Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data.
Quentin J LeclercAlastair ClementsHelen DunnJames HatcherJodi A LindsayLouis GrandjeanGwenan Mary KnightPublished in: medRxiv : the preprint server for health sciences (2023)
Antimicrobial resistance (AMR) to all antibiotic classes has been found in the pathogen Staphylococcus aureus . The reported prevalence of these resistances vary, driven by within-host AMR evolution at the patient level, and between-host transmission at the hospital level. Without dense longitudinal sampling, pragmatic analysis of AMR dynamics at multiple levels using routine surveillance data is essential to inform control measures. We explored S. aureus AMR diversity in 70,000 isolates from a UK paediatric hospital between 2000-2020, using electronic datasets containing multiple routinely collected isolates per patient with phenotypic antibiograms, hospitalisation information, and antibiotic consumption. At the hospital-level, the proportion of isolates that were meticillin-resistant (MRSA) increased between 2014-2020 from 25 to 50%, before sharply decreasing to 30%, likely due to a change in inpatient demographics. Temporal trends in the proportion of isolates resistant to different antibiotics were often correlated in MRSA, but independent in meticillin-susceptible S. aureus . Ciprofloxacin resistance in MRSA decreased from 70% to 40% of tested isolates between 2007-2020, likely linked to a national policy to reduce fluoroquinolone usage in 2007. At the patient level, we identified frequent AMR diversity, with 4% of patients ever positive for S. aureus simultaneously carrying, at some point, multiple isolates with different resistances. We detected changes over time in AMR diversity in 3% of patients ever positive for S. aureus . These changes equally represented gain and loss of resistance. Within this routinely collected dataset, we found that 65% of changes in resistance within a patient’s S. aureus population could not be explained by antibiotic exposure or between-patient transmission of bacteria, suggesting that within-host evolution via frequent gain and loss of AMR genes may be responsible for these changing AMR profiles. Our study highlights the value of exploring existing routine surveillance data to determine underlying mechanisms of AMR. These insights may substantially improve our understanding of the importance of antibiotic exposure variation, and the success of single S. aureus clones.
Keyphrases
- staphylococcus aureus
- antimicrobial resistance
- case report
- healthcare
- methicillin resistant staphylococcus aureus
- end stage renal disease
- public health
- ejection fraction
- newly diagnosed
- chronic kidney disease
- biofilm formation
- acute care
- electronic health record
- genetic diversity
- pseudomonas aeruginosa
- prognostic factors
- intensive care unit
- peritoneal dialysis
- big data
- adverse drug
- escherichia coli
- gene expression
- cystic fibrosis
- transcription factor
- cross sectional
- machine learning
- risk factors
- social media
- deep learning
- genome wide
- patient reported outcomes