Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage

Abstract

Background: Patients with critical illness due to infection with the 2019 coronavirus disease (COVID-19) show rapid disease progression to acute respiratory failure. The study aimed to screen the most useful predictive factor for critical illness caused by COVID-19.

Methods: The study prospectively involved 61 patients with COVID-19 infection as a derivation cohort, and 54 patients as a validation cohort. The predictive factor for critical illness was selected using LASSO regression analysis. A nomogram based on non-specific laboratory indicators was built to predict the probability of critical illness.

Results: The neutrophil-to-lymphocyte ratio (NLR) was identified as an independent risk factor for critical illness in patients with COVID-19 infection. The NLR had an area under receiver operating characteristic of 0.849 (95% confidence interval [CI], 0.707 to 0.991) in the derivation cohort and 0.867 (95% CI 0.747 to 0.944) in the validation cohort, the calibration curves fitted well, and the decision and clinical impact curves showed that the NLR had high standardized net benefit. In addition, the incidence of critical illness was 9.1% (1/11) for patients aged ≥ 50 and having an NLR < 3.13, and 50% (7/14) patients with age ≥ 50 and NLR ≥ 3.13 were predicted to develop critical illness. Based on the risk stratification of NLR according to age, this study has developed a COVID-19 pneumonia management process.

Conclusions: We found that NLR is a predictive factor for early-stage prediction of patients infected with COVID-19 who are likely to develop critical illness. Patients aged ≥ 50 and having an NLR ≥ 3.13 are predicted to develop critical illness, and they should thus have rapid access to an intensive care unit if necessary.

Keywords: 2019-nCoV; COVID-19; Model; NLR; Prognosis; SARS-CoV.

Fig. 1

A 50-year-old man with 2019 novel coronavirus (COVID-19) infection. a Ground glass shadow in multiple lobes and segments of bilateral lungs; the lesions were adjacent to the pleura (Illness Day 8, Hospital Day 0). b Ground glass shadow expanding and consolidation in bilateral lung (Illness Day 11, Hospital Day 3). c Ground glass shadow absorption and reduced consolidation area (Illness Day 15, Hospital Day 7). d Lesion dissipation (Illness Day 20, Hospital Day 12)

Fig. 2

The predictive factor neutrophil-to-lymphocyte ratio (NLR) was selected using LASSO regression analysis. a LASSO coefficient profiles of the non-zero variables of COVID-19 pneumonia. b Partial likelihood deviance plot of the lowest point of the red curve (solid line), which corresponds to a three-variable model. The dashed line on the right is a more concise model within one standard error (the number of variables is one)

Fig. 3

Nomogram predicting 7-day and 14-day critical probability of patients with COVID-19 pneumonia

Fig. 4

Evaluate the prediction effect of nomogram in the derivation (a–c) and velidation (d–f) cohorts. a, d Calibration plot, b, e decision curve and c, f clinical impact curve of the nomogram for critical probability in the COVID-19 cohort, in which the predicted critical probability was compared well with the actual probability and had superior standardized net benefit

Fig. 5

Time-dependent changes in NLR levels in the mild, moderate, and severe or critical groups. The NLR was higher in the severe or critical group, and a significant difference in the decline rate was observed between the two groups (p = 0.0240 and p < 0.0001 for derivation and validation cohorts, respectively)

Fig. 6

Kaplan–Meier curves of risk group stratification for no critical illness in the derivation cohorts. a The cutoffs of NLR for each risk group were as follows: low risk: < 3.13, and high risk: ≥ 3.13. b Risk group stratification according to age and c NLR combined with age

Fig. 7

COVID-19 pneumonia management process