Case fatality rate in COVID-19: a systematic review and meta-analysis
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Background
Estimating the prevalence of severe or critical illness and case fatality of COVID-19 outbreak in December, 2019 remains a challenge due to biases associated with surveillance, data synthesis and reporting. We aimed to address this limitation in a systematic review and meta-analysis and to examine the clinical, biochemical and radiological risk factors in a meta-regression.
Methods
PRISMA guidelines were followed. PubMed, Scopus and Web of Science were searched using pre-specified keywords on March 07, 2020. Peer-reviewed empirical studies examining rates of severe illness, critical illness and case fatality among COVID-19 patients were examined. Numerators and denominators to compute the prevalence rates and risk factors were extracted. Random-effects meta-analyses were performed. Results were corrected for publication bias. Meta-regression analyses examined the moderator effects of potential risk factors.
Results
The meta-analysis included 29 studies representing 2,090 individuals. Pooled rates of severe illness, critical illness and case fatality among COVID-19 patients were 15%, 5% and 0.8% respectively. Adjusting for potential underreporting and publication bias, increased these estimates to 26%, 16% and 7.4% respectively. Increasing age and elevated LDH consistently predicted severe / critical disease and case fatality. Hypertension; fever and dyspnea at presentation; and elevated CRP predicted increased severity.
Conclusions
Risk factors that emerged in our analyses predicting severity and case fatality should inform clinicians to define endophenotypes possessing a greater risk. Estimated case fatality rate of 7.4% after correcting for publication bias underscores the importance of strict adherence to preventive measures, case detection, surveillance and reporting.
Article activity feed
-
SciScore for 10.1101/2020.04.01.20050476: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable When not reported, study level means and standard deviations for age were imputed from the available statistics (i.e. median, IQR or range). 12 Proportions of the following variables within a study sample were extracted: age ≤ 18 years, age ≥60 years, female sex, diabetes mellitus, hypertension, heart disease, chronic liver disease, chronic kidney disease, chronic obstructive pulmonary disease, malignancy, immunosuppression (e.g. HIV), smoking and pregnancy. Table 2: Resources
Software and Algorithms Sentences Resources PubMed, Scopus and Web of … SciScore for 10.1101/2020.04.01.20050476: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable When not reported, study level means and standard deviations for age were imputed from the available statistics (i.e. median, IQR or range). 12 Proportions of the following variables within a study sample were extracted: age ≤ 18 years, age ≥60 years, female sex, diabetes mellitus, hypertension, heart disease, chronic liver disease, chronic kidney disease, chronic obstructive pulmonary disease, malignancy, immunosuppression (e.g. HIV), smoking and pregnancy. Table 2: Resources
Software and Algorithms Sentences Resources PubMed, Scopus and Web of Science databases were searched on March 7, 2020 with the aim of identifying studies that have been published in year 2020 examining the prevalence of severe illness, critically severe illness and mortality associated with COVID-19 infection using pre-determined keyword combinations (Table S1 in Appendix). PubMedsuggested: (PubMed, RRID:SCR_004846)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:28 Our systematic review has some limitations. First, while we eliminated studies with overlapping samples by screening for overlaps of institutes, study dates and authors, we cannot be 100% certain. Second, high degree of heterogeneity was a concern. However, this should be expected in any meta-analysis due to the variability in methodology and study samples and we used heterogeneity to explore covariates in meta-regression analyses. 18, 20 Third, funnel plots of all three meta-analyses indicating substantial publication bias, limiting the generalizability of uncorrected random-effects meta-analyses. Finally, the protocol was not pre-registered. Use of a systematic search strategy; use of random-effects meta-analyses and meta-regression analyses assuming high heterogeneity of effect-sizes; exploring the etiology of heterogeneity in meta-regression analyses, which also identified risk factors of morbidity and mortality; exploring the validity of our findings in sensitivity analyses; and statistically correcting for publication / underreporting bias are notable strengths of our systematic review and meta-analysis. In conclusion, after correcting for publication bias, COVID-19 associated overall rates of requirement for hospitalization, intensive care and case fatality could be as high as 26%, 16% and 7.4% respectively. This underscores the importance of strict adherence to preventive measures, case detection, surveillance and reporting. Hypertension; fever and dyspnea at prese...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
-
