On-admission Multifactorial Evaluation of Inflammation as Prognostic Marker of Death in Patients Diagnosed With Coronavirus Infectious Disease (COVID-19) Syndrome
Conditions: SARS-CoV-2 Acute Respiratory Disease, Covid19
Sponsor: Groupe Hospitalier de la Rochelle Ré Aunis

 
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Intitulé de l’étude 
Covid-19 Pandemic Triage Score (STC-19)   
Sponsor 
Groupe Hospitalier de la Rochelle Ré Aunis 
NCT number 
NCT04371471 
PI 
Dr. Serge Bénéteaud 
Organisation responsible 
for the analysis (if different) 
NUMAHEALTH INTERNATIONAL 
Responsible for analysis 
(if different) 
Dr. Kamyar Hedayat 
Methodology of reference 
(in France) 
 MR-004     
  MR-005     
  MR-006  
 
Data sources 
   Medical records 
  Survey / Cohort / Register including data from the national health 
data system 
  Medicalization Program of Information Systems 
  Other source of Data  
Background 
The aim of the health system is to prevent the occurrence of COVID-19 
pneumonia and its progression to acute respiratory distress syndrome 
(ARDS), which has a high mortality rate. There is currently no known 
method of predicting which cases will progress to ARDS. In ARDS, 
inflammation of the lungs renders mechanical ventilation ineffective 
due to the occurrence of alveolar edema. 
 
Context of the study 
 
 
Inflammation is the common denominator in the mechanisms resulting 
in death, be it acute respiratory distress syndrome (ARDS), sepsis or end-
organ failure1. Many studies have already associated inflammatory 
burden with mortality. It remains unclear which markers of inflammation 
are most strongly correlated and at what point of hospitalization. C-
Reactive Protein (CRP) is a well-studied marker of acute inflammatory 
reactant in patients with COVID-192. However, there are other indicators 
or actors in acute inflammation. For example, the neutrophil-to-
lymphocyte ratio (NLR)3-9 is associated with mortality on admission for 
patients with COVID-194. It is has been referred to as the genito-thyroid 
index(GTi)10. Another marker is serum cortisol. High serum cortisol at 
admission to the hospital was associated with higher mortality in one 
study11, but the opposite has also been observed12. Tissue levels have 
not consistently been associated with severity of illness13,14. Our group 
(KMH, JCL) has demonstrated that the effective tissue-level activity of 
cortisol can be modeled using a complete blood count with differential 

 
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(CBC)15 in chronic heart failure and acute myocardial infarction (AMI)16,17 
and that the model of admission cortisol activity was superior to serum 
cortisol in predicting mortality in AMI8. 
All current solutions focus on targeted treatment of the virus in an 
attempt to neutralize its epidemic spread and correct its downstream 
effects on the infected patient's body. We propose a radically different 
orientation which consists of starting from the patient, rather than the 
viral aggressor, by analyzing the state of his or her current adaptive 
response to the viral aggression. 
Objective(s) 
To evaluate changes in biomarkers associated with inflammation to 
determine : 
1) at what point in the first 5 days of hospitalization would factors 
associated with deterioration or death be present, 
2) which biomarker or indexes related to inflammation best predicted 
this deterioration or death. 
Design 
Single center retrospective study 
 
Study population 
 
Patient with clinical signs of CoV-2-SARS infection and signs of severity 
(polypnea, saturation < 90% room air, dyspnea, systolic blood pressure 
< 90 mmHg, altered consciousness, somnolence, confusion) and/or co-
morbidities (> 70 years of age, Respiratory pathology at risk of 
decompensation, Chronic renal failure on dialysis, Heart failure or IV, 
Cirrhosis ≥ B, Cardiovascular history, Diabetes with poor balance or co-
morbidities, Immunosuppression, Dementia) 
Ethics committee 
Study approved by the local ethics committee on 7 May 2020 
Method 
From medical records patients’ information, codded, anonymized data 
will be entered regarding age, sex, blood pressure, oxygen saturation, 
survival status, CRP, and a CBC with differential from the time of 
admission, days 2-3 and 3-5. 
Statistical analysis plan 
Demographic and biologic data will be used to describe the study 
population and to calculate the STC-19 score. Patient status (deceased 
or alive within 28 days after hospital admission) will be recorded. 
Categorical data will be collected for inclusion/exclusion criteria, 
gender, and patient living status. Continuous data will be collected for 
the complete blood count test. 
Means and standard deviations, numbers, percentages and confidence 
intervals will be used to describe quantitative and qualitative variables, 
respectively. 
Association between factors (age, creatinine, CRP, cortisol, genito-
thyroid index) and death will be studied. 
The STC-19 score will be calculated by the NumaHealth International 
statistician according to their proprietary calculation. 

