Crit Care. 2020 Nov 16;24(1):647. doi: 10.1186/s13054-020-03374-8.
ABSTRACT
BACKGROUND: Coronavirus disease 2019 (COVID-19), a highly infectious disease, has been rapidly spreading all over the world and remains a great threat to global public health. Patients diagnosed with severe or critical cases have a poor prognosis. Hence, it is crucial for us to identify potentially severe or critical cases early and give timely treatments for targeted patients. In the clinical practice of treating patients with COVID-19, we have observed that the neutrophil-to-lymphocyte ratio (NLR) of severe patients is higher than that in mild patients. We performed this systematic review and meta-analysis to evaluate the predictive values of NLR on disease severity and mortality in patients with COVID-19.
METHODS: We searched PubMed, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases to identify eligible studies (up to August 11, 2020). Two authors independently screened studies and extracted data. The methodological quality of the included studies was assessed by Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2).
RESULTS: Thirteen studies involving 1579 patients reported the predictive value of NLR on disease severity. The pooled sensitivity (SEN), specificity (SPE) and area under curve (AUC) were 0.78 (95% CI 0.70-0.84), 0.78 (95% CI 0.73-0.83) and 0.85 (95% CI 0.81-0.88), respectively. Ten studies involving 2967 patients reported the predictive value of NLR on mortality. The pooled SEN, SPE and AUC were 0.83 (95% CI 0.75-0.89), 0.83 (95% CI 0.74-0.89) and 0.90 (95% CI 0.87-0.92), respectively.
CONCLUSIONS: NLR has good predictive values on disease severity and mortality in patients with COVID-19 infection. Evaluating NLR can help clinicians identify potentially severe cases early, conduct early triage and initiate effective management in time, which may reduce the overall mortality of COVID-19.
TRIAL REGISTRY: This meta-analysis was prospectively registered on PROSPERO database (Registration number: CRD42020203612).
PMID:33198786 | PMC:PMC7667659 | DOI:10.1186/s13054-020-03374-8