当前位置: X-MOL 学术J. Adv. Res. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A decision support scheme for beta thalassemia and HbE carrier screening.
Journal of Advanced Research ( IF 11.4 ) Pub Date : 2020-04-24 , DOI: 10.1016/j.jare.2020.04.005
Reena Das 1 , Saikat Datta 2 , Anilava Kaviraj 3 , Soumendra Nath Sanyal 4 , Peter Nielsen 4 , Izabela Nielsen 4 , Prashant Sharma 1 , Tanmay Sanyal 5 , Kartick Dey 6 , Subrata Saha 4
Affiliation  

The most effective way to combat β-thalassemias is to prevent the birth of children with thalassemia major. Therefore, a cost-effective screening method is essential to identify β-thalassemia traits (BTT) and differentiate normal individuals from carriers. We considered five hematological parameters to formulate two separate scoring mechanisms, one for BTT detection, and another for joint determination of hemoglobin E (HbE) trait and BTT by employing decision trees, Naïve Bayes classifier, and Artificial neural network frameworks on data collected from the Postgraduate Institute of Medical Education and Research, Chandigarh, India. We validated both the scores on two different data sets and found 100% sensitivity of both the scores with their respective threshold values. The results revealed the specificity of the screening scores to be 79.25% and 91.74% for BTT and 58.62% and 78.03% for the joint score of HbE and BTT, respectively. A lower Youden's index was measured for the two scores compared to some existing indices. Therefore, the proposed scores can obviate a large portion of the population from expensive high-performance liquid chromatography (HPLC) analysis during the screening of BTT, and joint determination of BTT and HbE, respectively, thereby saving significant resources and cost currently being utilized for screening purpose.

中文翻译:


β 地中海贫血和 HbE 携带者筛查的决策支持方案。



对抗β地中海贫血最有效的方法是预防重型地中海贫血儿童的出生。因此,一种经济高效的筛查方法对于识别β地中海贫血特征(BTT)并区分正常个体和携带者至关重要。我们考虑了五个血液学参数来制定两种独立的评分机制,一种用于 BTT 检测,另一种用于通过采用决策树、朴素贝叶斯分类器和人工神经网络框架对从收集的数据进行联合测定血红蛋白 E (HbE) 性状和 BTT印度昌迪加尔医学教育与研究研究生院。我们在两个不同的数据集上验证了这两个分数,发现这两个分数与其各自的阈值的敏感性均为 100%。结果显示,BTT 筛查评分的特异性分别为 79.25% 和 91.74%,HbE 和 BTT 联合评分的特异性分别为 58.62% 和 78.03%。与一些现有指数相比,这两个分数的约登指数较低。因此,所提出的评分可以使大部分人群在 BTT 筛查以及 BTT 和 HbE 联合测定过程中免于进行昂贵的高效液相色谱 (HPLC) 分析,从而节省目前用于 BTT 的大量资源和成本。筛选目的。
更新日期:2020-04-24
down
wechat
bug