Assessment of the HScore as a Predictor of Disease Outcome in Patients With COVID-19

Mohammadreza Bordbar; Anahita Sanaei Dashti; Ali Amanati; Eslam Shorafa; Yasaman Mansoori; Seyed Javad Dehghani; Hossein Molavi Vardanjani


BMC Pulm Med. 2021;21(338) 

In This Article

Abstract and Introduction


Severe coronavirus disease 2019 (COVID-19) accompanies hypercytokinemia, similar to secondary hemophagocytic lymphohistiocytosis (sHLH). We aimed to find if HScore could predict disease severity in COVID-19. HScore was calculated in hospitalized children and adult patients with a proven diagnosis of COVID-19. The need for intensive care unit (ICU), hospital length of stay (LOS), and in-hospital mortality were recorded. The median HScore was 43.0 (IQR 0.0–63.0), which was higher in those who needed ICU care (59.7, 95% CI 46.4–72.7) compared to those admitted to non-ICU medical wards (38.8, 95% CI 32.2–45.4; P = 0.003). It was also significantly higher in patients who died of COVID-19 (105.1, 95% CI 53.7–156.5) than individuals who survived (41.5, 95% CI 35.8–47.1; P = 0.005). Multivariable logistic regression analysis revealed that higher HScore was associated with a higher risk of ICU admission (adjusted OR = 4.93, 95% CI 1.5–16.17, P = 0.008). The risk of death increased by 20% for every ten units increase in HScore (adjusted OR 1.02, 95% CI 1.00–1.04, P = 0.009). Time to discharge was statistically longer in high HScore levels than low levels (HR = 0.41, 95% CI 0.24–0.69). HScore is much lower in patients with severe COVID-19 than sHLH. Higher HScore is associated with more ICU admission, more extended hospitalization, and a higher mortality rate. A modified HScore with a new cut-off seems more practical in predicting disease severity in patients with severe COVID-19.


Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening severe systemic hyperinflammatory syndrome characterized by hypercytokinemia with multi-organ dysfunction. Viral etiologies have been recognized as triggers of sHLH and account for approximately 35% of adult cases.[1]

Recent literature by Zhou et al. indicates that severe coronavirus disease 2019 (COVID-19) accompanies by an aggressive inflammatory response known as a cytokine storm,[2] that bears similarities to sHLH (including excess production of tumor necrosis factor-α (TNF- α), monocyte chemoattractant protein-1 (MCP1), and interleukin-2 [IL-2]). The probability of sHLH can be predicted by a validated score called HScore.[3] A score higher than 169 was shown to predict the risk of sHLH with 93% sensitivity and 86% specificity.[4] Mehta and colleagues hypothesized that HScore might detect hyperinflammatory states in patients with severe COVID-19. Accordingly, HScore may help to decide which patients may benefit from immune-modulators such as high-dose steroid, interleukin (IL)-1, or IL-6 blockade by anakinra or tocilizumab.[5] However, the use of HScore for COVID- 19 patients has remained questionable by some authors due to limitations regarding body temperature, raised ferritin levels (in early phase ferritin concentrations hardly reach the HScore threshold of 2000 ng/mL), leukopenia (the HScore is unable to distinguish between lymphocytopenia and neutropenia), and the lack of published data on characteristic features.[6,7]

Hypothesizing that the cytokine storm is the principal cause of disease severity in patients with COVID-19, and considering the controversies in the literature regarding the potential of HScore, as an index of cytokine storm, to predict the severity of COVID-19, our study aimed to investigate whether and how HScore is associated with the need for ICU care, hospital length of stay (LOS), and in-hospital mortality in confirmed cases of COVID-19.