TY - JOUR
T1 - Threshold modeling for antibiotic stewardship in Oman
AU - Al-Hashimy, Zainab Said
AU - Al-Yaqoobi, Mubarak
AU - Jabari, Amal Al
AU - Kindi, Nawal Al
AU - Kazrooni, Ahmed Saleh Al
AU - Conway, Barbara R.
AU - Elhajji, Feras Darwish
AU - Bond, Stuart E.
AU - Lattyak, William J.
AU - Aldeyab, Mamoon A.
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/11/14
Y1 - 2024/11/14
N2 - Background: Antimicrobial stewardship supports rational antibiotic use. However, balancing access to antibiotic treatment while controlling resistance is challenging. This research used a threshold logistic modeling approach to identify targets for antibiotic usage associated with carbapenem-resistant Acinetobacter baumannii, carbapenem-resistant Klebsiella pneumonia, and extended-spectrum β-lactamases-producing Escherichia coli incidence in hospitals. Methods: This study utilizes an ecological population-level design. Monthly pathogen cases and antibiotic use were retrospectively determined for inpatients between January 2015 and December 2023. The hospital pharmacy and microbiology information systems were used to obtain this data. Thresholds were identified by applying nonlinear modeling and logistic regression. Results: Incidence rates of 0.199, 0.175, and 0.146 cases/100 occupied bed-days (OBD) for carbapenem-resistant A baumannii, carbapenem-resistant K pneumonia, and extended-spectrum β-lactamases-producing E coli, respectively, were determined as the cutoff values for high (critical) incidence rates. Thresholds for aminoglycosides (0.59 defined daily dose [DDD]/100 OBD), carbapenems (6.31 DDD/100 OBD), piperacillin-tazobactam (3.71 DDD/100 OBD), third-generation cephalosporins (3.71 DDD/100 OBD), and fluoroquinolones (1.91 DDD/100 OBD), were identified. Exceeding these thresholds would accelerate the gram-negative pathogens' incidence rate above the critical incidence levels. Conclusions: Threshold logistic models can help inform and implement effective antimicrobial stewardship interventions to manage resistance within hospital settings.
AB - Background: Antimicrobial stewardship supports rational antibiotic use. However, balancing access to antibiotic treatment while controlling resistance is challenging. This research used a threshold logistic modeling approach to identify targets for antibiotic usage associated with carbapenem-resistant Acinetobacter baumannii, carbapenem-resistant Klebsiella pneumonia, and extended-spectrum β-lactamases-producing Escherichia coli incidence in hospitals. Methods: This study utilizes an ecological population-level design. Monthly pathogen cases and antibiotic use were retrospectively determined for inpatients between January 2015 and December 2023. The hospital pharmacy and microbiology information systems were used to obtain this data. Thresholds were identified by applying nonlinear modeling and logistic regression. Results: Incidence rates of 0.199, 0.175, and 0.146 cases/100 occupied bed-days (OBD) for carbapenem-resistant A baumannii, carbapenem-resistant K pneumonia, and extended-spectrum β-lactamases-producing E coli, respectively, were determined as the cutoff values for high (critical) incidence rates. Thresholds for aminoglycosides (0.59 defined daily dose [DDD]/100 OBD), carbapenems (6.31 DDD/100 OBD), piperacillin-tazobactam (3.71 DDD/100 OBD), third-generation cephalosporins (3.71 DDD/100 OBD), and fluoroquinolones (1.91 DDD/100 OBD), were identified. Exceeding these thresholds would accelerate the gram-negative pathogens' incidence rate above the critical incidence levels. Conclusions: Threshold logistic models can help inform and implement effective antimicrobial stewardship interventions to manage resistance within hospital settings.
KW - Antibiotic prescribing
KW - Antibiotic resistance
KW - Antibiotic use
KW - Gram-negative bacteria
KW - Threshold logistic modeling
UR - http://www.scopus.com/inward/record.url?scp=85210771873&partnerID=8YFLogxK
U2 - 10.1016/j.ajic.2024.11.005
DO - 10.1016/j.ajic.2024.11.005
M3 - Article
C2 - 39549748
AN - SCOPUS:85210771873
JO - American Journal of Infection Control
JF - American Journal of Infection Control
SN - 0196-6553
ER -