113 Data extraction for the digital research environment

Key, Daniel; Booth, John; Shah, Mansoor Ul Hassan; Briggs, Lydia; Spiridou, Anastassia; Sebire, Neil J; Bryant, William A

doi:10.1136/archdischild-2021-gosh.113

Cited by 2 publications

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“…This was made possible through the framework developed by GOSH to store and make this data easily accessible for research purposes. Other healthcare institutions should develop systems like the GOSH DRIVE to record and analyse routinely collected data [60], as this may benefit these institutions directly, and allow new analyses to further improve our understanding of AMR. Improved sharing of information on data collection to accompany the public release of these routinely collected datasets will be beneficial to the scientific community more broadly.…”

Section: Discussionmentioning

confidence: 99%

Quantifying patient- and hospital-level antimicrobial resistance dynamics inStaphylococcus aureusfrom routinely collected data

Leclerc

Clements

Dunn

et al. 2023

Preprint

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Antimicrobial resistance (AMR) to all antibiotic classes has been found in the pathogenStaphylococcus 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 exploredS. aureusAMR 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-susceptibleS. 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 forS. aureussimultaneously carrying, at some point, multiple isolates with different resistances. We detected changes over time in AMR diversity in 3% of patients ever positive forS. 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'sS. aureuspopulation 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 singleS. aureusclones.

show abstract

Section: Discussionmentioning

confidence: 99%

Quantifying patient- and hospital-level antimicrobial resistance dynamics inStaphylococcus aureusfrom routinely collected data

Leclerc

Clements

Dunn

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…This was made possible through the framework developed by GOSH to store and make these data easily accessible for research purposes. Other healthcare institutions should develop systems like the GOSH DRIVE to record and analyse routinely collected data [62], as this may benefit these institutions directly, and allow new analyses to further improve our understanding of AMR. Improved sharing of information on data collection to accompany the public release of these routinely collected datasets will be beneficial to the scientific community more broadly.…”

Section: Discussionmentioning

confidence: 99%

Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data

Leclerc

Clements

Dunn

et al. 2023

Journal of Medical Microbiology

View full text Add to dashboard Cite

Introduction. Antimicrobial resistance (AMR) to all antibiotic classes has been found in the pathogen Staphylococcus aureus . The reported prevalence of these resistances varies, 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. Gap Statement. The value and limitations of routinely collected hospital data to gain insight into AMR dynamics at the hospital and individual levels simultaneously are unclear. Methodology. We explored S. aureus AMR diversity in 70 000 isolates from a UK paediatric hospital between 2000–2021, using electronic datasets containing multiple routinely collected isolates per patient with phenotypic antibiograms and information on hospitalization and antibiotic consumption. Results. At the hospital level, the proportion of isolates that were meticillin-resistant (MRSA) increased between 2014–2020 from 25–50 %, 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 70–40 % 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. Conclusion. 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.

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113 Data extraction for the digital research environment

Cited by 2 publications

References 0 publications

Quantifying patient- and hospital-level antimicrobial resistance dynamics inStaphylococcus aureusfrom routinely collected data

Quantifying patient- and hospital-level antimicrobial resistance dynamics inStaphylococcus aureusfrom routinely collected data

Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data

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