Background: Meeting antibiotic stewardship goals in the neonatal intensive care unit (NICU) is challenging because of the unique nature of newborns and the lack of specificity of clinical signs of sepsis. Antibiotics are commonly continued for 48 hours pending culture results and clinical status. The goal of this study was to examine if the implementation of a 48-hour automatic stop (autostop) order during NICU admissions would decrease antibiotic use at UnityPoint Health-Meriter.
Methods: An observational double-cohort study was performed in a level 3 NICU. Antibiotic use was evaluated before and after the autostop initiative. The admission order set included 48 hours of ampicillin and gentamicin coverage.
Results: After the autostop initiation, total doses given per patient decreased by 35% and doses per patient-day decreased by 25% (P < .0001). The greatest effect was a 66% decrease in the use of vancomycin, an antibiotic not included in the admission order set. Providers proactively continued antibiotics for infants in whom they had high suspicion for sepsis and in those with positive blood or cerebral spinal fluid culture results.
Conclusions: An admission-order autostop was highly effective at decreasing antibiotic usage with no doses intended for a pathogen missed. Fewer doses of certain antibiotics outside of the admission order set were administered, particularly vancomycin, which results in our speculation that provider awareness of the antibiotic stewardship initiative might have altered prescribing practices.
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http://dx.doi.org/10.1093/jpids/piy043 | DOI Listing |
BMC Infect Dis
December 2024
Clinical Pharmacy Department, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
Background: The World Health Organization (WHO) has identified carbapenem-resistant Pseudomonas aeruginosa (CRPA) as one of the three critical priority pathogens. There is scarce literature evaluating the treatment outcomes in patients with CRPA infections treated with traditional non-carbapenem β-lactam (NCBL) agents. Thus, this study aims to assess the effectiveness of traditional NCBL compared to novel β-lactam agents (NVL) for treating non-carbapenem β-lactam -susceptible CRPA.
View Article and Find Full Text PDFEur J Med Res
December 2024
Department of Medical Laboratory Science, College of Medicine and Health Sciences, Debre Markos University, 269, Debre Markos, Ethiopia.
Background: Antibiotic resistance (AMR) remains a global public health threat with a high burden in sub-Saharan countries. The overuse of antimicrobials in the clinical setting is the main factor for the spread of antibiotic resistance. Diagnostic uncertainty in differentiating between bacterial and viral infections is the major contributor to antimicrobial overuse.
View Article and Find Full Text PDFBMC Med
December 2024
Foodborne and Waterborne Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Background: Helicobacter pylori infection causes gastritis, peptic ulcers, and gastric cancer. The infection is typically acquired in childhood and persists throughout life. The major impediment to successful therapy is antibiotic resistance.
View Article and Find Full Text PDFAPMIS
January 2025
Laboratory Sciences Research Center, Golestan University of Medical Sciences, Gorgan, Iran.
Colistin is a last-resort treatment for multidrug-resistant Gram-negative bacterial infections, particularly in critically ill patients. Nevertheless, it remains a major threat to public health. We assessed the proportion of colistin-resistant Gram-negative isolates from intensive care unit (ICU) infections in different years, areas, pathogens, and antimicrobial susceptibility tests (AST).
View Article and Find Full Text PDFBJU Int
December 2024
Department of Urology, Glickman Urological Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
Objective: To develop, externally validate, and test a series of computer algorithms to accurately predict antibiotic susceptibility test (AST) results at the time of clinical diagnosis, up to 3 days before standard urine culture results become available, with the goal of improving antibiotic stewardship and patient outcomes.
Patients And Methods: Machine learning algorithms were developed and trained to predict susceptibility or resistance using over 4.7 million discrete AST classifications from urine cultures in a cohort of adult patients from outpatient and inpatient settings from 2012 to 2022.
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