Clinical Laboratory Parameters Associated with Severe or Critical Novel Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-analysis

Abstract

Background: To date, several clinical laboratory parameters associated with COVID-19 severity have been reported. However, these parameters have not been observed consistently across studies. The aim of this review was to assess clinical laboratory parameters which may serve as markers or predictors of severe or critical COVID-19 disease Methods: We conducted a systematic search of MEDLINE, Embase, Web of Science, CINAHL and Google Scholar databases from 2019 through April 18, 2020, and reviewed bibliographies of eligible studies, relevant systematic reviews, and the medRxiv pre-print server. We included hospital-based observational studies reporting clinical laboratory parameters of confirmed cases of COVID-19 and excluded studies having large proportions (>10%) of children and pregnant women. Two authors independently carried out screening of articles, data extraction and quality assessment. Meta-analyses were done using random effects model. Meta-median difference (MMD) and 95% confidence interval (CI) was calculated for each laboratory parameter. Results:Forty-five studies in 6 countries were included. Compared to non-severe COVID-19 cases, severe or critical COVID-19 disease was characterised by higher neutrophil count (MMD:1.23 [95% CI: 0.58 to 1.88] ×10 9 cells/L), and lower lymphocyte and CD4 counts with MMD (95% CI) of -0.39 (-0.47, -0.31) ×10 9 cells/L and -204.9 (-302.6, -107.1) cells/μl, respectively.Other notable results were observed for C-reactive protein (MMD: 36.97 [95% CI: 27.58, 46.35] mg/L), interleukin-6 (MMD: 17.37 [95% CI: 4.74, 30.00] pg/ml,), Troponin I (MMD: 0.01 [0.00, 0.02] ng/ml), and D-dimer (MMD: 0.65 [0.45, 0.85] mg/ml).

Clinical laboratory parameters associated with severe or critical novel coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis

“…We registered our study protocol with the International Prospective Register of Systematic Reviews (PROSPERO); registration number CRD42020176651 [ 17 ]. This review and meta-analysis was conducted and has been reported according to The Preferred Reporting Items for Systematic Reviews and Meta- Analyses (PRISMA) statement and Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines [ 18 , 19 ].…”

Association between markers of immune response at hospital admission and COVID‐19 disease severity and mortality: A meta‐analysis and meta‐regression

“…Additional sensitivity analyses were performed by excluding studies with a high risk of bias and studies with confidence intervals not overlapping with the 95% CIs of the pooled estimates (ie, "outlier studies"). 11 To account for Type I error rate for multiple hypothesis testing (ie, 27 and 23 laboratory markers for disease severity and mortality, respectively), Bonferroni correction was used to declare the significance levels of P values. 24 The Bonferroni corrected P value for the disease severity tests including overall estimates, sensitivity analysis by the risk of duplicates, and sensitivity analysis by the risk of bias was .002 (ie, corrected P = .05/27) and for sensitivity analysis of outliers, where only 15 laboratory markers were tested, was .003 (ie, corrected P = .05/15).…”

“…[7][8][9] These disease processes can be monitored using various biochemical and hematologic markers that are routinely measured at the time of hospitalization, potentially contributing to the accurate prediction of severity and mortality among patients hospitalized for COVID-19 and allowing for early intervention. 10,11 However, the development of useful predictive tools incorporating laboratory parameters will require studies with large sample sizes covering broad population groups to be accurate and generalizable. Usually, individual studies are small and hence meta-analyses could provide critical evidence needed for clinical and policy decisions.…”

“…To date, meta-analyses assessing the impact of COVID-19 on laboratory markers have suffered from various methodological and reporting issues, including a lack of consideration for potentially overlapping datasets, incorrect estimation of study means and error, and not including data on mortality. 10,11 In addition, given the importance of age and sex as predictors of disease severity, the contribution of these factors to any associations between laboratory parameters and COVID-19 severity has not received adequate attention. 2,10,11 To resolve these limitations, we first conducted a systematic review and meta-analysis on the association between admission laboratory values and disease severity and mortality in patients hospitalized for COVID-19.…”

“…10,11 In addition, given the importance of age and sex as predictors of disease severity, the contribution of these factors to any associations between laboratory parameters and COVID-19 severity has not received adequate attention. 2,10,11 To resolve these limitations, we first conducted a systematic review and meta-analysis on the association between admission laboratory values and disease severity and mortality in patients hospitalized for COVID-19. We then assessed the contributions of age and sex to the observed associations using meta-regression techniques.…”