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]: 0.800À0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769À0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746À0.907; 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.

Serum S100B protein as a marker of severity in Covid-19 patients

“…According to WHO clinical criteria at admission time, patients were hospitalized in High (HIC) and Low Intensity Care (LIC) wards, respectively. Severity of Covid-19 at the time of blood sampling was quanti ed using a Covidscore, attributing a value ranging from 0% to 100% [4][5][6][7]9]. Namely, patients recovered in HIC (n=16) presented: severe pneumonia (fever or suspected respiratory infection, plus one of the following: respiratory rate >30 breaths/min; severe respiratory distress or SpO2 ≤93% on room air); and LIC (n=58) comprehended a group spanning from uncomplicated disease to pneumonia but without signs of severe pneumonia.…”

“…Evaluation of Covid-19 severity and possible outcomes is limited by clinical heterogeneity and lack of speci c markers [1][2][3] Several laboratory parameters are considered in clinical practice, but the identi cation of novel indicators in blood specimens is a key issue for understanding the underlying biological mechanisms and improving prognostic accuracy [4][5][6][7][8][9] As a candidate marker we focused on the S100B protein, which is regarded to be involved in in ammatory processes as a Danger-Associated Molecular Patterns (DAMP) molecule [10,11]. S100B is a small acidic calcium-binding protein, originally isolated in the nervous system, where it is concentrated in astrocytes, being also present in oligodendrocytes, Schwann cells, enteric glial cells, and some neuron subpopulations [12,13].…”

Exclusion of bacterial co-infection in COVID-19 using baseline inflammatory markers and their response to antibiotics

“…It is likely that many COVID-19 associated antibiotic prescriptions are given in the absence of bacterial coinfection, thus hampering antimicrobial stewardship efforts and potentially increasing antimicrobial resistance [12][13][14]. Many studies have focused on clinical and laboratory features that risk stratify outcome in COVID-19 [15][16][17][18], but currently infections caused by virus alone cannot be readily distinguished from those with a bacterial component. C-reactive protein (CRP), white cell count (WCC) and procalcitonin (PCT) have been used to distinguish between influenza and bacterial pneumonia, allowing antibiotic treatment to be omitted or stopped [19][20][21][22].…”

Early prediction of the risk of severe coronavirus disease 2019: A key step in therapeutic decision making

“…In an article published in the July issue of EBioMedicine, Xiao et al. propose a novel risk score for this purpose; the HNC-LL score [1] . Specifically, the HNC-LL score includes hypertension, neutrophil count, C-Reactive Protein (CRP), lymphocyte count, and lactate dehydrogenase.…”

“…The delay between the onset of symptoms and the medical examination is a key factor to consider as it provides an estimation of the stage of disease, which was not taken into account in the study by Xiao et al. [1] …”