Characterisation of clinical, laboratory and imaging factors related to mild vs. severe covid-19 infection: a systematic review and meta-analysis
- PMID: 32755287
- PMCID: PMC7877997
- DOI: 10.1080/07853890.2020.1802061
Characterisation of clinical, laboratory and imaging factors related to mild vs. severe covid-19 infection: a systematic review and meta-analysis
Abstract
Background: Early detection of disease progression associated with severe COVID-19, and access to proper medical care lowers fatality rates of severe cases. Currently, no studies had systematically examined the variables in detecting severe COVID-19.
Method: Systematic searching of electronic databases identified observational studies which recruited participants with confirmed COVID-19 infection who were divided into different groups according to disease severity were identified.
Results: To analysis 41 studies with 5064 patients were included.Patients who are elderly (SMD, 1.90; 95% CI, 1.01 to 2.8), male (OR, 1.71; 95% CI, 1.39 to 2.11) and have comorbidities or flu-like symptoms were significantly associated with the development to severe cases. Severe cases were associated with significant increased WBC (OR, 5.83; 95% CI, 2.76 to 12.32), CRP (OR, 3.62; 95% CI, 1.62 to 8.03), D-dimer (SMD, 1.69; 95% CI, 1.09 to 2.28), AST (OR, 4.64; 95% CI, 3.18 to 6.77) and LDH (OR, 7.94; 95% CI, 2.09 to 30.21). CT manifestation of bilateral lung involvement (OR, 4.55; 95% CI, 2.17 to 9.51) was associated with the severe cases. Conclusions and Relevance: Our findings offer guidance for a wide spectrum of clinicians to early identify severe COVID-19 patients, transport to specialised centres, and initiate appropriate treatment. Key Messages This systematic review and meta-analysis examined 41 studies including 5,064 patients with confirmed COVID-19. Severe cases were associated with age, male gender, and with fever, cough and respiratory diseases, increased WBC, CRP, D-dimer, AST and LDH levels. Furthermore, CT manifestation of bilateral lung involvement was associated with the severe cases. These findings provide guidance to health professionals with early identification of severe COVID-19 patients, transportation to specialised care and initiate appropriate supportive treatment.
Keywords: COVID-19; clinical characteristics; disease severity; laboratory indicators; meta-analysis.
Conflict of interest statement
We declare no competing interests.
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