Sociodemographic, clinical and pharmacological characteristics associated with the prognosis of patients with SARS-CoV-2 infection (Características sociodemográficas, clínicas y farmacológicas asociadas con el pronóstico en pacientes con infección por SARS-CoV-2)

Study type

• Study topic:
  Human medicinal product

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

  Disease epidemiology

  Drug utilisation

  Effectiveness study (incl. comparative)
• Data collection methods:
  Secondary use of data

Non-interventional study

• Non-interventional study design:
  Cohort

Study drug and medical condition

• Anatomical Therapeutic Chemical (ATC) code:
  (J07BC20) combinations

  combinations
• Medical condition to be studied:
  COVID-19

Population studied

• Short description of the study population:
  Patients diagnosed with COVID-19 identified from the SIDIAP database for the study period of January 2020 to April 2020.
• Age groups:
  • Paediatric Population (< 18 years)

    • Neonate

      • Preterm newborn infants (0 – 27 days)
      • Term newborn infants (0 – 27 days)
    • Infants and toddlers (28 days – 23 months)
    • Children (2 to < 12 years)
    • Adolescents (12 to < 18 years)
  • Adult and elderly population (≥18 years)

    • Adults (18 to < 65 years)

      • Adults (18 to < 46 years)
      • Adults (46 to < 65 years)
    • Elderly (≥ 65 years)

      • Adults (65 to < 75 years)
      • Adults (75 to < 85 years)
      • Adults (85 years and over)
• Special population of interest:
  Immunocompromised

  Other
• Special population of interest, other:
  COVID-19 patients
• Estimated number of subjects:
  800000

Study design details

• Main study objective:
  Assess infection rate for SARS-CoV-2 and describe sociodemographic, clinical and pharmacological characteristics.
• Outcomes:
  Infection rate for SARS-CoV-2, Association between sociodemographic, clinical and pharmacological characteristics with the prognosis of COVID19 patients
• Data analysis plan:
  Exploration of events, logistic conditional regression, risk estimation