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Threshold modeling for antibiotic stewardship in Oman - 17/03/25

Doi : 10.1016/j.ajic.2024.11.005 
Zainab Said Al-Hashimy, MSc a, b, Mubarak Al-Yaqoobi, FRCPath, MD c, Amal Al Jabari, FRCPath, MD c, Nawal Al Kindi, FRCPath, FRCPI, MD c, d, Ahmed Saleh Al Kazrooni, MD c, d, Barbara R. Conway, PhD b, e, Feras Darwish Elhajji, PhD f, Stuart E. Bond, PhD g, William J. Lattyak, BSc h, Mamoon A. Aldeyab, PhD b, g, ⁎
a Department of Clinical Pharmacy, Directorate of Pharmaceutical Care and Medical Stores, Khawlah Hospital, Muscat, Oman 
b Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield, UK 
c Department of Microbiology, Directorate of Laboratories, Khawlah Hospital, Muscat, Oman 
d Directorate of Infection Prevention and Occupational Safety, Khawlah Hospital, Muscat, Oman 
e Institute of Skin Integrity and Infection Prevention, University of Huddersfield, Huddersfield, UK 
f Faculty of Pharmacy, Applied Science Private University, Amman, Jordan 
g Pharmacy Department, Mid Yorkshire Hospitals NHS Trust, Wakefield, UK 
h Statistical Consulting Department, Scientific Computing Associates Corp, River Forest, IL, USA 

⁎Address correspondence to Mamoon A. Aldeyab, Department of Pharmacy, School of Applied Sciences, University of Huddersfield, Huddersfield, UK.Department of Pharmacy, School of Applied Sciences, University of HuddersfieldHuddersfieldUK

Resumen

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.

El texto completo de este artículo está disponible en PDF.

Highlights

•
Balancing access to antimicrobials while controlling resistance is challenging.
•
Relationships between antibiotic use and resistance can be nonlinear.
•
Threshold logistic models help define critical levels of pathogen incidence.
•
Threshold logistic models provide targets for antibiotic consumption.
•
Threshold logistic approach can inform antimicrobial stewardship interventions.

El texto completo de este artículo está disponible en PDF.

Key Words : Antibiotic resistance, Threshold logistic modeling, Antibiotic use, Gram-negative bacteria, Antibiotic prescribing


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 Conflicts of interest: None to report.


© 2024  The Authors. Publicado por Elsevier Masson SAS. Todos los derechos reservados.
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Vol 53 - N° 4

P. 514-519 - avril 2025 Regresar al número
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