Antimicrobial resistance is a threat to global public health and comes with increased death rates, health problems and economic costs. Annual associated deaths have been estimated at 700,000 events worldwide, and is predicted to increase to 10 million by 2050 without action. Overuse of antibiotics is one of the main drivers and is particularly prevalent among people with respiratory tract infections (RTIs). These account for 60% of antibiotic prescribing in primary care, itself responsible for around 75% of all health service antibiotic prescribing. As antibiotics generally only have little effect on self-limiting RTIs, current guidelines advocate to opt for a no or delayed antibiotic prescribing strategy in the majority of RTIs in primary care. Reducing unnecessary within-episode antibiotic prescribing could represent a significant opportunity to reduce antibiotic exposure at minimal risk to patient care. Data on repeat antibiotic prescriptions within the same clinical infection episode are however lacking.
Objectives of this study are therefore (1) to assess rates of within-RTI-episode repeat antibiotic prescriptions, (2) to estimate the consecutive duration of antibiotic use within episodes, and (3) to investigate possible predictors for within-episode repeat antibiotic prescriptions.
For this purpose, a retrospective cohort study will be conducted within patients who have consulted a GP for RTIs and who were prescribed antibiotics during that episode. The rate for repeat antibiotic prescribing will be estimated and potential predictors will be assessed.
Antimicrobial resistance is a threat to global public health and comes with increased mortality, morbidity and economic costs. Overuse of antibiotics is one of the main drivers and is particularly prevalent among people with respiratory tract infections (RTIs). As antibiotics generally only have little effect on self-limiting RTIs, current guidelines advocate to opt for a no or delayed antibiotic prescribing strategy in the majority of RTIs in primary care. Reducing unnecessary within-episode antibiotic prescribing could represent a significant opportunity to reduce antibiotic exposure at minimal risk to patient care. Data on repeat antibiotic prescriptions within the same clinical infection episode are however lacking.
Objectives of this study are therefore to assess rates of within-RTI-episode repeat antibiotic prescriptions, to estimate the consecutive duration of antibiotic use within episodes, and to identify possible predictors for within-episode repeat antibiotic prescriptions.
For this purpose, all individuals with a CPRD code for an RTI between March 2018 and January 2022 (pre- and intra-COVID pandemic periods) will be included in this study. Selected individuals must have had at least one antibiotic prescription within 1 day before or during the coded RTI episode. Each RTI episode is considered to start at the first RTI diagnosis and ends 28 days after the last following GP consultation, allowing a gap of no more than 28 days between two consecutive consultations.
The primary outcome of interest is the rate of repeat antibiotic prescriptions within the same RTI episode. This is defined as having had at least one additional antibiotic prescription at least one day after the primary prescription. Analyses will be stratified by calendar time (pre- and intra-COVID), age (children and adults), RTI type (lower, upper, unspecified), and type of antibiotics (penicillins, sulphonamides, tetracyclines, macrolides, quinolones, other). Using stepwise logistic regression, potential predictors for repeat antibiotic prescribing will be identified.
The primary outcome of interest is the rate of repeat antibiotic prescriptions within the same RTI episode. This is defined as having had at least one additional antibiotic prescription at least one day after the primary prescription. Multiple prescriptions on the same day will be considered the same prescribing event.
Secondary outcomes of interest are (1) the total number of repeat antibiotic prescriptions within the same RTI episodes, (2) the corresponding cumulative expected duration of antibiotic use within RTI episodes, and (3) the time between first and repeat antibiotic prescription. The expected duration of use will be calculated for each antibiotic prescription using written dosage instructions, pack quantities and contents. Expected duration will be expressed as the number of days that were covered by an antibiotic prescription. In the event of overlap between the primary and repeat prescription, or between repeat prescriptions, the number of days will be extended by the number of overlap days.
Arief Lalmohamed - Chief Investigator - Utrecht University
Arief Lalmohamed - Corresponding Applicant - Utrecht University
Alastair Hay - Collaborator - University of Bristol
Albert Bolhuis - Collaborator - University of Bath
Janneke van de Wijgert - Collaborator - University Medical Centre Utrecht
Martin Gulliford - Collaborator - King's College London (KCL)
Roderick P. Venekamp - Collaborator - University Medical Centre Utrecht
Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation