作为严重登革热预测指标的血液学参数:来自西孟加拉邦北部地区的一项研究。

IF 0.8 4区 医学 Q4 INFECTIOUS DISEASES Journal of Vector Borne Diseases Pub Date : 2024-12-05 DOI:10.4103/JVBD.JVBD_119_24
Sudipta K Roy, Bappaditya Ghosh, Ayan Chakraborty, Santanu Hazra, Bidyut K Goswami, Soumen Bhattacharjee
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引用次数: 0

摘要

背景目标:在过去两年中,由于登革热病毒(DENV)的单一和多种血清型以及继发性感染,登革热病例有所增加,最终导致印度大量住院和死亡。本研究的重点是评估西孟加拉邦北部急性登革热患者的症状和血液学参数,以早期预测疾病严重程度,并分析循环登革热病毒血清型与严重程度之间的相关性。方法:540例确诊为NS1阳性的登革热患者中,重度DHF占13.7% (N=74),轻度DF占86.3% (N=466),采用logistic回归进行风险预测。从血液中分离DENV RNA,转化为cDNA,利用DENV特异性引物进行RT-qPCR检测/血清分型。结果:仅有14.48% (N=11)的患者出现登革热单一血清型(DENV2或DENV3)感染。相比之下,登革热患者中存在多血清型感染(N=65), DENV2和DENV3合并感染的流行,影响了最关键的血液学参数(如血细胞比容和血小板计数)的严重变化。多元二元logistic回归模型显示,只有6个参数,即年龄(p=0.032)、关节疼痛(p=0.015)、血红蛋白水平(p=0.015)。解释结论:最常见的DENV2和DENV3感染显著影响研究地区的红细胞压积和血小板计数。我们的预测模型结合了年龄、关节疼痛、血红蛋白、红细胞、白细胞和淋巴细胞,可以有效地预测登革热的严重程度。
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Haematological parameters as predictors of severe dengue: a study from northern districts of West Bengal.

Background objectives: A hike in dengue cases was recorded in last two years, resulting from both single and multiple-serotypes of dengue virus (DENV) and secondary infections, culminating in significant hospitalizations and deaths in India. This study focuses on evaluating symptomatic and haematological parameters in acute dengue patients of the northern part of West Bengal to predict disease severity early on and also to analyze the correlation between circulating DENV serotypes with severity.

Methods: Dengue patients (N=540) diagnosed as NS1 positives were categorized into 13.7% severe DHF (N=74) and 86.3% mild DF (N=466) and prediction of risk was done using logistic regression. DENV RNA was isolated from blood, converted to cDNA, and detected/serotyped via RT-qPCR by using DENV specific primers.

Results: Only 14.48% (N=11) patients showed single serotypic (DENV2 or DENV3) infection of dengue. In contrast, multi-serotypic infections (N=65) with the prevalence of DENV2 and DENV3 co-infections were found among the dengue patients, affecting severe changes in the most critical haematological parameters such as hematocrit and platelet count. The multivariate binary logistic regression model revealed that only six parameters viz., age (p=0.032), presence of joint pain (p=0.015), Haemoglobin level (p<0.001), total RBC count (p=0.024), total WBC count (p=0.003), lymphocyte% (p=0.019) were found to be significantly associated with the risk of DHF.

Interpretation conclusion: Most prevalent DENV2 and DENV3 infections significantly impact hematocrit and platelet counts in the study region. Our prediction model, incorporating age, joint pain, hemoglobin, RBC, WBC, and lymphocyte, may effectively predict dengue severity.

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来源期刊
Journal of Vector Borne Diseases
Journal of Vector Borne Diseases INFECTIOUS DISEASES-PARASITOLOGY
CiteScore
0.90
自引率
0.00%
发文量
89
审稿时长
>12 weeks
期刊介绍: National Institute of Malaria Research on behalf of Indian Council of Medical Research (ICMR) publishes the Journal of Vector Borne Diseases. This Journal was earlier published as the Indian Journal of Malariology, a peer reviewed and open access biomedical journal in the field of vector borne diseases. The Journal publishes review articles, original research articles, short research communications, case reports of prime importance, letters to the editor in the field of vector borne diseases and their control.
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