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1.
Int J Antimicrob Agents ; 61(2): 106710, 2023 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-36642234

RESUMO

OBJECTIVES: Antibiotic spectrum index (ASI) is a recently developed antimicrobial stewardship (AMS) tool that aims to classify antibiotics based on activity against clinically relevant bacterial pathogens. METHODS: We utilised ASI in a 2-year retrospective study between April 2019 and April 2021 in four paediatric intensive care units of a specialist UK children's hospital to quantify antibiotic use based on age, presence of immunosuppression and AMS input. We then compared ASI to days of therapy (DOT) to determine the utility of this AMS metric. We have made changes to Gerber's original ASI list and score of antibiotics to align with prescribing and resistance patterns in the UK. RESULTS: Median ASI/antibiotic days increased with age: for infants under 1 year of age 4.1 (IQR 4.0-4.3), for children 1-5 years 4.4 (IQR 4.0-4.6) and for children over 5 years 4.5 (IQR 4.1-4.6). Immunocompromised patients received much broader-spectrum antibiotics than immunocompetent patients throughout the whole study period. Patients who had AMS input had a higher ASI compared with those who did not throughout the whole period, likely due to more complex patients being discussed on such rounds. CONCLUSIONS: Our results show a complex picture of changing antibiotic consumption and prescribing in a large specialist paediatric hospital in the UK with a long-standing AMS programme before and throughout the COVID-19 pandemic. ASI shows less variability than DOT and can potentially be used to identify patient groups and time periods where broader-spectrum antibiotics are used to help guide further AMS efforts.


Assuntos
Gestão de Antimicrobianos , COVID-19 , Criança , Lactente , Humanos , Pré-Escolar , Antibacterianos/uso terapêutico , Estudos Retrospectivos , Pandemias , Cuidados Críticos
2.
EClinicalMedicine ; 64: 102212, 2023 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-37745025

RESUMO

Background: Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infection. It remains unclear how MIS-C phenotypes vary across SARS-CoV-2 variants. We aimed to investigate clinical characteristics and outcomes of MIS-C across SARS-CoV-2 eras. Methods: We performed a multicentre observational retrospective study including seven paediatric hospitals in four countries (France, Spain, U.K., and U.S.). All consecutive confirmed patients with MIS-C hospitalised between February 1st, 2020, and May 31st, 2022, were included. Electronic Health Records (EHR) data were used to calculate pooled risk differences (RD) and effect sizes (ES) at site level, using Alpha as reference. Meta-analysis was used to pool data across sites. Findings: Of 598 patients with MIS-C (61% male, 39% female; mean age 9.7 years [SD 4.5]), 383 (64%) were admitted in the Alpha era, 111 (19%) in the Delta era, and 104 (17%) in the Omicron era. Compared with patients admitted in the Alpha era, those admitted in the Delta era were younger (ES -1.18 years [95% CI -2.05, -0.32]), had fewer respiratory symptoms (RD -0.15 [95% CI -0.33, -0.04]), less frequent non-cardiogenic shock or systemic inflammatory response syndrome (SIRS) (RD -0.35 [95% CI -0.64, -0.07]), lower lymphocyte count (ES -0.16 × 109/uL [95% CI -0.30, -0.01]), lower C-reactive protein (ES -28.5 mg/L [95% CI -46.3, -10.7]), and lower troponin (ES -0.14 ng/mL [95% CI -0.26, -0.03]). Patients admitted in the Omicron versus Alpha eras were younger (ES -1.6 years [95% CI -2.5, -0.8]), had less frequent SIRS (RD -0.18 [95% CI -0.30, -0.05]), lower lymphocyte count (ES -0.39 × 109/uL [95% CI -0.52, -0.25]), lower troponin (ES -0.16 ng/mL [95% CI -0.30, -0.01]) and less frequently received anticoagulation therapy (RD -0.19 [95% CI -0.37, -0.04]). Length of hospitalization was shorter in the Delta versus Alpha eras (-1.3 days [95% CI -2.3, -0.4]). Interpretation: Our study suggested that MIS-C clinical phenotypes varied across SARS-CoV-2 eras, with patients in Delta and Omicron eras being younger and less sick. EHR data can be effectively leveraged to identify rare complications of pandemic diseases and their variation over time. Funding: None.

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