Prospective role of cefiderocol in the management of carbapenem-resistant Acinetobacter baumannii infections: Review of the evidence

Carbapenem-resistant Acinetobacter baumannii (CRAB) has been classified by the World Health Organization as being in the critical category of pathogens requiring urgent new antibiotic treatment options. Cefiderocol, the first approved siderophore cephalosporin, was designed for the treatment of carbapenem-resistant Gram-negative pathogens, particularly the non-fermenting species A. baumannii and Pseudomonas aeruginosa. Cefiderocol is mostly stable against hydrolysis by serine β-lactamases and metallo-β-lactamases, which are leading causes of carbapenem resistance. This review collates the available evidence on the in vitro activity, pharmacokinetics/pharmacodynamics, and efficacy and safety of cefiderocol, and outlines its current role in the management of CRAB infections. In vitro surveillance data show susceptibility rates of \u3e90% for cefiderocol against CRAB isolates as well as in vitro synergism with a variety of antibiotics recommended in guidelines. Clinical efficacy of cefiderocol monotherapy against CRAB infections has been demonstrated in the descriptive, open-label CREDIBLE-CR and the non-inferiority, double-blind APEKS-NP randomised clinical trials as well as in real-world cases in patients with underlying health problems. To date, the frequency of on-therapy development of cefiderocol resistance in A. baumannii appears to be low, but monitoring is highly recommended. Within current treatment guidelines for moderate-to-severe CRAB infections, cefiderocol is recommended for infections in which other antibiotics failed and in combination with other active antibiotics. In vivo pre-clinical data support the combination of sulbactam or avibactam with cefiderocol to enhance efficacy and to suppress the emergence of cefiderocol resistance. The benefit of combination therapy in the clinical setting is yet to be determined in prospective studies

All-cause mortality rates in adults with carbapenem-resistant Gram-negative bacterial infections: a comprehensive review of pathogen-focused, prospective, randomized, interventional clinical studies

Carbapenem resistance; Gram-negative; CefiderocolResistència als carbapenems; Gram-negatius; CefiderocolResistencia a carbapenémicos; Gram-negativo; CefiderocolIntroduction Pathogen-focused, randomized, controlled trials (PF-RCT) are important in the fight against carbapenem-resistant (CR) Gram-negative infections. Some recently approved antibiotics and older generic antibiotics with activity against CR Gram-negative bacteria were investigated in PF-RCTs in a variety of infections. Areas covered We searched Pubmed, Cochrane database and international clinical trial databases for PF-RCTs for the period between 2005 and 2020 and compared the study designs, patient populations, infection types, pathogens, and Day-28 all-cause mortality (ACM). Expert opinion PF-RCTs are particularly challenging to quantitatively assess and compare due to the heterogeneity in infection types, pathogens, CR mechanism, inclusion/exclusion criteria, and endpoints. Data interpretation is further complicated by lack of formal statistical analysis plans and/or non-inferiority design, and limited power across most PF-RCTs. The studies with new antibiotics (i.e. plazomicin, meropenem/vaborbactam, cefiderocol) ranked lower regarding feasibility, with relatively small sample sizes (analyzed: 37–118) versus the comparative effectiveness studies of older generic drugs (analyzed: 94–406). ACM ranged between 11.8% and 40% for CR Enterobacterales, 17.7% and 57.4% for CR Acinetobacter spp., and 20.0% and 30.8% for CR Pseudomonas aeruginosa. The information gathered must be considered carefully alongside the study limitations and caution should be exercised when making direct comparisons across trials

Safety and Efficacy of Gatifloxacin Therapy for Children with Recurrent Acute Otitis Media (AOM) and/or AOM Treatment Failure

Background. Because of concerns about arthrotoxicity, fluoroquinolones are restricted for use in children. This study describes the safety and efficacy of gatifloxacin when used for treatment of children with recurrent acute otitis media (ROM) or acute otitis media (AOM) treatment failure (AOMTF). Methods. We performed an analysis of 867 children included in 4 clinical trials who had ROM and/or AOMTF and were treated with gatifloxacin (10 mg/kg once daily for 10 days). Results. Gatifloxacin had adverse event rates that were similar overall to those of a comparator antibiotic (amoxicillin-clavulanate), except for increased diarrhea in children !2 years old receiving amoxicillin-clavulanate. There was no evidence of arthrotoxicity, hepatotoxicity, alteration of glucose homeostasis, or central nervous system toxicity acutely or during 1 year follow-up in any child. Regarding efficacy, in 2 noncomparative trials, the gatifloxacin cure rate of AOM was 89% (95% confidence interval [CI], 83%-95%) at the test of cure (TOC) visit, 3-10 days after completion of therapy. In 2 comparative trials of gatifloxacin versus amoxicillin-clavulanate, the efficacy of gatifloxacin was 88% (95% CI, 82%-94%). Gatifloxacin led to better clinical outcomes than amoxicillinclavulanate for AOMTF (91% vs. 81%; ), for AOMTF and age !2 years old (89% vs. 69%; ), P p .029 P p .009 and for severe AOM in children !2 years old (90% vs. 75%; ). Among children with AOMTF previously P p .012 treated with amoxicillin-clavulanate or ceftriaxone injections, gatifloxacin cure rates were high (88% and 75%, respectively). Conclusions. Gatifloxacin appears to be safe for children, with no evidence of producing arthrotoxicity in 867 children exposed to the antibiotic when used as treatment for ROM and AOMTF

The role of networks to overcome large-scale challenges in tomography: The non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

A study of chemical reactions by flow injection techniques

The kinetic nature of flow injection (FI) experiments has led to the development of analytical methods that rely on the concentration gradients that are formed as a result of the hydrodynamics of the flowing stream. The concentration-time profile of the flow injection peak contains a wealth of chemical information, most of which are ignored in the typical FI experiment based on peak height. The objective of this work was to study a number of novel ways in which concentration-time data obtained from a variety of FI experiments can be used for analytical determinations and for the determination of fundamental reaction parameters. Time intervals were used as quantitative analytical parameters for slow and fast reactions. The Belousov-Zhabotinskii oscillating chemical reaction was generated in a flow injection system and monitored under conditions of stopped flow. The injection of an analyte into the slowly reacting system altered the behavior of the reaction. Times between events on the absorbance-time profile were used in a new kinetic method of analysis. The time interval between doublet peaks was the analytical parameter used in a study of FI doublet peaks. Mixing devices used in the experiment were compared and various aspects of the theory behind flow injection peak-width methods were discussed. Results from FI doublet peak determinations were presented and the overall precision of the method was evaluated. Formation quotients and reaction rate constants were calculated from sets of data points taken from the concentration-time profile of the FI peak. A flow injection system incorporating a well-stirred tank was used to create the concentration gradients from which the data were obtained. Two iterative methods were used to calculate formation quotients from absorbance-time data. The well-stirred tank model was modified for the situation of removal of sample by reaction. Novel ways to determine rate constants from absorbance-time data were based on the derived equations