Dataset Information

Value of leukocytosis and elevated C-reactive protein in predicting severe coronavirus 2019 (COVID-19): A systematic review and meta-analysis.

ABSTRACT:

Background

Since December 2019, coronavirus 2019 (COVID-19) has spread worldwide. Identifying poor prognostic factors is helpful for risk stratification. In this meta-analysis, we investigated the association between severe COVID-19 and a change in white blood cell (WBC) count, an elevation of C-reactive protein (CRP), and fever. Moreover, we aimed to evaluate the diagnostic accuracy of leukocytosis and an elevation of CRP.

Methods

We performed a systematic search of PubMed, EMBASE, Scopus, and the Cochrane Library through April 20th, 2020. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. A sensitivity analysis was conducted according to the study size (>200 or <200) and median age (>55 or <55). Meta-regression analyses were conducted to examine possible sources of heterogeneity. We calculated the diagnostic accuracy of leukocytosis and CRP.

Results

Eighteen studies with 3278 patients were selected. Fever, leukocytosis, and elevated CRP were associated with poor outcomes (OR (95% CI) 1.63 (1.06-2.51), 4.51 (2.53-8.04), and 11.97 (4.97-28.8), respectively). Leukopenia was associated with a better prognosis (OR 0.56, 95% CI 0.40-0.78). Sensitivity analyses showed similar tendencies. Meta-regression analysis for leukocytosis indicated that age, dyspnea, and hypertension contributed to heterogeneity. The pooled area under the leukocytosis and CRP curves were 0.70 (0.64-0.76) and 0.89 (0.80-0.99), respectively.

Conclusion

In patients with COVID-19, fever, leukocytosis, and an elevated CRP were associated with severe outcomes. Leukocytosis and CRP on arrival may predict poor outcomes.

SUBMITTER: Yamada T

PROVIDER: S-EPMC7832771 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Value of leukocytosis and elevated C-reactive protein in predicting severe coronavirus 2019 (COVID-19): A systematic review and meta-analysis.

Yamada Takayuki T Wakabayashi Mako M Yamaji Takahiro T Chopra Nitin N Mikami Takahisa T Miyashita Hirotaka H Miyashita Satoshi S

Clinica chimica acta; international journal of clinical chemistry 20200610

<h4>Background</h4>Since December 2019, coronavirus 2019 (COVID-19) has spread worldwide. Identifying poor prognostic factors is helpful for risk stratification. In this meta-analysis, we investigated the association between severe COVID-19 and a change in white blood cell (WBC) count, an elevation of C-reactive protein (CRP), and fever. Moreover, we aimed to evaluate the diagnostic accuracy of leukocytosis and an elevation of CRP.<h4>Methods</h4>We performed a systematic search of PubMed, EMBAS ...[more]

PMID: 32533986

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Project description:Objective:Clinical and laboratory biomarkers to predict the severity of coronavirus disease 2019 (COVID-19) are essential in this pandemic situation of which resource allocation must be urgently prepared especially in the context of respiratory support readiness. Lymphocyte count has been a marker of interest since the first COVID-19 publication. We conducted a systematic review and meta-analysis in order to investigate the association of lymphocyte count on admission and the severity of COVID-19. We would also like to analyze whether patient characteristics such as age and comorbidities affect the relationship between lymphocyte count and COVID-19. Methods:Comprehensive and systematic literature search was performed from PubMed, SCOPUS, EuropePMC, ProQuest, Cochrane Central Databases, and Google Scholar. Research articles in adult patients diagnosed with COVID-19 with information on lymphocyte count and several outcomes of interest, including mortality, acute respiratory distress syndrome (ARDS), intensive care unit (ICU) care, and severe COVID-19, were included in the analysis. Inverse variance method was used to obtain mean differences and its standard deviations. Maentel-Haenszel formula was used to calculate dichotomous variables to obtain odds ratios (ORs) along with its 95% confidence intervals. Random-effect models were used for meta-analysis regardless of heterogeneity. Restricted-maximum likelihood random-effects meta-regression was performed for age, gender, cardiac comorbidity, hypertension, diabetes mellitus, COPD, and smoking. Results:There were a total of 3099 patients from 24 studies. Meta-analysis showed that patients with poor outcome have a lower lymphocyte count (mean difference - 361.06 μL [- 439.18, - 282.95], p < 0.001; I 2 84%) compared to those with good outcome. Subgroup analysis showed lower lymphocyte count in patients who died (mean difference - 395.35 μL [- 165.64, - 625.07], p < 0.001; I 2 87%), experienced ARDS (mean difference - 377.56 μL [- 271.89, - 483.22], p < 0.001; I 2 0%), received ICU care (mean difference - 376.53 μL [- 682.84, - 70.22], p = 0.02; I 2 89%), and have severe COVID-19 (mean difference - 353.34 μL [- 250.94, - 455.73], p < 0.001; I 2 85%). Lymphopenia was associated with severe COVID-19 (OR 3.70 [2.44, 5.63], p < 0.001; I 2 40%). Meta-regression showed that the association between lymphocyte count and composite poor outcome was affected by age (p = 0.034). Conclusion:This meta-analysis showed that lymphopenia on admission was associated with poor outcome in patients with COVID-19.

