Background Evidence links COVID-19 severity to hyper-inflammation. Treatment with tocilizumab, a monoclonal antibody directed against the interleukin-6 (IL-6) receptor, was shown to lead to clinical improvement in patients with severe COVID-19. We, therefore, performed the present systematic review and meta-analysis to investigate whether the circulating levels of IL-6 is a reliable indicator of disease severity among patients affected with COVID-19. Methods A systematic search was conducted in PubMed, Scopus, Web of Science, and Google Scholar on April 19, 2020. Results Eleven studies provided data of IL-6 levels in patients with severe to critical COVID-19 (severe) and patients with mild to moderate COVID-19 (non-severe). The included studies were of moderate to high quality. The mean patients’ age was 60.9 years, ranging from 45.2 to 76.7 years in the severe group and 46.8 years, ranging from 37.9 to 61 years, in the nonsevere group. Fifty-two percent were male in the severe group, as compared to 46% in the non-severe group. An overall random effects meta-analysis showed significantly higher serum levels of IL-6 in the severe group than in the non-severe group with a mean difference of +23.1 pg/mL (95% CI: 12.42–33.79) and the overall effect of 4.24 ( P -value < 0.001). Meta-regressions showed that neither age nor sex significantly influenced the mean difference of IL-6 between the groups. Conclusions Meta-analysis and meta-regression reveal a reliable relationship between IL-6 and COVID-19 severity, independent of age and sex. Future research is, however, required to assess the effect of BMI on the pattern of IL-6 production in patients with COVID-19. Also, there might be confounding factors that influence the relationship between IL-6 and COVID-19 severity and remain as yet unknown.

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Highlights CT severity score (CSS) could predict ICU admission, intubation, and mortality. Reticular pattern in lung CT scans, could be protective against adverse outcomes. CSS was weakly correlated with initial qSOFA score. CSS could not predict the length of stay in hospital.

Background COVID-19 has caused great concern for patients with underlying medical conditions. We aimed to determine the prognosis of patients with current or previous cancer with either a PCR-confirmed COVID-19 infection or a probable diagnosis according to chest CT scan. Methods We conducted a case control study in a referral hospital on confirmed COVID-19 adult patients with and without a history of cancer from February25th to April21st, 2020. Patients were matched according to age, gender, and underlying diseases including ischemic heart disease (IHD), diabetes mellitus (DM), and hypertension (HTN). Demographic features, clinical data, comorbidities, symptoms, vital signs, laboratory findings, and chest computed tomography (CT) images have been extracted from patients’ medical records. Multivariable logistic regression was used to estimate odd ratios and 95% confidence intervals of each factor of interest with outcomes. Results Fifty-three confirmed COVID-19 patients with history of cancer were recruited and compared with 106 non-cancerous COVID-19 patients as controls. Male to female ratio was 1.33 and 45% were older than 65. Dyspnea and fever were the most common presenting symptoms in our population with 57.86 and 52.83% respectively. Moreover, dyspnea was significantly associated with an increased rate of mortality in the cancer subgroup (p = 0.013). Twenty-six patients (49%) survived among the cancer group while 89 patients (84%) survived in control (p = 0.000). in cancer group, patients with hematologic cancer had 63% mortality while patients with solid tumors had 37%. multivariate analysis model for survival prediction showed that history of cancer, impaired consciousness level, tachypnea, tachycardia, leukocytosis and thrombocytopenia were associated with an increased risk of death. Conclusion In our study, cancer increased the mortality rate and hospital stay of COVID-19 patients and this effect remains significant after adjustment of confounders. Compared to solid tumors, hematologic malignancies have been associated with worse consequences and higher mortality rate. Clinical and para-clinical indicators were not appropriate to predict death in these patients.