首页> 外文期刊>Journal of Biosciences and Medicines >Glutathione Reductase, Liver Transaminases and Atypical Lymphocytes Count as Early Predictive Biomarkers in Diagnosis of Thrombocytopenia in Dengue Viral Infection
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Glutathione Reductase, Liver Transaminases and Atypical Lymphocytes Count as Early Predictive Biomarkers in Diagnosis of Thrombocytopenia in Dengue Viral Infection

机译:谷胱甘肽还原酶,肝脏转氨酶和非典型淋巴细胞计数作为早期预测生物标志物在登革热病毒感染中血小板减少症的诊断

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Objective: The aim of the study is to identify whether Atypical Lymphocyte (AL), liver transaminases, and Glutathione Reductase (GR) can be used as potential biomarkers in the assessment of severity and thrombocytopenia in dengue. Methods: A cross-sectional analytical study was carried out on diagnosed dengue patients admitted to Nawaloka Hospital, Sri Lanka. Blood samples were taken from patients (n = 50) on the day of admission, 3~(rd) and 5~(th) day from admission for analysis of GR, aspartate transaminase, alanine transaminase, platelets, white blood cells, and Atypical Lymphocytes (AL). Results: GR level of all three measured stages had a higher area under the curve (>88%), high sensitivity and specificity compared to liver transaminases. A significant regression model represents on admission GR and AL levels as predictive variables to platelet levels in day 03 from admission (Day 3 Platelet level = 127155.3 - 383 * GR - 0.431 * AL). Conclusion: Liver transaminases, GR, and AL% can be considered as a profile of predictive biomarkers in early diagnosis of severity of dengue infection. The degree of thrombocytopenia can be predicted using on admission GR and AL% level in acute dengue viral infection.
机译:目的:该研究的目的是鉴定非典型淋巴细胞(A1),肝脏转氨酶和谷胱甘肽还原酶(GR)可用作潜在的生物标志物,以评估登革热的严重程度和血小板减少症。方法:对斯里兰卡纳瓦卢卡医院诊断的登革艇患者进行了横截面分析研究。血液样品在入院时从患者(n = 50)取出,3〜(RD)和5〜(th)日入院,用于分析GR,天冬氨酸转氨酶,丙氨酸转氨酶,血小板,白细胞和非典型淋巴细胞(AL)。结果:与肝脏转氨酶相比,所有三个测量阶段的GR水平在曲线(> 88%)下具有更高的区域,高灵敏度和特异性。一个显着的回归模型代表入院GR和Al水平,作为入院第03天的血小板水平的预测变量(第3天血小板级= 127155.3-383 * GR-0.431 * Al)。结论:肝脏转氨酶,GR和Al%可被认为是预测生物标志物在早期诊断中预测生物标志物的概况,诊断了登革症感染严重程度。可以在急性登革热病毒感染中预测血小板减少程度的血小板减少程度。

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