Impact of adequate empirical combination therapy on mortality in septic shock due to Pseudomonas aeruginosa bloodstream infections: a multicentre retrospective cohort study.

OBJECTIVES: To determine the association of adequate empirical combination therapy (AECT) with 30-day all-cause mortality in patients with septic shock due to Pseudomonas aeruginosa bloodstream infections (BSI). METHODS: This multicentre, retrospective cohort study analysed data from 14 public hospitals in Italy, including all consecutive adult patients admitted during 2021-2022 with septic shock due to P. aeruginosa BSI. We compared the outcomes of patients receiving AECT to those on adequate empirical monotherapy (AEMT) using Cox regression analyses. RESULTS: Of the 98 patients who received adequate empirical antibiotic treatment for septic shock due to P. aeruginosa BSI, 24 underwent AECT and 74 were given AEMT. AECT was associated with a lower 30-day all-cause mortality (25%, six out of 24) compared to AEMT (56.8%, 42 out of 74; P = 0.007). Multivariate Cox regression analysis indicated AECT as the only factor significantly associated with improved survival (aHR 0.30; 95% CI 0.12-0.71; P = 0.006). By contrast, the use of monotherapy or combination therapy in the definitive regimen did not influence mortality (aHR 0.73; 95% CI 0.25-2.14; P = 0.568). CONCLUSIONS: AECT may be associated with reduced mortality compared to monotherapy in septic shock patients due to P. aeruginosa BSI. However, the administration of definitive adequate monotherapy or combination therapy yields similar outcomes, suggesting that once susceptibility is documented, switching to a single active in vitro drug is safe and feasible. Further studies are recommended to validate these findings.

The role of sulbactam-durlobactam in treating carbapenem-resistant Acinetobacter infections.

PURPOSE OF REVIEW: Infections caused by multidrug-resistant Acinetobacter baumannii present a significant global health challenge. Available treatment options are limited and frequently constrained by unfavourable safety and pharmacokinetic profiles. Sulbactam-durlobactam is a novel ß-lactamase inhibitors combination specifically developed to target A. baumannii, including carbapenem-resistant strains. The purpose of this review is to assess the current evidence supporting the role of sulbactam-durlobactam in the management of A. baumannii infections. RECENT FINDINGS: We summarize the available evidence regarding the pharmacokinetic and pharmacodynamic profiles of sulbactam-durlobactam from key in-vitro and in-vivo studies. Additionally, efficacy results from the Phase III randomized controlled trial and real-world data on sulbactam-durlobactam's use against severe A. baumannii infections are also discussed. SUMMARY: Sulbactam-durlobactam is a promising addition to the treatment options for carbapenem-resistant A. baumannii infections. Ongoing research and vigilance are essential to monitor the development of in-vivo resistance, assess effectiveness across diverse patient populations, and explore potential synergistic combinations with other antimicrobials. Careful stewardship and comprehensive clinician education will be crucial to optimizing the clinical use of sulbactam-durlobactam.

Novel agents in development for the treatment of resistant Gram-negative infections.

INTRODUCTION: Several novel agents are in advanced stages of clinical development, potentially expanding our treatment options against third- and fourth-generation cephalosporin-resistant and carbapenem-resistant Gram-negative bacteria (GNB), including those pathogens for which the current number of effective treatments is limited. AREAS COVERED: This review focuses on agents that have completed or ongoing phase-3 studies. A PubMed search was conducted up to 31 May 2024. EXPERT OPINION: Novel agents in late-stage clinical development belong to the ß-lactam or ß-lactam/ß-lactamase inhibitor combinations class and display variable antimicrobial activity depending on the specific ß-lactamases expressed by GNB, particularly carbapenemases. While many of these novel agents demonstrate in vitro activity against carbapenem-resistant GNB, their efficacy has mainly been evaluated in phase-3 randomized controlled trials (RCT) for infections caused by carbapenem-susceptible GNB. Although evidence from real-world observational studies is generally less robust than that from RCT, it could be crucial for updating clinical guidelines on treating carbapenem-resistant GNB with these new agents in the absence of dedicated RCT.

New antibiotics in clinical pipeline for treating infections caused by metallo-ß-lactamases producing Gram-negative bacteria.

