Corrigendum: Definition of the immune parameters related to COVID-19 severity.

[This corrects the article DOI: 10.3389/fimmu.2022.850846.].

C-reactive protein and clinical outcome in COVID-19 patients: the importance of harmonized measurements.

C-reactive protein (CRP) is a cytokine-mediated acute phase reactant with a recognized role in inflammatory conditions and infectious disease. In coronavirus disease 2019 (COVID-19), elevated CRP concentrations in serum were frequently detected and significantly associated with poor outcome in terms of disease severity, need for intensive care, and in-hospital death. For these reasons, the marker was proposed as a powerful test for prognostic classification of COVID-19 patients. In most of available publications, there was however confounding information about how interpretative criteria for CRP in COVID-19 should be derived, including quality of employed assays and optimal cut-off definition. Assuring result harmonization and controlling measurement uncertainty in terms of performance specifications are fundamental to allow worldwide application of clinical information according to specific CRP thresholds and to avoid risk of patient misclassification.

Definition of the Immune Parameters Related to COVID-19 Severity.

A relevant portion of patients with disease caused by the severe acute respiratory syndrome coronavirus 2 (COVID-19) experience negative outcome, and several laboratory tests have been proposed to predict disease severity. Among others, dramatic changes in peripheral blood cells have been described. We developed and validated a laboratory score solely based on blood cell parameters to predict survival in hospitalized COVID-19 patients. We retrospectively analyzed 1,619 blood cell count from 226 consecutively hospitalized COVID-19 patients to select parameters for inclusion in a laboratory score predicting severity of disease and survival. The score was derived from lymphocyte- and granulocyte-associated parameters and validated on a separate cohort of 140 consecutive COVID-19 patients. Using ROC curve analysis, a best cutoff for score of 30.6 was derived, which was associated to an overall 82.0% sensitivity (95% CI: 78-84) and 82.5% specificity (95% CI: 80-84) for detecting outcome. The scoring trend effectively separated survivor and non-survivor groups, starting 2 weeks before the end of the hospitalization period. Patients' score time points were also classified into mild, moderate, severe, and critical according to the symptomatic oxygen therapy administered. Fluctuations of the score should be recorded to highlight a favorable or unfortunate trend of the disease. The predictive score was found to reflect and anticipate the disease gravity, defined by the type of the oxygen support used, giving a proof of its clinical relevance. It offers a fast and reliable tool for supporting clinical decisions and, most important, triage in terms of not only prioritization but also allocation of limited medical resources, especially in the period when therapies are still symptomatic and many are under development. In fact, a prolonged and progressive increase of the score can suggest impaired chances of survival and/or an urgent need for intensive care unit admission.

Lipase elevation in serum of COVID-19 patients: frequency, extent of increase and clinical value.

OBJECTIVES: Previous studies reported lipase elevations in serum of COVID-19 patients trying to establish a causal link between SARS-CoV-2 infection and pancreatic damage. However, the degree and prevalence of hyperlipasemia was not uniform across studies. METHODS: We retrospectively evaluated 1,092 hospitalized patients with COVID-19 and at least one available lipase result. The number and frequency of patients with lipase above the upper reference limit (URL), >3 URL, and >6 URL were estimated. Correlations between lipase values and other biomarkers of organ or tissue damage were performed to identify possible extra-pancreatic sources of lipase release. The potential prognostic role of lipase to predict death and intensive care unit (ICU) admission during hospitalization was also evaluated. RESULTS: Lipase was >URL in 344 (31.5%) of COVID-19 patients. Among them, 65 (5.9%) and 25 (2.3%) had a peak lipase >3 URL and >6 URL, respectively. In the latter group, three patients had acute pancreatitis of gallstone or drug-induced etiology. In others, the etiology of lipase elevations appeared multifactorial and could not be directly related to SARS-CoV-2 infection. No correlation was found between lipase and other tested biomarkers of organ and tissue damage. Lipase concentrations were not different between survivors and non-survivors; however, lipase was significantly increased (p<0.001) in patients admitted to the ICU, even if the odds ratio for lipase as predictor of ICU admission was not significant. CONCLUSIONS: Lipase was elevated in ∼1/3 of COVID-19 patients, but the clinical significance of this finding is unclear and irrelevant to patient prognosis during hospitalization.

Sources and clinical significance of aspartate aminotransferase increases in COVID-19.

