Department of Pathology, Faculty of Medicine, Cairo University, Cairo, Egypt; Department of Pathology, College of Medicine, Qassim University, Buraidah, Qassim, Saudi Arabia.
Chest Diseases Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
J Infect Public Health. 2021 May;14(5):561-569. doi: 10.1016/j.jiph.2021.03.001. Epub 2021 Mar 5.
BACKGROUNDː: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), within few months of being declared as a global pandemic by WHO, the number of confirmed cases has been over 75 million and over 1.6 million deaths since the start of the Pandemic and still counting, there is no consensus on factors that predict COVID-19 case progression despite the diversity of studies that reported sporadic laboratory predictive values predicting severe progression. We review different biomarkers to systematically analyzed these values to evaluate whether are they are correlated with the severity of COVID-19 disease and so their ability to be a predictor for progression.
The current meta-analysis was carried out to identify relevant articles using eight different databases regarding the values of biomarkers and risk factors of significance that predict progression of mild or moderate cases into severe and critical cases. We defined the eligibility criteria using a PICO model.
Twenty-two relevant articles were selected for meta-analysis the following biomarkers C-reactive protein, interleukin-6, LDH, neutrophil, %PD-1 expression, D-dimer, creatinine, AST and Cortisol all recorded high cut-off values linked to severe and critical cases while low lymphocyte count, and low Albumin level were recorded. Also, we meta- analyzed age and comorbidities as a risk factors of progression as hypertension, Diabetes and chronic obstructive lung diseases which significantly correlated with cases progression (p < 0.05).
ː The current meta-analysis is the first step for analysing and getting cut-off references values of significance for prediction COVID-19 case progression. More studies are needed on patients infected with SARS-CoV-2 and on a larger scale to establish clearer threshold values that predict progression from mild to severe cases. In addition, more biomarkers testing also help in building a scoring system for the prediction and guiding for proper timely treatment.
COVID-19 是由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的,在世界卫生组织宣布 COVID-19 成为全球大流行后的短短几个月内,确诊病例数已超过 7500 万,自大流行开始以来,死亡人数已超过 160 万,且仍在不断增加。尽管有许多研究报告了预测严重进展的零星实验室预测值,但对于预测 COVID-19 病例进展的因素仍没有共识。我们综述了不同的生物标志物,系统地分析了这些值,以评估它们是否与 COVID-19 疾病的严重程度相关,以及它们是否能够成为进展的预测指标。
本荟萃分析旨在使用八个不同的数据库确定相关文章,这些文章涉及生物标志物和有意义的危险因素的价值,这些因素可预测轻度或中度病例向严重和危重症病例的进展。我们使用 PICO 模型定义了纳入标准。
共选择了 22 篇相关文章进行荟萃分析,以下生物标志物:C 反应蛋白、白细胞介素-6、乳酸脱氢酶、中性粒细胞、%PD-1 表达、D-二聚体、肌酐、天冬氨酸氨基转移酶和皮质醇均记录了与严重和危重症病例相关的高截断值,而低淋巴细胞计数和低白蛋白水平则与之相关。此外,我们荟萃分析了年龄和合并症作为进展的危险因素,如高血压、糖尿病和慢性阻塞性肺疾病,这些因素与病例进展显著相关(p < 0.05)。
本荟萃分析是分析和获得用于预测 COVID-19 病例进展的有意义的截断值的第一步。需要对感染 SARS-CoV-2 的患者进行更多的研究,并进行更大规模的研究,以建立更清晰的预测从轻度到重度病例进展的阈值。此外,更多的生物标志物检测也有助于建立预测和指导及时适当治疗的评分系统。