Background: Early identification of patients who are at high risk of poor clinical outcomes is of great important in saving lives for patients with the novel corona virus disease 2019 (COVID-19) in context of limited medical resources.
Objective: To evaluate value of the neutrophil to lymphocyte ratio (NLR), calculated at hospital admission and in isolation, for prediction of the subsequent presence of disease aggravation and serious clinical outcomes (e.g., shock, death).
Methods: We designed a prospective cohort study of 352 hospitalized patients with COVID-19 between January 9 and February 26, 2020 in Yichang city, Hubei province. Patients with a NLR equal to and higher than the cutoff value derived from the receiver operating characteristic curve method were classified as the exposure group. The primary outcome was disease deterioration, defined as promotion of clinical classifications of the disease during hospitalization (e.g., moderate to severe/critical; severe to critical,). The secondary outcomes were shock and death occurred during the treatment.
Results: During the follow up, 51 (14.5%) patients’ condition deteriorated, 15 patients (4.3%) complicated septic shock, and 15 patients (4.3%) died. NLR was higher in patients with deterioration than those without (median: 5.33 vs. 2.14, P <0.001), as well as between patients with and without serious clinical outcomes (shock vs. no shock: 6.19 vs. 2.25, P <0.001; death vs. survival: 7.19 vs. 2.25, P <0.001). NLR measured at hospital admission had high value in predicting subsequent disease deterioration, shock and death (all the areas under the curve > 0.80). The sensitivity of ≥ 2.6937 for the NLR in predicting subsequent disease deterioration, shock and death were 82.0% (95% confidence interval, 69.0 to 91.0), 93.3% (68.0 to 100), and 92.9% (66.0 to 100); and the corresponding negative predictive values were 95.7% (93.0 to 99.2), 99.5% (98.6 to 100) and 99.5% (98.6 to 100), respectively.
Conclusions: The NLR measured at admission and in isolation can be used to effectively predict subsequent presence of disease deterioration and serious clinical outcomes for patients with COVID-19.