 
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Justification of the public 
interest character of the 
study  
If this score is validated, it will provide care recommendations 
determined by the number of factors in the severe or moderately 
severe pathophysiology zones.  
It will allow an immediate reduction in access to hospital resources and 
a reduction in the over-servicing of emergency and intensive care units 
when the patient's clinical condition permits without secondary risk to 
the patient. 
Timetable for the study and 
provisional schedule for 
communicating the results 
Data collection of patients hospitalized between March and May 2020 : 
from June to July 2020 
Analysis and communication of results : From August to October 2020 
References 
1.Wendel Garcia PD, Fumeaux T, Guerci P, et al. Prognostic factors 
associated with mortality risk and disease progression in 639 critically ill 
patients with COVID-19 in Europe: Initial report of the international 
RISC-19-ICU prospective observational cohort. EClinicalMedicine. 
2020;25:100449. 
 
2.Liu C, Liu X, Mao Z, et al. Interpretable Machine Learning Model for 
Early Prediction of Mortality in ICU Patients with Rhabdomyolysis. Med 
Sci Sports Exerc. 2021;53(9):1826-1834. 
 
3.Hedayat K, Schuff BM, Lapraz JC, et al. Genito-Thyroid index: a global 
systems approach to the neutrophil-to-lymphocyte ratio according to 
the theory of Endobigoeny applied to ambulatory patients with chronic 
heart failure. Journal of Cardiology and Clinical Research. 
2017;5(1):1091-1097. 
 
4.Li X, Liu C, Mao Z, et al. Predictive values of neutrophil-to-lymphocyte 
ratio on disease severity and mortality in COVID-19 patients: a 
systematic review and meta-analysis. Critical care. 2020;24(1):647. 
 
5.Ma A, Cheng J, Yang J, Dong M, Liao X, Kang Y. Neutrophil-to-
lymphocyte ratio as a predictive biomarker for moderate-severe ARDS 
in severe COVID-19 patients. Critical care. 2020;24(1):288. 
 
6.Zeng ZY, Feng SD, Chen GP, Wu JN. Predictive value of the neutrophil 
to lymphocyte ratio for disease deterioration and serious adverse 
outcomes in patients with COVID-19: a prospective cohort study. BMC 
Infect Dis. 2021;21(1):80. 
 
7.de Jager CP, Wever PC, Gemen EF, et al. The neutrophil-lymphocyte 
count ratio in patients with community-acquired pneumonia. PloS one. 
2012;7(10):e46561. 
 
8.de Jager CP, van Wijk PT, Mathoera RB, de Jongh-Leuvenink J, van der 
Poll T, Wever PC. Lymphocytopenia and neutrophil-lymphocyte count 
ratio predict bacteremia better than conventional infection markers in 
an emergency care unit. Crit Care. 2010;14(5):R192. 

 
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9.Hedayat K, Lapraz J-C, Schuff BM, et al. Genito-Thyroid index: a global 
systems approach to the neutrophil-to-lymphocyte ratio according to 
the theory of Endobiogeny applied to ambulatory patients with chronic 
heart failure. J Cardio Clin Res. 2017;5(1):1091-1097. 
 
10.Hedayat KM. The theory of Endobiogeny: biological modeling using 
downstream physiologic output as inference of upstream global 
systems regulation J Complex Health Sci. 2020;3(1):1-8. 
 
11. Guven M, Gultekin H. Could serum total cortisol level at admission 
predict mortality due to coronavirus disease 2019 in the intensive care 
unit? A prospective study. Sao Paulo Med J. 2021;139(4):398-404. 
 
12.Tan T, Khoo B, Mills EG, et al. Association between high serum total 
cortisol concentrations and mortality from COVID-19. Lancet Diabetes 
Endocrinol. 2020;8(8):659-660. 
 
13.Oakley RH, Cidlowski JA. The biology of the glucocorticoid receptor: 
new signaling mechanisms in health and disease. The Journal of allergy 
and clinical immunology. 2013;132(5):1033-1044. 
 
14.Groeneweg FL, Karst H, de Kloet ER, Joels M. Rapid non-genomic 
effects of corticosteroids and their role in the central stress response. 
The Journal of endocrinology. 2011;209(2):153-167. 
 
15.Hedayat KM. The theory of endobiogeny: biological modeling using 
downstream physiologic output as inference of upstream global system 
regulation. J Compl Health Sci 2020;3(1):1-8. 
 
16.Hedayat K, Lapraz J-C, Schuff BM, et al. A novel approach to 
modeling tissue-level activity of cortisol levels according to the theory 
of Endobiogeny, applied to chronic heart failure. J Complex Health Sci. 
2018;1(1):2-8. 
 
17.Braukyliene R, Hedayat KM, Zajanckauskiene L, et al. Prognostic 
Value of Cortisol Index of Endobiogeny in Acute Myocardial Infarction 
Patients. Medecina. 2021;57:12.