PURPOSE OF REVIEW: To discuss novel antibiotics under clinical development, focusing on agents showing in-vitro activity against metallo-ß-lactamases (MBL)-producing carbapenem-resistant Gram-negative bacteria (CR-GNB). RECENT FINDINGS: Currently, only a few approved agents show activity, alone or in synergistic combinations, against MBL-producing CR-GNB. If approved by regulatory agencies in case of favorable results from ongoing (and, for some agents, already completed) phase-3 studies, some novel ß-lactam/ß-lactamase inhibitor (BL/BLI) combinations could become available in the next few years as additional important options for treating MBL-producing CR-GNB infections. Additional interesting agents that belong both to BL/BLI combinations and to antibiotic classes other than BL and BL/BLI combinations have also shown activity against MBL-producing CR-GNB, with most of them being in early phases of clinical development. SUMMARY: Improving the use of these novel agents through virtuous antimicrobial stewardship frameworks able to guarantee both the efficacious treatment of infections requiring their use and the avoidance of their use whenever not necessary remains a challenge of utmost importance that should not be overlooked.

COVID-19 throughout pandemic waves and virus variants: a real-life experience in an Italian hospital.

New therapies and vaccines changed the management of COVID-19. The aim of this retrospective study was to describe characteristics, in-hospital mortality and its predictors in patients with moderate/severe COVID-19, considering the 4 different pandemic waves and viral variants' prevalence from February 2020 to January 2022. Among 1135 patients included, 873 (77%) had at least one comorbidity, 177 (16%) were immunocompromised. From waves 1 to 4, patients with severe respiratory failure and ICU admission decreased over time (p < 0.001), like the length of in-hospital stay (p < 0.001). Despite a reduction of in-hospital mortality from 19% to 11%, increased risk of death was related to older age and immunocompromising conditions, especially during the 4th wave (HR = 5.07 and HR = 10.86, p < 0.001 respectively) while remdesivir treatment in the 3rd wave (HR = 0.41, p = 0.010) and positive serology (aHR = 0.66, p = 0.027) were protective for survival. These data support the need for tailoring vaccine campaign for future COVID-19 waves.

Artificial intelligence and prescription of antibiotic therapy: present and future.

INTRODUCTION: In the past few years, the use of artificial intelligence in healthcare has grown exponentially. Prescription of antibiotics is not exempt from its rapid diffusion, and various machine learning (ML) techniques, from logistic regression to deep neural networks and large language models, have been explored in the literature to support decisions regarding antibiotic prescription. AREAS COVERED: In this narrative review, we discuss promises and challenges of the application of ML-based clinical decision support systems (ML-CDSSs) for antibiotic prescription. A search was conducted in PubMed up to April 2024. EXPERT OPINION: Prescribing antibiotics is a complex process involving various dynamic phases. In each of these phases, the support of ML-CDSSs has shown the potential, and also the actual ability in some studies, to favorably impacting relevant clinical outcomes. Nonetheless, before widely exploiting this massive potential, there are still crucial challenges ahead that are being intensively investigated, pertaining to the transparency of training data, the definition of the sufficient degree of prediction explanations when predictions are obtained through black box models, and the legal and ethical framework for decision responsibility whenever an antibiotic prescription is supported by ML-CDSSs.

Prediction of candidemia with machine learning techniques: state of the art.

In this narrative review, we discuss studies assessing the use of machine learning (ML) models for the early diagnosis of candidemia, focusing on employed models and the related implications. There are currently few studies evaluating ML techniques for the early diagnosis of candidemia as a prediction task based on clinical and laboratory features. The use of ML tools holds promise to provide highly accurate and real-time support to clinicians for relevant therapeutic decisions at the bedside of patients with suspected candidemia. However, further research is needed in terms of sample size, data quality, recognition of biases and interpretation of model outputs by clinicians to better understand if and how these techniques could be safely adopted in daily clinical practice.

Candida is a type of fungus that can cause fatal infections. To confirm the presence of the infection, doctors may search for the fungus in the blood. Here, we discuss if computer systems can help to identify infection more easily and more rapidly.

Attributable mortality of candidemia - Results from the ECMM Candida III multinational European Observational Cohort Study.

