Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019

Abstract

Background: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity.

Methods: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively.

Findings: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed.

Interpretation: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions.

Funding: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).

Keywords: COVID-19; HNC-LL; Prediction; SARS-COV-2; Severity.

Fig. 1

Study flowchart. A total of 690 patients with confirmed COVID-19 between 1 January and 18 March 2020 were included in this study. After excluding patients who had incomplete clinical data, those who were coinfected with other respiratory viruses, and those who were discharged within 24 h after admission, 442 patients were retained in the final analysis. Of these, 333 were hospitalised in Honghu. Simple random sampling in a ratio of 7:3 was performed to assign 231 patients into a training cohort (the Honghu training cohort) and 101 patients into an internal validation cohort (the Honghu internal validation cohort). In addition, 110 patients hospitalised in Nanchang were used as an external validation cohort (the Nanchang external validation cohort).

Fig. 2

Receiver operating characteristic (ROC) curves for evaluating the predictive ability of the HNC-LL score for disease severity in different cohorts. ROC curve of the HNC-LL score in (a) the Honghu training cohort, (b) the Honghu internal validation cohort, and (c) the Nanchang external validation cohort. AUC, area under the ROC curve; CI, confidence interval.

Fig. 3

Comparison of predictive performance for disease severity among the HNC-LL score and independent risk factors, MuLBSTA score, CURB-65, and NLR using ROC curves. (a) ROC curves of the HNC-LL score and independent risk factors in the entire cohort. (b) ROC curves of the HNC-LL, NLR, and MuLBSTA scores in the entire cohort. (c) ROC curves of the HNC-LL and CURB-65 scores in the Nanchang external validation cohort. Neutrophil, neutrophil count; Lymphocyte, lymphocyte count; CRP, C-reactive protein; LDH, lactate dehydrogenase; NLR, neutrophil-to-lymphocyte ratio model; ROC, receiver operating characteristic curve; MuLBSTA score, a model based on multilobular infiltrates, lymphocyte ≤0.8 × 10⁹/L, bacterial coinfection, acute smoking, smoking cessation, hypertension, and age ≥60 years; CURB-65, a model based on age, confusion, urea, respiratory rate, and blood pressure. P values were calculated using DeLong's test.

Fig. 4

Severe illness-free survival curves for high and low severity risk groups. Patients in three cohorts diagnosed with non-severe disease on admission were included in this analysis. Based on their HNC-LL scores, they were stratified into the high and low severe risk groups according to the cut-off value of –1.508. HR, hazard ratio; CI, confidence interval. P value was calculated using the log-rank test. *A patient was excluded from this analysis for lack of follow-up information.

Fig. 5

Comparison of the ability to predict severe disease between the HNC-LL score and independent risk factors, MuLBSTA score, and NLR using ROC curves. Patients in the entire cohort diagnosed as non-severe on admission were included in this analysis. (a) Comparison of clinical utility between the HNC-LL score and independent risk factors. (b) Comparison of clinical utility among the HNC-LL, NLR, and MuLBSTA scores. P values were calculated using DeLong's test.