CASE AND CONTROLS NESTED IN AN AMBISPECTIVE COHORT TO EVALUATE THE EFFECT OF CO-MEDICATION ON THE EVOLUTION OF SARS-CoV-2 CORONAVIRUS INFECTION (COVID-19) (HULP-COVID19-ACE2-20)

Study type

• Study type:
  Non-interventional study
• Scope of the study:
  Assessment of risk minimisation measure implementation or effectiveness

  Disease epidemiology

Non-interventional study

• Non-interventional study design:
  Cohort

  Case-control

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (A01AD08) becaplermin

  becaplermin

  (S03CA01) dexamethasone and antiinfectives

  dexamethasone and antiinfectives
• Medical condition to be studied:
  Coronavirus infection

Population studied

• Age groups:
  Term newborn infants (0 – 27 days)

  Infants and toddlers (28 days – 23 months)

  Children (2 to < 12 years)

  Adolescents (12 to < 18 years)

  Adults (18 to < 46 years)

  Adults (46 to < 65 years)

  Adults (65 to < 75 years)

  Adults (75 to < 85 years)

  Adults (85 years and over)
• Special population of interest:
  Renal impaired

  Hepatic impaired

  Immunocompromised

  Pregnant women
• Estimated number of subjects:
  3500

Study design details

• Main study objective:
  (i) To assess the association of previous/concomitant use of drugs or vaccines with the evolution of COVID-19.(ii) To assess the factors associated with the evolution of COVID-19 in a universal cohort of patients cared for in the hospitals
• Outcomes:
  • Combined variable that includes:- Death- Severe pneumonia (at least one criterion from each group): Fever, or Suspected respiratory infection and respiratory rate of ≥30, or SaO2 ambient air <93%- Need to be admitted to the Intensive Care Unit- Need for mechanical ventilation- Need for FiO2 above 40%- Criteria for respiratory distress, (i)To establish what other chronic treatments are factors associated with the evolution of COVID-19.(ii) To establish which hospital treatments are factors associated with the evolution of COVID-19.(iii) To establish what previous diseases and clinical characteristics are associated with the evolution of COVID-19.(iv)Establish that analytical values are factors associated with the evolution of COV
• Data analysis plan:
  Having overcome the primary and secondary objectives, we proposed to be able to model some of the clinically and statistically relevant variables in order to make predictions of outcome variables, such as survival or prognosis, using propensity score ajustment.