Study type

Study topic

Disease /health condition
Human medicinal product

Study type

Non-interventional study

Scope of the study

Assessment of risk minimisation measure implementation or effectiveness
Other

If ‘other’, further details on the scope of the study

Negative control

Data collection methods

Secondary use of data
Non-interventional study

Non-interventional study design

Case-control
Study drug and medical condition

Anatomical Therapeutic Chemical (ATC) code

(J01) ANTIBACTERIALS FOR SYSTEMIC USE
ANTIBACTERIALS FOR SYSTEMIC USE

Medical condition to be studied

Myocardial infarction
Population studied

Short description of the study population

Patients of all ages with an active or died registration status during the study period of January 1st, 2004 to December 31st, 2009 in the Invision Data Mart. Patients must have attained one year of enrolment in the database at the beginning of the study period.

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)

Estimated number of subjects

80000
Study design details

Main study objective

to assess the absence of association between antibiotics use and myocardial infarction by replicationg a nested case-control design in a US claims database (LabRx)

Outcomes

To estimate the risk of myocardial infarction associated with antibiotics exposure (users and non-users)To estimate the risk of myocardial infarction associated with various antibiotics classesTo estimate the risk of myocardial infarction associated with specific individual antibioticsTo assess the effect of dose and duration of use for specific individual antibiotics, To replicate the analysis using a population-based case-control design

Data analysis plan

We will compute odds ratios (OR) and 95% confidence intervals of first occurrence of acute myocardial infarction associated with current use of antibiotics (as a group and different classes and individual drugs when possible) as compared to non-use with conditional logistic regression. Age, sex, calendar year, and other variables will be introduced in the model to control for potential confounding. Also, dose and duration-relationships will be examined.
Documents
Study results
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