Low anti-SARS-CoV-2 S antibody levels predict increased mortality and dissemination of viral components in the blood of critical COVID-19 patients.

BACKGROUND: Anti-SARS-CoV-2 S antibodies prevent viral replication. Critically ill COVID-19 patients show viral material in plasma, associated with a dysregulated host response. If these antibodies influence survival and viral dissemination in ICU-COVID patients is unknown. PATIENTS/METHODS: We studied the impact of anti-SARS-CoV-2 S antibodies levels on survival, viral RNA-load in plasma, and N-antigenaemia in 92 COVID-19 patients over ICU admission. RESULTS: Frequency of N-antigenaemia was >2.5-fold higher in absence of antibodies. Antibodies correlated inversely with viral RNA-load in plasma, representing a protective factor against mortality (adjusted HR [CI 95%], p): (S IgM [AUC ≥ 60]: 0.44 [0.22; 0.88], 0.020); (S IgG [AUC ≥ 237]: 0.31 [0.16; 0.61], <0.001). Viral RNA-load in plasma and N-antigenaemia predicted increased mortality: (N1-viral load [≥2.156 copies/ml]: 2.25 [1.16; 4.36], 0.016); (N-antigenaemia: 2.45 [1.27; 4.69], 0.007). CONCLUSIONS: Low anti-SARS-CoV-2 S antibody levels predict mortality in critical COVID-19. Our findings support that these antibodies contribute to prevent systemic dissemination of SARS-CoV-2.

Viral RNA load in plasma is associated with critical illness and a dysregulated host response in COVID-19.

BACKGROUND: COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. METHODS: A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. RESULTS: The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p < 0.001). Critical patients had higher viral RNA loads in plasma than non-critically ill patients, with non-survivors showing the highest values. When outpatients and ward patients were compared, viral RNAemia did not show significant associations in the multivariate analysis. In contrast, when ward patients were compared with ICU patients, both viral RNAemia and viral RNA load in plasma were associated with critical illness (OR [CI 95%], p): RNAemia (3.92 [1.183-12.968], 0.025), viral RNA load (N1) (1.962 [1.244-3.096], 0.004); viral RNA load (N2) (2.229 [1.382-3.595], 0.001). Viral RNA load in plasma correlated with higher levels of chemokines (CXCL10, CCL2), biomarkers indicative of a systemic inflammatory response (IL-6, CRP, ferritin), activation of NK cells (IL-15), endothelial dysfunction (VCAM-1, angiopoietin-2, ICAM-1), coagulation activation (D-Dimer and INR), tissue damage (LDH, GPT), neutrophil response (neutrophils counts, myeloperoxidase, GM-CSF) and immunodepression (PD-L1, IL-10, lymphopenia and monocytopenia). CONCLUSIONS: SARS-CoV-2 RNAemia and viral RNA load in plasma are associated with critical illness in COVID-19. Viral RNA load in plasma correlates with key signatures of dysregulated host responses, suggesting a major role of uncontrolled viral replication in the pathogenesis of this disease.

MR- proADM to detect specific types of organ failure in infection.

BACKGROUND: Following the SEPSIS-3 consensus, detection of organ failure as assessed by the SOFA (Sequential Organ Failure Assessment) score, is mandatory to detect sepsis. Calculating SOFA outside of the Intensive Care Unit (ICU) is challenging. The alternative in this scenario, the quick SOFA, is very specific but less sensible. Biomarkers could help to detect the presence of organ failure secondary to infection either in ICU and non-ICU settings. MATERIALS AND METHODS: We evaluated the ability of four biomarkers (C-Reactive protein (CRP), lactate, mid-regional proadrenomedullin (MR-proADM) and procalcitonin (PCT)) to detect each kind of organ failure considered in the SOFA in 213 patients with infection, sepsis or septic shock, by using multivariate regression analysis and calculation of the area under the receiver operating curve (AUROC). RESULTS: In the multivariate analysis, MR-proADM was an independent predictor of five different failures (respiratory, coagulation, cardiovascular, neurological and renal). In turn, lactate predicted three (coagulation, cardiovascular and neurological) and PCT two (cardiovascular and renal). CRP did not predict any of the individual components of SOFA. The highest AUROCs were those of MR-proADM and PCT to detect cardiovascular (AUROC, CI95%): MR-proADM (0.82 [0.76-0.88]), PCT (0.81 [0.75-0.87] (P < .05) and renal failure: MR-proADM (0.87 [0.82-0.92]), PCT (0.81 [0.75-0.86]), (P < .05). None of the biomarkers tested was able to detect hepatic failure. CONCLUSIONS: In patients with infection, MR-proADM was the biomarker detecting the largest number of SOFA score components, with the exception of hepatic failure.

Superior accuracy of mid-regional proadrenomedullin for mortality prediction in sepsis with varying levels of illness severity.

BACKGROUND: The use of novel sepsis biomarkers has increased in recent years. However, their prognostic value with respect to illness severity has not been explored. In this work, we examined the ability of mid-regional proadrenomedullin (MR-proADM) in predicting mortality in sepsis patients with different degrees of organ failure, compared to that of procalcitonin, C-reactive protein and lactate. METHODS: This was a two-centre prospective observational cohort, enrolling severe sepsis or septic shock patients admitted to the ICU. Plasma biomarkers were measured during the first 12 h of admission. The association between biomarkers and 28-day mortality was assessed by Cox regression analysis and Kaplan-Meier curves. Patients were divided into three groups as evaluated by the Sequential Organ Failure Assessment (SOFA) score. The accuracy of the biomarkers for mortality was determined by area under the receiver operating characteristic curve (AUROC) analysis. RESULTS: A total of 326 patients with severe sepsis (21.7%) or septic shock (79.3%) were enrolled with a 28-day mortality rate of 31.0%. Only MR-proADM and lactate were associated with mortality in the multivariate analysis: hazard ratio 8.5 versus 3.4 (p < 0.001). MR-proADM showed the best AUROC for mortality prediction at 28 days in the analysis over the entire cohort (AUROC [95% CI] 0.79 [0.74-0.84]) (p < 0.001). When patients were stratified by the degree of organ failure, MR-proADM was the only biomarker to predict mortality in all severity groups (SOFA ≤ 6, SOFA = 7-12, and SOFA ≥ 13), AUROC [95% CI] of 0.75 [0.61-0.88], 0.74 [0.66-0.83] and 0.73 [0.59-0.86], respectively (p < 0.05). All patients with MR-proADM concentrations ≤0.88 nmol/L survived up to 28 days. In patients with SOFA ≤ 6, the addition of MR-proADM to the SOFA score increased the ability of SOFA to identify non-survivors, AUROC [95% CI] 0.70 [0.58-0.82] and 0.77 [0.66-0.88], respectively (p < 0.05 for both). CONCLUSIONS: The performance of prognostic biomarkers in sepsis is highly influenced by disease severity. MR-proADM accuracy to predict mortality is not affected by the degree of organ failure. Thus, it is a good candidate in the early identification of sepsis patients with moderate disease severity but at risk of mortality.