The LUSZ COVID-19 Severity Index: A Prognostic and Predictive Score of Mortality for Hospitalized Patients With Covid-19

Overview

The coronavirus disease 2019 (COVID-19) has spread rapidly and caused a global pandemic, as defined by the WHO, within a short period of time. The prognostic of disease severity is still a challenge and early identification of risk factors to be involved in its progression is of high importance. The scoring of variables related to worse outcomes is key for a targeted and/or advanced protocol. Besides, the need for a predictive-wide model is mandatory for hospitalized unvaccinated patients to avoid any delay in the characterization of severe illness and the development of complications. The LUSZ COVID-19 Severity Index was developed as a predictive tool based on \>100 risk factors/biomarkers, that could effectively identify high-risk patients and prevent mortality.

The scientific community is in urgent need of reliable biomarkers related to COVID-19 disease progression, in order to stratify high-risk patients. The rapid disease spread necessitates the immediate categorization of patients into risk groups following diagnosis, to ensure optimal resource allocation. Novel biomarkers are needed to identify patients who will suffer rapid disease progression to severe complications and death. The identification of novel biomarkers is strictly related to the understanding of viral pathogenetic mechanisms, as well as cellular and organ damage. Effective biomarkers would be helpful for screening, clinical management, and prevention of serious complications. Indeed, previous studies suggested and developed predictive scores (CALL, Chosen, HA2T2, ANDC, ABC2-SPH, ICOP, SEIMC, IRS, NLP, APACHE II, GRAM, and others) that estimate the severity of the disease, the risk of needing invasive mechanical ventilation (IMV) among patients with COVID-19 and the risk of mortality. Many scores including so many relevant parameters have been used to predict the status of a patient. In addition to comorbidities, age, etc., some hematological parameters, including white blood cell (WBC), lymphopenia, c-Reactive Protein (CRP), and some biochemical parameters, such as lactate dehydrogenase (LDH), creatine kinase (CK), and troponin were reported to be associated with COVID-19 severity. In fact, the patient's initial laboratory scoring is useful but not sufficient to avoid mortality: high neutrophil count (\>0.7 × 103/μL), lymphopenia (\<0.8 × 103/μL), elevated CRP (\>4.75 mg/dL), and elevated LDH (\>593 U/L) were the most important predictors of mortality. Another prognostic marker the lymphocyte-to-CRP ratio (LCR), was also helpful. A rise in the NLR and a decline in LCR correlates with the severity of COVID-19. Specifically, a low LCR at presentation was seen to predict ICU admission and the need for invasive ventilation. Patients critically ill with COVID-19 had a hyperinflammation, the associated biomarkers may be beneficial for risk stratification. Many studies found other associations with serum CRP, procalcitonin (PCT), D-dimer, and serum ferritin. Subsequent studies demonstrate that the inflammatory response plays a critical role in COVID-19, and inflammatory cytokine storm increases the severity of COVID-19. In fact, the serum levels of IL-6 can effectively assess disease severity and predict outcomes in patients with COVID-19. So, these prognostic models have been introduced to guide treatment and resource management. In this study, we aimed to specify high-risk factors and biomarkers of fatal outcomes in hospitalized subjects with coronavirus depending on many variables analysis, and also to compare the efficacy of targeted treatments (antiviral, antiretroviral, immunosuppressive antagonist, etc.) in order to help clinicians better choose a therapeutic strategy. The population had been divided into groups according to the WHO Ordinal Clinical Severity Scale on which the LUSZ SCORE was applied; The percentage of mortality, in and out of the hospital, the length of stay in the hospital, the pulmonary inflammatory lesions and their distribution, the SARS-CoV-2 IgM and IgG variations at admission, the inflammatory markers, the complete blood count, the coagulation factors and enzymes, proteins and electrolytes profile, glucose and lipid profile, and others were measured before and after LUSZ scoring. The establishment of this novel predictive scoring model of disease progression may help identify patients with COVID-19 who may subsequently develop a critical illness. Thus, we can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources, which helps to deliver proper treatment according to each case.