BACKGROUND: Aspartate aminotransferase (AST) is often increased in COVID-19 and, in some studies, AST abnormalities were associated with mortality risk. METHODS: 2054 hospitalized COVID-19 patients were studied. To identify sources of AST release, correlations between AST peak values and other biomarkers of tissue damage, i.e., alanine aminotransferase (ALT) for hepatocellular damage, creatine kinase (CK) for muscle damage, lactate dehydrogenase for multiorgan involvement, alkaline phosphatase and γ-glutamyltransferase for cholestatic injury, and C-reactive protein (CRP) for systemic inflammation, were performed and coefficients of determination estimated. The role of AST to predict death and intensive care unit admission during hospitalization was also evaluated. All measurements were performed using standardized assays. RESULTS: AST was increased in 69% of patients. Increases could be fully explained by summing the effects of hepatocellular injury [AST dependence from ALT, 66.8% [95% confidence interval (CI): 64.5-69.1)] and muscle damage [AST dependence from CK, 42.6% (CI: 39.3-45.8)]. We were unable to demonstrate an independent association of AST increases with worse outcomes. CONCLUSION: The mechanisms for abnormal AST in COVID-19 are likely multifactorial and a status related to tissue suffering could play a significant role. The clinical significance of AST elevations remains unclear.

Searching for a role of procalcitonin determination in COVID-19: a study on a selected cohort of hospitalized patients.

Objectives: Procalcitonin (PCT) has been proposed for differentiating viral vs. bacterial infections. In COVID-19, some preliminary results have shown that PCT testing could act as a predictor of bacterial co-infection and be a useful marker for assessment of disease severity. Methods: We studied 83 COVID-19 hospitalized patients in whom PCT was specifically ordered by attending physicians. PCT results were evaluated according to the ability to accurately predict bacterial co-infections and death in comparison with other known biomarkers of infection and with major laboratory predictors of COVID-19 severity. Results: Thirty-three (39.8%) patients suffered an in-hospital bacterial co-infection and 44 (53.0%) patients died. In predicting bacterial co-infection, PCT showed a relatively low accuracy (area under receiver-operating characteristic [ROC] curve [AUC]: 0.757; 95% confidence interval [CI]: 0.651-0.845), with a strength for detecting the outcome not significantly different from that of white blood cell count and C-reactive protein (CRP). In predicting patient death, PCT showed an AUC of 0.815 (CI: 0.714-0.892), not better than those of other more common laboratory tests, such as blood lymphocyte percentage (AUC: 0.874, p=0.19), serum lactate dehydrogenase (AUC: 0.860, p=0.47), blood neutrophil count (AUC: 0.845, p=0.59), and serum albumin (AUC: 0.839, p=0.73). Conclusions: Procalcitonin (PCT) testing, even when appropriately ordered, did not provide a significant added value in COVID-19 patients when compared with more consolidated biomarkers of infection and poor clinical outcome. The major application of PCT in COVID-19 is its ability, associated with a negative predictive value >90%, to exclude a bacterial co-infection when a rule-out cut-off (<0.25 µg/L) is applied.

A Comprehensive Appraisal of Laboratory Biochemistry Tests as Major Predictors of COVID-19 Severity.

CONTEXT.­: A relevant portion of coronavirus disease 2019 (COVID-19) patients develop severe disease with negative outcomes. Several biomarkers have been proposed to predict COVID-19 severity, but no definite interpretative criteria have been established to date for stratifying risk. OBJECTIVE.­: To evaluate 6 serum biomarkers (C-reactive protein, lactate dehydrogenase, D-dimer, albumin, ferritin, and cardiac troponin T) for predicting COVID-19 severity and to define related cutoffs able to aid clinicians in risk stratification of hospitalized patients. DESIGN.­: A retrospective study of 427 COVID-19 patients was performed. Patients were divided into groups based on their clinical outcome: nonsurvivors versus survivors and patients admitted to an intensive care unit versus others. Receiver operating characteristic curves and likelihood ratios were employed to define predictive cutoffs for evaluated markers. RESULTS.­: Marker concentrations at peak were significantly different between groups for both selected outcomes. At univariate logistic regression analysis, all parameters were significantly associated with higher odds of death and intensive care. At the multivariate analysis, high concentrations of lactate dehydrogenase and low concentrations of albumin in serum remained significantly associated with higher odds of death, whereas only low lactate dehydrogenase activities remained associated with lower odds of intensive care admission. The best cutoffs for death prediction were greater than 731 U/L for lactate dehydrogenase and 18 g/L or lower for albumin, whereas a lactate dehydrogenase activity lower than 425 U/L was associated with a negative likelihood ratio of 0.10 for intensive treatment. CONCLUSIONS.­: Our study identifies which biochemistry tests represent major predictors of COVID-19 severity and defines the best cutoffs for their use.