E Fortin1, P S Fontela2, A R Manges3, R W Platt4, D L Buckeridge4, C Quach5. 1. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec and Montréal, Canada. 2. Department of Pediatrics, The Montreal Children's Hospital, McGill University, Montréal, Canada. 3. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada School of Population and Public Health, University of British Columbia, Vancouver, Canada. 4. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada. 5. Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, Canada Direction des risques biologiques et de la santé au travail, Institut national de santé publique du Québec, Québec and Montréal, Canada Department of Pediatrics, The Montreal Children's Hospital, McGill University, Montréal, Canada caroline.quach@mcgill.ca.
Abstract
OBJECTIVES: The optimal measure to use for surveillance of antimicrobial usage in hospital settings, especially when including paediatric populations, is unknown. This systematic review of literature aims to list, define and compare existing measures of antimicrobial use that have been applied in settings that included paediatric inpatients, to complement surveillance of resistance. METHODS: We identified cohort studies and repeated point-prevalence studies presenting data on antimicrobial use in populations of inpatients or validations/comparisons of antimicrobial measures through a systematic search of literature using MEDLINE, EMBASE, CINAHL and LILACS (1975-2011) and citation tracking. Study populations needed to include hospitalized paediatric patients. Two reviewers independently extracted data on study characteristics and results. RESULTS: Overall, 3878 records were screened and 79 studies met selection criteria. Twenty-six distinct measures were found, the most frequently used being defined daily doses (DDD)/patient-days and exposed patients/patients. Only two studies compared different measures quantitatively, showing (i) a positive correlation between proportion of exposed patients and antimicrobial-days/patient-days and (ii) a strong correlation between doses/patient-days and agent-days/patient-days (r = 0.98), with doses/patient-days correlating more with resistance rates (r = 0.80 versus 0.55). CONCLUSIONS: The measure of antimicrobial use that best predicts antimicrobial resistance prevalence and rates, for surveillance purposes, has still not been identified; additional evidence on this topic is a necessity.
OBJECTIVES: The optimal measure to use for surveillance of antimicrobial usage in hospital settings, especially when including paediatric populations, is unknown. This systematic review of literature aims to list, define and compare existing measures of antimicrobial use that have been applied in settings that included paediatric inpatients, to complement surveillance of resistance. METHODS: We identified cohort studies and repeated point-prevalence studies presenting data on antimicrobial use in populations of inpatients or validations/comparisons of antimicrobial measures through a systematic search of literature using MEDLINE, EMBASE, CINAHL and LILACS (1975-2011) and citation tracking. Study populations needed to include hospitalized paediatric patients. Two reviewers independently extracted data on study characteristics and results. RESULTS: Overall, 3878 records were screened and 79 studies met selection criteria. Twenty-six distinct measures were found, the most frequently used being defined daily doses (DDD)/patient-days and exposed patients/patients. Only two studies compared different measures quantitatively, showing (i) a positive correlation between proportion of exposed patients and antimicrobial-days/patient-days and (ii) a strong correlation between doses/patient-days and agent-days/patient-days (r = 0.98), with doses/patient-days correlating more with resistance rates (r = 0.80 versus 0.55). CONCLUSIONS: The measure of antimicrobial use that best predicts antimicrobial resistance prevalence and rates, for surveillance purposes, has still not been identified; additional evidence on this topic is a necessity.
Authors: Myriam Gharbi; Katja Doerholt; Stefania Vergnano; Julia Anna Bielicki; Stéphane Paulus; Esse Menson; Andrew Riordan; Hermione Lyall; Sanjay Valabh Patel; Jolanta Bernatoniene; Ann Versporten; Maggie Heginbothom; Herman Goossens; Mike Sharland Journal: BMJ Open Date: 2016-11-03 Impact factor: 2.692
Authors: L Calle-Miguel; G Modroño Riaño; A I Iglesias Carbajo; M A Alonso Álvarez; C Vicente Martínez; G Solís Sánchez Journal: Rev Esp Quimioter Date: 2021-01-26 Impact factor: 1.553