Early biochemical analysis of COVID-19 patients helps severity prediction.

COVID-19 pandemic has put the protocols and the capacity of our Hospitals to the test. The management of severe patients admitted to the Intensive Care Units has been a challenge for all health systems. To assist in this challenge, various models have been proposed to predict mortality and severity, however, there is no clear consensus for their use. In this work, we took advantage of data obtained from routine blood tests performed on all individuals on the first day of hospitalization. These data has been obtained by standardized cost-effective technique available in all the hospitals. We have analyzed the results of 1082 patients with COVID19 and using artificial intelligence we have generated a predictive model based on data from the first days of admission that predicts the risk of developing severe disease with an AUC = 0.78 and an F1-score = 0.69. Our results show the importance of immature granulocytes and their ratio with Lymphocytes in the disease and present an algorithm based on 5 parameters to identify a severe course. This work highlights the importance of studying routine analytical variables in the early stages of hospital admission and the benefits of applying AI to identify patients who may develop severe disease.

Immune cell population and cytokine profiling suggest age dependent differences in the response to SARS-CoV-2 infection

Aging population is at higher risk of developing severe COVID-19, including hospitalization and death. In this work, to further understand the relationship between host age-related factors, immunosenescence/exhaustion of the immune system and the response to the virus, we characterized immune cell and cytokine responses in 58 COVID-19 patients admitted to the hospital and 40 healthy controls of different age ranges. Lymphocyte populations and inflammatory profiles were studied in blood samples, using different panels of multicolor flow cytometry. As expected, our analysis reveals differences at both the cellular and cytokine level in COVID-19 patients. Interestingly, when the age range analysis was carried out, the immunological response to the infection was found to differ with age, being especially affected in the group of 30–39 years. In this age range, an increased exhausted T cell response and a decrease of naïve T helper lymphocytes was found in patients, as well as a reduced concentration of the proinflammatory TNF, IL-1β and IL-8 cytokines. Besides, the correlation between age and the study variables was evaluated, and multiple cell types and interleukins were found to correlate with donor age. Notably, the correlations of T helper naïve and effector memory cells, T helper 1–17 cells, TNF, IL-10, IL-1β, IL-8, among others, showed differences between healthy controls and COVID-19 patients. Our findings, in the context of other previous studies, suggest that aging affects the behavior of the immune system in COVID-19 patients. They suggest that young individuals are able to mount an initial response to SARS-CoV-2, but some of them present an accelerated exhaustion of the cell response and an insufficient inflammatory response, resulting in a moderate to severe COVID-19. On the other hand, in older patients there is a smaller immune cell response to the virus, reflected in fewer differences in immune populations between COVID-19 patients and controls. Nevertheless, old patients show more evidence of an inflammatory phenotype, suggesting that the underlying inflammation associated with their age is exacerbated by the SARS-CoV-2 infection.

Clinical evaluation of the Procleix SARS-CoV-2 assay, a sensitive, high-throughput test that runs on an automated system.

Testing is crucial in controlling COVID-19. The Procleix® SARS-CoV-2 assay, a transcription-mediated amplification nucleic acid test that runs on an automated system, was evaluated using inactivated virus and clinical samples. The sensitivity of the assay was assessed using heat-inactivated SARS-CoV-2 and compared to 3 other tests. Clinical validation utilized 2 sets of samples: (1) Nasal, nasopharyngeal and oropharyngeal samples (n = 963) from asymptomatic individuals, and (2) nasopharyngeal samples from symptomatic patients: 100 positive and 100 negative by RT-PCR. The Procleix assay had greater sensitivity (3-fold to 100-fold) than the comparators and had high specificity (100%) in asymptomatic subjects. In symptomatic patients, the Procleix assay detected 100% of PCR-positives and found 24 positives in the initial PCR-negatives. Eighteen of these were confirmed positive and 6 were inconclusive. These studies showed that the Procleix SARS-CoV-2 assay was a sensitive and specific tool for detecting COVID-19.

Analysis of SARS-CoV-2 reverse transcription-quantitative polymerase chain reaction cycle threshold values vis-à-vis anti-SARS-CoV-2 antibodies from a high incidence region.

OBJECTIVES: To examine the relationship between antibody status and cycle threshold (Ct) values, the prognostic value of the latter for COVID-19 patients, and the inter-assay comparability of SARS-CoV-2 Ct values. METHODS: In 347 COVID-19 inpatients, SARS-CoV-2 Ct values (via reverse transcription-quantitative polymerase chain reaction) on admission were compared between 2 assays and correlated with the antibody response (in the course of the disease), the clinical course and the time since onset of symptoms. RESULTS: Ct values for 2 of 3 target genes showed significant differences between the 2 assays used (P=0.012 and P<0.0001). Ct values were significantly higher for antibody positive patients (P<0.0001) and positively correlated with the amount of time since onset of symptoms (R: 0.332-0.363; P<0.001). Patients with fatal outcomes showed higher viral loads than survivors (P<0.0001). CONCLUSIONS: Ct values depend strongly on assay used and target gene examined and should not be used as quantitative values to guide therapeutic or diagnostic decisions. The inverse association between antibody status and viral load suggests that antibodies contribute to the elimination of the virus, independent of the outcome, which is influenced by the viral load on admission and might depend more strongly on other parts of the immune response.

Clinical correlates of anti-SARS-CoV-2 antibody profiles in Spanish COVID-19 patients from a high incidence region.

Laboratory testing for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consists of two pillars: the detection of viral RNA via rt-PCR as the diagnostic gold standard in acute cases, and the detection of antibodies against SARS-CoV-2. However, concerning the latter, questions remain about their diagnostic and prognostic value and it is not clear whether all patients develop detectable antibodies. We examined sera from 347 Spanish COVID-19 patients, collected during the peak of the epidemic outbreak in Spain, for the presence of IgA and IgG antibodies against SARS-CoV-2 and evaluated possible associations with age, sex and disease severity (as measured by duration of hospitalization, kind of respiratory support, treatment in ICU and death). The presence and to some degree the levels of anti-SARS-CoV-2 antibodies depended mainly on the amount of time between onset of symptoms and the collection of serum. A subgroup of patients did not develop antibodies at the time of sample collection. Compared to the patients that did, no differences were found. The presence and level of antibodies was not associated with age, sex, duration of hospitalization, treatment in the ICU or death. The case-fatality rate increased exponentially with older age. Neither the presence, nor the levels of anti-SARS-CoV-2 antibodies served as prognostic markers in our cohort. This is discussed as a possible consequence of the timing of the sample collection. Age is the most important risk factor for an adverse outcome in our cohort. Some patients appear not to develop antibodies within a reasonable time frame. It is unclear, however, why that is, as these patients differ in no respect examined by us from those who developed antibodies.