ASSOCIATION BETWEEN THE USE OF DRUGS IN CHRONIC PAIN AND THE INCIDENCE AND SEVERITY OF COVID-19 INFECTION: A CASE-POPULATION STUDY (DC-COVID19)

Study type

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

Non-interventional study

• Non-interventional study design:
  Case-control

Study drug and medical condition

• Medical condition to be studied:
  Coronavirus test positive

Population studied

• Age groups:
  • 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
• Estimated number of subjects:
  500

Study design details

• Main study objective:
  To assess if analgesic treatments and chronic pain have any impact on the prevalence and severity of COVID-19 infection through collecting population data from patients with confirmed COVID-19 with different evolution.
• Outcomes:
  - To assess the association between the use of drugs and the COVID-19 infection.- To assess the association between the use of drugs and the COVID-19 infection related to the patient evolution.
• Data analysis plan:
  500/5000Univariate: The proportion of patients on NSAIDs, corticosteroids, opioids, anticonvulsants, antidepressants, lidocaine, cannabinoids (together and separately) before the date of admission (index date) will be calculated and compared with population exposure to these drugs in a random sample of controls from databases of the Pain Units (last 6 months) and paired with the cases by age (exact), sex, Autonomous Community and month of the year. The crude OR and its 95% CI will be calculated for the association between the use of these drugs and the four outcome variables mentioned (admission by COVID-19, admission to the ICU by COVID-19, death by COVID-19 and a combined variable of the three).Multivariate: For each of the outcome variables, a conditioned logistic regression model will be constructed and the adjusted OR for comorbidities and other treatments that the patient would have taken will be estimated.