Gastrointestinal Manifestations and Outcomes of COVID-19: A Comprehensive Systematic Review and Meta-analysis.

Introduction Pulmonary symptoms are the most prominent manifestations of Coronavirus disease 2019 (COVID-19). However, gastrointestinal (GI) symptoms have been reported widely as well. Literature describing the relation of these symptoms with outcomes of COVID-19 patients is limited in terms of sample size, geographic diversity, and the spectrum of GI symptoms included. We aim to evaluate the association of GI symptoms with outcomes of hospitalized COVID-19 patients. Methods A systematic review and meta-analysis of observational studies assessing GI symptoms and outcomes in COVID-19 patients were undertaken using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria and the Meta-analysis of Observational Studies in Epidemiology (MOOSE) checklist. Details on outcomes included ICU vs. non-ICU admission, severe vs. non-severe disease, invasive mechanical ventilation (IMV) vs. no-IMV use, oxygen saturation <90% vs. >90%, in-hospital mortality vs. discharged alive and survivors. We obtained the odds ratio (OR), 95% confidence interval (95%CI), and forest plots. Sensitivity analysis was used to analyze publication bias and heterogeneity. Results In 35 studies with 7931 confirmed COVID-19 patients, we found that anorexia (pooled OR:2.05; 95%CI: 1.36-3.09, p=0.0006) and abdominal pain (OR 2.80; 95%CI: 1.41-5.54, p=0.003) were associated with a higher risk of poor outcomes and no such association was found for diarrhea (OR 1.04; 95%CI: 0.85-1.26, p=0.71), nausea (OR 0.73; 95%CI: 0.38-1.39, p=0.34) and vomiting (OR 1.24; 95%CI 0.86-1.79, p=0.25). Conclusion The meta-analysis concludes that anorexia and abdominal pain are associated with poor outcomes in hospitalized COVID-19 patients, while diarrhea, nausea, and vomiting have no association. Future research should focus on whether detecting GI invasion in conjunction with fecal polymerase chain reaction (PCR) testing can aid in the early triage of high-risk individuals and improve outcomes.

Biomarkers and outcomes of COVID-19 hospitalisations: systematic review and meta-analysis.

OBJECTIVE: To evaluate association between biomarkers and outcomes in COVID-19 hospitalised patients. COVID-19 pandemic has been a challenge. Biomarkers have always played an important role in clinical decision making in various infectious diseases. It is crucial to assess the role of biomarkers in evaluating severity of disease and appropriate allocation of resources. DESIGN AND SETTING: Systematic review and meta-analysis. English full text observational studies describing the laboratory findings and outcomes of COVID-19 hospitalised patients were identified searching PubMed, Web of Science, Scopus, medRxiv using Medical Subject Headings (MeSH) terms COVID-19 OR coronavirus OR SARS-CoV-2 OR 2019-nCoV from 1 December 2019 to 15 August 2020 following Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines. PARTICIPANTS: Studies having biomarkers, including lymphocyte, platelets, D-dimer, lactate dehydrogenase (LDH), C reactive protein (CRP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, procalcitonin (PCT) and creatine kinase (CK), and describing outcomes were selected with the consensus of three independent reviewers. MAIN OUTCOME MEASURES: Composite poor outcomes include intensive care unit admission, oxygen saturation <90%, invasive mechanical ventilation utilisation, severe disease, in-hospital admission and mortality. The OR and 95% CI were obtained and forest plots were created using random-effects models. Publication bias and heterogeneity were assessed by sensitivity analysis. RESULTS: 32 studies with 10 491 confirmed COVID-19 patients were included. We found that lymphopenia (pooled-OR: 3.33 (95% CI: 2.51-4.41); p<0.00001), thrombocytopenia (2.36 (1.64-3.40); p<0.00001), elevated D-dimer (3.39 (2.66-4.33); p<0.00001), elevated CRP (4.37 (3.37-5.68); p<0.00001), elevated PCT (6.33 (4.24-9.45); p<0.00001), elevated CK (2.42 (1.35-4.32); p=0.003), elevated AST (2.75 (2.30-3.29); p<0.00001), elevated ALT (1.71 (1.32-2.20); p<0.00001), elevated creatinine (2.84 (1.80-4.46); p<0.00001) and LDH (5.48 (3.89-7.71); p<0.00001) were independently associated with higher risk of poor outcomes. CONCLUSION: Our study found a significant association between lymphopenia, thrombocytopenia and elevated levels of CRP, PCT, LDH, D-dimer and COVID-19 severity. The results have the potential to be used as an early biomarker to improve the management of COVID-19 patients, by identification of high-risk patients and appropriate allocation of healthcare resources in the pandemic.

Early epidemiological indicators, outcomes, and interventions of COVID-19 pandemic: A systematic review.

BACKGROUND: Coronavirus disease-2019 (COVID-19), a pandemic that brought the whole world to a standstill, has led to financial and health care burden. We aimed to evaluate epidemiological characteristics, needs of resources, outcomes, and global burden of the disease. METHODS: Systematic review was performed searching PubMed from December 1, 2019, to March 25, 2020, for full-text observational studies that described epidemiological characteristics, following MOOSE protocol. Global data were collected from the JHU-Corona Virus Resource Center, WHO-COVID-2019 situation reports, KFF.org, and Worldometers.info until March 31, 2020. The prevalence percentages were calculated. The global data were plotted in excel to calculate case fatality rate (CFR), predicted CFR, COVID-19 specific mortality rate, and doubling time for cases and deaths. CFR was predicted using Pearson correlation, regression models, and coefficient of determination. RESULTS: From 21 studies of 2747 patients, 8.4% of patients died, 20.4% recovered, 15.4% were admitted to ICU and 14.9% required ventilation. COVID-19 was more prevalent in patients with hypertension (19.3%), smoking (11.3%), diabetes mellitus (10%), and cardiovascular diseases (7.4%). Common complications were pneumonia (82%), cardiac complications (26.4%), acute respiratory distress syndrome (15.7%), secondary infection (11.2%), and septic shock (4.3%). Though CFR and COVID-19 specific death rates are dynamic, they were consistently high for Italy, Spain, and Iran. Polynomial growth models were best fit for all countries for predicting CFR. Though many interventions have been implemented, stern measures like nationwide lockdown and school closure occurred after very high infection rates (>10cases per 100 000population) prevailed. Given the trend of government measures and decline of new cases in China and South Korea, most countries will reach the peak between April 1-20, if interventions are followed. CONCLUSIONS: A collective approach undertaken by a responsible government, wise strategy implementation and a receptive population may help contain the spread of COVID-19 outbreak. Close monitoring of predictive models of such indicators in the highly affected countries would help to evaluate the potential fatality if the second wave of pandemic occurs. The future studies should be focused on identifying accurate indicators to mitigate the effect of underestimation or overestimation of COVID-19 burden.