Co-resistance between oral antibiotics for pyelonephritis and those for cystitis—applying an escalation antibiogram model to local community data

Objectives:
We applied an escalation antibiogram to community urine data to assess how presumptive resistance to first-line antibiotics for cystitis affects resistance to antibiotics used to treat pyelonephritis.

Methods:
We extracted susceptibility data from Escherichia coli isolates grown from urine samples from general practice during a 5 year period (2019–2023) in a region served by three NHS hospital trusts. Female patients over 18 years old were included, giving a total of 130 514 isolates. We applied a Bayesian model to estimate antibiotic resistance rates for oral pyelonephritis antibiotics, when presuming resistance to each of the first-line antibiotics used for cystitis. The model estimates the probability of resistance with 95% credible intervals and was applied to a variety of patient groups based on age and history of recurrent urinary tract infections.

Results:
Resistance to cystitis antibiotics has a marked effect on the probability of resistance to oral antibiotics used to treat pyelonephritis. In particular, amoxicillin/clavulanate should be avoided for pyelonephritis if resistance to pivmecillinam is presumed, because predicted resistance rates exceed 50%. For patients with presumed resistance to nitrofurantoin or trimethoprim, the optimal pyelonephritis antibiotic depends on both age group and history of past infections.

Conclusions:
Analysis using an escalation antibiogram informed by our Bayesian model is a useful tool to support empirical antibiotic prescribing for pyelonephritis. It provides an estimate of local resistance rates and a comparison of antibiotic options with a measure of the uncertainty in the data.