Protein Electrophoresis as a Tool for Complications Prediction in COVID-19 Hospitalised Patients

The inflammation is central in COVID-19 infections. Our aim is to evaluate the clinical value of measuring inflammation by using serum protein electrophoresis (SPE). SPE evaluation of inflammation should be able to predict outcome, follow up evolution or treatment efficacy in patients with coronavirus infection and thus anticipate their evolution to severe viral infection and allow an optimal clinical management. SPE inflammation diagnostics will be benchmarked with other diagnostics of inflammation, currently used more routinely.

In late December 2019, an outbreak of an emerging respiratory disease (COVID-19) caused by a novel coronavirus named SARS-CoV-2 began in Wuhan City, Hubei Province, China and quickly spread in a substantial number of countries. The epidemic was declared a pandemic by the Word Health Organization (WHO) on 12 March 2020. SARS-CoV-2 has demonstrated the capability to spread rapidly, leading to significant impacts on healthcare systems and causing societal disruption.

Both clinical and epidemiological features of patients with COVID-19 have recently been reported, demonstrating that the SARS-CoV-2 infection can be asymptomatic in some cases or symptomatic in others. Symptomatology usually begins as mild with fever, fatigue, dry cough, and occasional dyspnea. In a minority of patients, a sudden onset of severe symptoms may develop 5-8 days into the illness including shortness of breath, pneumonitis, acute respiratory distress syndrome (ARDS) and multi organ dysfunction leading to intensive care unit (ICU) admission and high mortality. In some cases, accumulating evidence suggests that severe COVID-19 symptoms could be due to a cytokine storm syndrome. As of May 3rd 2020, the virus had infected 3,349,786 patients worldwide with more than 238,600 deaths, more often among older patients with underlying health conditions.

With caseloads overwhelming hospitals and resources stretched thin in this surging pandemic (high demand for oxygen, prolonged ventilation and even extracorporeal membrane oxygenation (ECMO), particularly for patients with acute ARDS), there is an urgent need to enhance clinical skills in order to predict from the many mild cases those few that will progress to critical illness allowing a more efficient resource allocation and clinical management.

Several studies on patient blood have described features that were most predictive of ARDS. These studies showed that severe cases, compared to mild cases, had : 1) older age; 2) abnormalities in chest scanning (CT) such as multiple patch-like shadows and ground glass opacity; 3) organ and coagulation dysfunction with a higher levels of alanine aminotransferase (ALT), lactate dehydrogenase (LDH), C-reactive protein (CRP), ferritin and D-dimer; 4) as well as markedly higher levels of immunological characteristics such as IL-2R, IL-6, IL-10, and TNF- α ; 5) and an absolute T lymphocytes (CD4+ and CD8+ T cells) number markedly lower in nearly all severe cases. These observations suggest that severity and mortality might be due to virally driven systemic hyperinflammation secondary to failure of the immune response to control infection (as shown for other viruses).

With this study we want to caracterize the predictive performance of the serum inflammation profiles by protein electrophoresis, associated with clinical, radiological and biological risk factors for worsening. This study is a prospective, observational study conducted on patients hospitalized for an infection with the SARS-CoV-2 virus.

Eligibility Criteria:
Inclusion Criteria:

* Male of female aged 18 or over
* Patients with at least one of the following diagnostic criteria, allowing to suspect an infection by the virus SARS-CoV- 2 :

  * Clinical picture with fever, and/or exertional dyspnea, and/or PO2 \< 80mmHg
  * And/or chest scanner very suggestive or compatible with a COVID-19 infection
  * And/or a RT-PCR positive result already known
* Hospitalized patient in a COVID-19 medical unit, based on one or several diagnostic elements described
* Possibility to collect blood and urine samples as described in protocol
* Patients informed of the study, having understood it, and who didn't oppose to their participation

Exclusion Criteria:

* Clinical condition justifying immediate hospitalization in the intensive care unit
* During the initial patient management, an immediate need of oxygen requiring intubation and/or oxygen supply greater than 6 liters / minute
* Patients under legal protection
* Pregnant or breastfeeding women