD4 associated with specific values of leukocytes and lymphocytes is established. The number of elements belonging to each set was counted and the probability of belonging to each of the ranges tested was determined. A total of 7 out of the 9 ranges of leukocytes measured showed a probability of success equal to or greater than 0,76, achieving a probability of 1 in the ranks lower than 4.000/mm3 and 3.000/mm3, respectively. The ability of the methodology for determining the value of the LT-CD4 was demonstrated, achieving a higher predictive capacity than the unrefined methodology. The evidence shows that the applied methodology is effective for clinical use, thus leading to a reduction of costs and resources.

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