Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients
Diagnostic and prognostic value of hematological and immunological markers in COVID-19 infection: A meta-analysis of 6320 patients
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DOI：
10.1371/journal.pone.0238160
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发表时间：
2020-08-21
期刊：
影响因子：
3.7
通讯作者：
Kandil, Emad
中科院分区：
文献类型：
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作者：
Elshazli, Rami M.;Toraih, Eman A.;Kandil, Emad
目的对2019冠状病毒病（COVID-19）流行相关的血液学和免疫学标志物的诊断和预后价值进行循证表征，对于了解感染的临床过程以及评估生物标志物的开发和验证至关重要。方法基于截至2020年4月22日在Web of Science、PubMed、Scopus和Science Direct中进行的系统检索，共纳入52篇符合条件的文章，涉及6，320例实验室确认的COVID-19队列。对36项实验室指标进行了两两比较，分别是逆转与轻度疾病、重症监护室（ICU）与普通病房、存活者与存活者。使用DerSimonian Laird方法/随机效应模型计算合并的标准化均值差（SMD）和95%置信区间（CI），并转换为比值比（OR）。采用决策树算法识别导致严重COVID-19疾病的关键风险因素。结果白色血细胞（WBC）水平升高的队列（OR = 1.75），中性粒细胞计数（OR = 2.62），D-二聚体（OR = 3.97），凝血酶原时间（PT）延长（OR = 1.82），纤维蛋白原（OR = 3.14）、血沉（OR = 1.60）、降钙素原（OR = 4.76）、IL-6（OR = 2.10）和IL-10（OR = 4.93）进展为重度表型的几率更高。决策树模型（灵敏度= 100%，特异性= 81%）显示，中性粒细胞计数在临界值大于3.74x10（9）/L时，对于识别重度COVID-19高风险患者具有较高的性能。同样，ICU入院与WBC（OR = 5.21）、中性粒细胞（OR = 6.25）、D-二聚体（OR = 4.19）和PT延长（OR = 2.18）水平升高相关。高IL-6（OR = 13.87）、CRP（OR = 7.09）、D-二聚体（OR = 6.36）和中性粒细胞（OR = 6.25）患者的死亡率最高。结论几种血液学和免疫学标志物，特别是嗜中性粒细胞计数，可能有助于纳入COVID-19感染评估的常规面板中，以确保风险分层和有效管理。
Objective Evidence-based characterization of the diagnostic and prognostic value of the hematological and immunological markers related to the epidemic of Coronavirus Disease 2019 (COVID-19) is critical to understand the clinical course of the infection and to assess in development and validation of biomarkers. Methods Based on systematic search in Web of Science, PubMed, Scopus, and Science Direct up to April 22, 2020, a total of 52 eligible articles with 6,320 laboratory-confirmed COVID-19 cohorts were included. Pairwise comparison between severeversusmild disease, Intensive Care Unit (ICU)versusgeneral ward admission and expiredversussurvivors were performed for 36 laboratory parameters. The pooled standardized mean difference (SMD) and 95% confidence intervals (CI) were calculated using the DerSimonian Laird method/random effects model and converted to the Odds ratio (OR). The decision tree algorithm was employed to identify the key risk factor(s) attributed to severe COVID-19 disease. Results Cohorts with elevated levels of white blood cells (WBCs) (OR = 1.75), neutrophil count (OR = 2.62), D-dimer (OR = 3.97), prolonged prothrombin time (PT) (OR = 1.82), fibrinogen (OR = 3.14), erythrocyte sedimentation rate (OR = 1.60), procalcitonin (OR = 4.76), IL-6 (OR = 2.10), and IL-10 (OR = 4.93) had higher odds of progression to severe phenotype. Decision tree model (sensitivity = 100%, specificity = 81%) showed the high performance of neutrophil count at a cut-off value of more than 3.74x10(9)/L for identifying patients at high risk of severe COVID-19. Likewise, ICU admission was associated with higher levels of WBCs (OR = 5.21), neutrophils (OR = 6.25), D-dimer (OR = 4.19), and prolonged PT (OR = 2.18). Patients with high IL-6 (OR = 13.87), CRP (OR = 7.09), D-dimer (OR = 6.36), and neutrophils (OR = 6.25) had the highest likelihood of mortality. Conclusions Several hematological and immunological markers, in particular neutrophilic count, could be helpful to be included within the routine panel for COVID-19 infection evaluation to ensure risk stratification and effective management.