Τίτλος:
Forecasting models of infections due to carbapenem-resistant Gram-negative bacteria in an intensive care unit in an endemic area
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
Objectives: The aim of this study was to forecast the monthly incidence rates of infections [infections/1000 bed-days (IBD)] due to carbapenem-resistant Klebsiella pneumoniae (CRKP), carbapenem-resistant Pseudomonas aeruginosa (CRPA), carbapenem-resistant Acinetobacter baumannii (CRAB) and total carbapenem-resistant Gram-negative bacteria (CRGNB) in an endemic intensive care unit (ICU) during the subsequent year (December 2016–December 2017) following the observational period. Methods: A 52-month observational period (August 2012–November 2016) was used. Two forecasting models, including a simple seasonal model for CRGNB, CRKP and CRPA and Winters’ additive model for CRAB infections, were applied. Results: The models predicted the highest infection rates for CRKP, CRAB and CRGNB in January and September 2017 (23.8/23.4, 24.6/28.5 and 46.8/46.7 IBD, respectively) and for CRPA in February and March 2017 (8.3 and 7.9, respectively). The highest observed rates for CRKP, CRAB and CRGNB were indeed in January and September 2017 (25.6/19.0, 34.2/23.8 and 59.8/42.8 IBD, respectively); and for CRPA in February and March of the same year (15.2 and 12.7, respectively). The increased rates may be associated with personnel's annual work programme and behavioural factors. Conclusion: Forecasting models in endemic ICUs may assist in implementation strategies for infection control measures. © 2019 International Society for Antimicrobial Chemotherapy
Συγγραφείς:
Karampatakis, T.
Tsergouli, K.
Iosifidis, E.
Antachopoulos, C.
Mouloudi, E.
Karyoti, A.
Tsakris, A.
Roilides, E.
Περιοδικό:
Journal of Global Antimicrobial Resistance
Εκδότης:
Elsevier Ireland Ltd
Λέξεις-κλειδιά:
Acinetobacter infection; adolescent; adult; aged; Article; carbapenem resistant Acinetobacter baumannii; carbapenem resistant Klebsiella pneumoniae; carbapenem resistant Pseudomonas aeruginosa; controlled study; endemic disease; female; forecasting; human; incidence; infection rate; intensive care unit; Klebsiella infection; major clinical study; male; observational study; priority journal; Pseudomonas infection; retrospective study; validation process; Acinetobacter baumannii; antibiotic resistance; Bayes theorem; classification; drug effect; Gram negative infection; Klebsiella pneumoniae; length of stay; microbial sensitivity test; middle aged; Pseudomonas aeruginosa; season; theoretical model; very elderly; young adult, carbapenem derivative, Acinetobacter baumannii; Adolescent; Adult; Aged; Aged, 80 and over; Bayes Theorem; Carbapenems; Drug Resistance, Bacterial; Female; Gram-Negative Bacterial Infections; Humans; Intensive Care Units; Klebsiella pneumoniae; Length of Stay; Male; Microbial Sensitivity Tests; Middle Aged; Models, Theoretical; Pseudomonas aeruginosa; Retrospective Studies; Seasons; Young Adult
DOI:
10.1016/j.jgar.2019.06.019