Project description:BackgroundCoronavirus disease 2019 (COVID-19) has currently become a major global public health problem. The prevalence of COVID-19 has increased rapidly worldwide. Because there is no effective COVID-19 vaccine available yet, it is increasingly important to understand the average incubation period of severe acute respiratory syndrome novel coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, to design appropriate preventive and control strategies.ObjectiveThis systematic review and meta-analysis was designed to estimate the pooled average incubation period of SARS-CoV-2, the virus that causes COVID-19.MethodsWe conducted a systematic electronic web-based search of online databases, including PubMed, Google Scholar, Embase, and the World Health Organization Hinari portal. We included peer-reviewed research studies written in the English language on the incubation period of SARS-CoV-2 using pre-defined quality and inclusion criteria. STATA version 15 statistical software was used to analyze the data. Joanna Briggs Institute critical appraisal quality assessment tool for observational studies was utilized to evaluate the included studies. We extracted relevant data and presented in a tabular form. The I 2 test was used to assess heterogeneity across studies. Funnel plot asymmetry and Egger tests were used to check for publication bias. The final effect size was determined by applying a random-effects model.ResultsOur search identified 206 studies, amongst which 18 studies, representing 22,595 participants were included in the final analysis. The pooled average incubation period of SARS-CoV-2 was 5.7 days (95% CI, 5.1-6.4). Subgroup analyses by geographic location showed that the pooled average incubation period of SARS-CoV-2 was 6.1 days (95% CI, 5.34-6.94) in China and 4.54 (95% CI, 3.9-5.2) in other countries (Singapore, South Korea, and globally).ConclusionsThe pooled average incubation period of SARS-CoV-2 was about 6 days. The longest incubation period was observed in China. Global health initiatives as well as local health planners should consider this average incubation period when designing optimal prevention and control strategies for SARS-CoV-2. (Curr Ther Res Clin Exp. 2020; 81:XXX-XXX).

Project description:BackgroundTo date, several clinical laboratory parameters associated with Coronavirus disease 2019 (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.Methods and findingsWe 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. Forty-five studies in 6 countries were included. Compared to non-severe COVID-19 cases, severe or critical COVID-19 was characterised by higher neutrophil count (MMD: 1.23 [95% CI: 0.58 to 1.88] ×109 cells/L), and lower lymphocyte, CD4 and CD8 T cell counts with MMD (95% CI) of -0.39 (-0.47, -0.31) ×109 cells/L, -204.9 (-302.6, -107.1) cells/μl and -123.6 (-170.6, -76.6) 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).ConclusionsRelative to non-severe COVID-19, severe or critical COVID-19 is characterised by increased markers of innate immune response, decreased markers of adaptive immune response, and increased markers of tissue damage and major organ failure. These markers could be used to recognise severe or critical disease and to monitor clinical course of COVID-19.

Project description:ObjectivesExisting findings regarding the relationship between comorbidities and the severity of coronavirus disease 2019 (COVID-19) are inconsistent and insufficient. The aim of this study was to evaluate the association between different comorbidities and the severity of COVID-19.MethodsThe PubMed, Embase, and Cochrane Library databases were searched to identify studies reporting the rates of comorbidities in COVID-19 patients with severe/fatal outcomes. Subgroup analyses were conducted according to disease severity and the country of residence. Odds ratios (OR) with 95% confidence intervals (CI) were pooled using random-effects models.ResultsA total of 34 eligible studies were identified. In patients with severe/fatal COVID-19, the most prevalent chronic comorbidities were obesity (42%, 95% CI 34-49%) and hypertension (40%, 95% CI 35-45%), followed by diabetes (17%, 95% CI 15-20%), cardiovascular disease (13%, 95% CI 11-15%), respiratory disease (8%, 95% CI 6-10%), cerebrovascular disease (6%, 95% CI 4-8%), malignancy (4%, 95% CI 3-6%), kidney disease (3%, 95% CI 2-4%), and liver disease (2%, 95% CI 1-3%). In order of the prediction, the pooled ORs of the comorbidities in patients with severe or fatal COVID-19 when compared to patients with non-severe/fatal COVID-19 were as follows: chronic respiratory disease, OR 3.56 (95% CI 2.87-4.41); hypertension, OR 3.17 (95% CI 2.46-4.08); cardiovascular disease, OR 3.13 (95% CI 2.65-3.70); kidney disease, OR 3.02 (95% CI 2.23-4.08); cerebrovascular disease, OR 2.74 (95% CI 1.59-4.74); malignancy, OR 2.73 (95% CI 1.73-4.21); diabetes, OR 2.63 (95% CI 2.08-3.33); and obesity, OR 1.72 (95% CI 1.04-2.85). No correlation was observed between liver disease and COVID-19 aggravation (OR 1.54, 95% CI 0.95-2.49).ConclusionsChronic comorbidities, including obesity, hypertension, diabetes, cardiovascular disease, cerebrovascular disease, respiratory disease, kidney disease, and malignancy are clinical risk factors for a severe or fatal outcome associated with COVID-19, with obesity being the most prevalent and respiratory disease being the most strongly predictive. Knowledge of these risk factors could help clinicians better identify and manage the high-risk populations.

Dataset Information

Value of leukocytosis and elevated C-reactive protein in predicting severe coronavirus 2019 (COVID-19): A systematic review and meta-analysis.

Background

Methods

Results

Conclusion

Publications

Value of leukocytosis and elevated C-reactive protein in predicting severe coronavirus 2019 (COVID-19): A systematic review and meta-analysis.

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