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1.
Clin Microbiol Rev ; 34(1)2020 12 16.
Article in English | MEDLINE | ID: mdl-33177185

ABSTRACT

The limited armamentarium against drug-resistant Gram-negative bacilli has led to the development of several novel ß-lactam-ß-lactamase inhibitor combinations (BLBLIs). In this review, we summarize their spectrum of in vitro activities, mechanisms of resistance, and pharmacokinetic-pharmacodynamic (PK-PD) characteristics. A summary of available clinical data is provided per drug. Four approved BLBLIs are discussed in detail. All are options for treating multidrug-resistant (MDR) Enterobacterales and Pseudomonas aeruginosa Ceftazidime-avibactam is a potential drug for treating Enterobacterales producing extended-spectrum ß-lactamase (ESBL), Klebsiella pneumoniae carbapenemase (KPC), AmpC, and some class D ß-lactamases (OXA-48) in addition to carbapenem-resistant Pseudomonas aeruginosa Ceftolozane-tazobactam is a treatment option mainly for carbapenem-resistant P. aeruginosa (non-carbapenemase producing), with some activity against ESBL-producing Enterobacterales Meropenem-vaborbactam has emerged as treatment option for Enterobacterales producing ESBL, KPC, or AmpC, with similar activity as meropenem against P. aeruginosa Imipenem-relebactam has documented activity against Enterobacterales producing ESBL, KPC, and AmpC, with the combination having some additional activity against P. aeruginosa relative to imipenem. None of these drugs present in vitro activity against Enterobacterales or P. aeruginosa producing metallo-ß-lactamase (MBL) or against carbapenemase-producing Acinetobacter baumannii Clinical data regarding the use of these drugs to treat MDR bacteria are limited and rely mostly on nonrandomized studies. An overview on eight BLBLIs in development is also provided. These drugs provide various levels of in vitro coverage of carbapenem-resistant Enterobacterales, with several drugs presenting in vitro activity against MBLs (cefepime-zidebactam, aztreonam-avibactam, meropenem-nacubactam, and cefepime-taniborbactam). Among these drugs, some also present in vitro activity against carbapenem-resistant P. aeruginosa (cefepime-zidebactam and cefepime-taniborbactam) and A. baumannii (cefepime-zidebactam and sulbactam-durlobactam).


Subject(s)
Gram-Negative Bacteria/drug effects , beta-Lactamase Inhibitors/pharmacology , beta-Lactams/pharmacology , Drug Combinations , Drug Resistance, Multiple, Bacterial/drug effects , Microbial Sensitivity Tests , beta-Lactamase Inhibitors/pharmacokinetics , beta-Lactams/pharmacokinetics
3.
Simul Healthc ; 16(6): 386-391, 2021 Dec 01.
Article in English | MEDLINE | ID: mdl-32910105

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19)] outbreak has been declared a global pandemic by the World Health Organization. The COVID-19 pandemic has highlighted problems of sustainable infection prevention and control measures worldwide, particularly the emerging issues with an insufficient supply of personal protective equipment. The aim of this study was to provide an action plan for mitigation of occupational hazards and nosocomial spread of SARS-CoV-2 through a failure mode analysis based on observations during in situ simulations. METHODS: A multicenter, cross-sectional, observational, simulation-based study was performed in Latvia from March 2 to 26, 2020. This study was conducted at 7 hospitals affiliated with Riga Stradins University. The presentation of a COVID-19 patient was simulated with an in situ simulations, followed by a structured debrief. Healthcare Failure Modes and Effects Analysis is a tool for conducting a systematic, proactive analysis of a process in which harm may occur. We used Healthcare Failure Modes and Effects Analysis to analyze performance gaps and systemic issues. RESULTS: A total of 67 healthcare workers from 7 hospitals participated in the study (range = 4-17). A total of 32 observed failure modes were rated using a risk matrix. Twenty-seven failure modes (84.4%) were classified as either medium or high risk or were single-point weaknesses, hence evaluated for action type and action; 11 (40.7%) were related to organizational, 11 (40.7%) to individual, and 5 (18.5%) to environmental factors. CONCLUSIONS: Simulation-based failure mode analysis helped us identify the risks related to the preparedness of the healthcare workers and emergency departments for the COVID-19 pandemic in Latvia. We believe that this approach can be implemented to assess and maintain readiness for the outbreaks of emerging infectious diseases in the future.


Subject(s)
COVID-19 , Cross-Sectional Studies , Emergency Service, Hospital , Health Personnel , Humans , Infection Control , Pandemics , SARS-CoV-2
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