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中性粒细胞与淋巴细胞比值和血小板与淋巴细胞比值可预测埃塞俄比亚新冠肺炎患者的病情严重程度:一项回顾性研究

Neutrophil-to-Lymphocyte Ratio and Platelet-to-Lymphocyte Ratio Can Predict the Severity in COVID-19 Patients from Ethiopia: A Retrospective Study.

作者信息

Ayalew Getnet, Mulugeta Birhan, Haimanot Yeabfekad, Adane Tiruneh, Bayleyegn Biruk, Abere Aberham

机构信息

Department of Medical Microbiology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

Department of Immunology and Molecular Biology, School of Biomedical and Laboratory Sciences, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.

出版信息

Int J Gen Med. 2022 Oct 7;15:7701-7708. doi: 10.2147/IJGM.S383558. eCollection 2022.

Abstract

BACKGROUND

Coronaviruses are a broad family of pathogens that can cause mild to severe respiratory illnesses. Due to a strong inflammatory response and a weak immunological response, viral pneumonia inflammation, like Coronavirus Disease 2019 (COVID-19), displays an unbalanced immune response. Therefore, circulating biomarkers of inflammation and the immune system can serve as reliable predictors of a patient's prognosis for COVID-19. Hematological ratios are reliable markers of inflammation that are frequently utilized in pneumonia, primarily in viral infections with low cost in developing countries.

PURPOSE

To examine the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) in predicting the severity of COVID-19 patients.

METHODS

An institutional-based retrospective study was done on 105 hospitalized COVID-19 patients at the University of Gondar comprehensive specialized referral hospital, Northwest Ethiopia. The laboratory evaluations that were gathered, evaluated, and reported on included the total leucocyte count (TLC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute monocyte count (AMC), NLR, LMR, and PLR. The Kruskal-Wallis test and Wilcoxon matched-pairs signed test were used to see whether there were any differences between the continuous variables. Receiver operating curve (ROC) analysis was used to determine the appropriate cut-off values for NLR, PLR, and LMR. -value <0.05 was considered a statistically significant association.

RESULTS

ANC, NLR, and PLR were highest in the critical group (p = 0.001), while this group had the least ALC and LMR (p = 0.001). We calculated the optimal cut-off values of the hematological ratios; NLR (8.4), LMR (1.4), and PLR (18.0). NLR had the highest specificity and sensitivity, at 83.8% and 80.4%, respectively.

CONCLUSION

Our research showed that NLR and PLR were good indicators of severity in COVID-19. However, our findings indicate that MLR is not a reliable predictor.

摘要

背景

冠状病毒是一类广泛的病原体,可导致从轻度到重度的呼吸道疾病。由于强烈的炎症反应和较弱的免疫反应,病毒性肺炎炎症,如2019冠状病毒病(COVID-19),表现出免疫反应失衡。因此,炎症和免疫系统的循环生物标志物可作为COVID-19患者预后的可靠预测指标。血液学比值是炎症的可靠标志物,在肺炎中经常使用,主要用于发展中国家成本较低的病毒感染。

目的

研究中性粒细胞与淋巴细胞比值(NLR)、淋巴细胞与单核细胞比值(LMR)和血小板与淋巴细胞比值(PLR)在预测COVID-19患者病情严重程度方面的作用。

方法

在埃塞俄比亚西北部贡德尔大学综合专科医院对105例住院的COVID-19患者进行了一项基于机构的回顾性研究。收集、评估和报告的实验室评估指标包括白细胞总数(TLC)、绝对中性粒细胞计数(ANC)、绝对淋巴细胞计数(ALC)、绝对单核细胞计数(AMC)、NLR、LMR和PLR。采用Kruskal-Wallis检验和Wilcoxon配对符号检验来观察连续变量之间是否存在差异。采用受试者工作特征曲线(ROC)分析来确定NLR、PLR和LMR的合适截断值。P值<0.05被认为具有统计学意义。

结果

危重组的ANC、NLR和PLR最高(P = 0.001),而该组的ALC和LMR最低(P = 0.001)。我们计算了血液学比值的最佳截断值;NLR(8.4)、LMR(1.4)和PLR(18.0)。NLR的特异性和敏感性最高,分别为83.8%和80.4%。

结论

我们的研究表明,NLR和PLR是COVID-19病情严重程度的良好指标。然而,我们的研究结果表明,MLR不是一个可靠的预测指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b7b6/9553031/54c336f2702b/IJGM-15-7701-g0001.jpg

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