INTRODUCTION: Despite antifungal advancements, candidaemia still has a high mortality rate of up to 40%. The ECMM Candida III study in Europe investigated the changing epidemiology and outcomes of candidaemia for better understanding and management of these infections. METHODS: In this observational cohort study, participating hospitals enrolled the first ten consecutive adults with blood culture-proven candidemia. Collected data included patient demographics, risk factors, hospital stay duration (follow-up of 90 days), diagnostic procedures, causative Candida spp., management details, and outcome. Controls were included in a 1:1 fashion from the same hospitals. The matching process ensured similarity in age (10-year range), primary underlying disease, hospitalization in intensive care versus non-ICU ward, and major surgery within 2 weeks before candidemia between cases and controls. Overall and attributable mortality were described, and a survival probability for cases and controls was performed. RESULTS: One hundred seventy-one pairs consisting of patients with candidemia and matched controls from 28 institutions were included. In those with candidemia, overall mortality was 40.4%. Attributable mortality was 18.1% overall but differed between causative Candida species (7.7% for Candida albicans, 23.7% for Candida glabrata/Nakaseomyces glabratus, 7.7% for Candida parapsilosis and 63.6% for Candida tropicalis). Regarding risk factors, the presence of a central venous catheter, total parenteral nutrition and acute or chronic renal disease were significantly more common in cases versus controls. Duration of hospitalization, and especially that of ICU stay, was significantly longer in candidemia cases (20 (IQR 10-33) vs 15 days (IQR 7-28); p = 0.004). CONCLUSIONS: Although overall and attributable mortality in this subgroup analysis of matched case/control pairs remains high, the attributable mortality appears to have decreased in comparison to historical cohorts. This decrease may be driven by improved prognosis of Candida albicans and Candida parapsilosis candidemia; whereas candidemia due to other Candida spp. exhibits a much higher attributable mortality.

Use of Cefiderocol in Adult Patients: Descriptive Analysis from a Prospective, Multicenter, Cohort Study.

INTRODUCTION: Cefiderocol is a siderophore cephalosporin showing activity against various carbapenem-resistant Gram-negative bacteria (CR-GNB). No data currently exist about real-world use of cefiderocol in terms of types of therapy (e.g., empirical or targeted, monotherapy or combined regimens), indications, and patient characteristics. METHODS: In this multicenter, prospective study, we aimed at describing the use of cefiderocol in terms of types of therapy, indications, and patient characteristics. RESULTS: Cefiderocol was administered as empirical and targeted therapy in 27.5% (55/200) and 72.5% (145/200) of cases, respectively. Overall, it was administered as monotherapy in 101/200 cases (50.5%) and as part of a combined regimen for CR-GNB infections in the remaining 99/200 cases (49.5%). In multivariable analysis, previous isolation of carbapenem-resistant Acinetobacter baumannii odds ratio (OR) 2.56, with 95% confidence interval (95% CI) 1.01-6.46, p = 0.047] and previous hematopoietic stem cell transplantation (OR 8.73, 95% CI 1.05-72.54, p = 0.045) were associated with administration of cefiderocol as part of a combined regimen, whereas chronic kidney disease was associated with cefiderocol monotherapy (OR 0.38 for combined regimen, 95% CI 0.16-0.91, p = 0.029). Cumulative 30-day mortality was 19.8%, 45.0%, 20.7%, and 22.7% in patients receiving targeted cefiderocol for infections by Enterobacterales, A. baumannii, Pseudomonas aeruginosa, and any metallo-ß-lactamase producers, respectively. CONCLUSIONS: Cefiderocol is mainly used for targeted treatment, although empirical therapies account for more than 25% of prescriptions, thus requiring dedicated standardization and guidance. The almost equal distribution of cefiderocol monotherapy and cefiderocol-based combination therapies underlines the need for further study to ascertain possible differences in efficacy between the two approaches.

Optimizing Antifungal Treatment Strategies to Prevent Invasive Pulmonary Aspergillosis Infection-Related Deaths in Intensive Care Unit Patients: The Need for Standardization of Research Definitions.

The clinical spectrum of invasive pulmonary aspergillosis (IPA) has expanded in recent decades. A large group of patients admitted to intensive care units (ICU) is indeed susceptible to the development of IPA. Although timely diagnosis and antifungal therapy of IPA in this expanding population is crucial to prevent IPA-related deaths, the magnitude of the favorable prognostic impact of antifungal therapy is difficult to measure precisely. In our opinion, the development of standardized research definitions could have favorable implications for further improving our ability both to measure the favorable effect of antifungal treatment and to prevent IPA-related death in ICU patients.

Interpreting the results of rapid molecular diagnostic tests for carbapenem-resistant Enterobacterales infection: current clinical perspective while waiting for further evidence.

INTRODUCTION: Carbapenem-resistant Enterobacterales (CRE) causing severe infections in humans have represented an important challenge for clinicians worldwide during the past two decades. AREAS COVERED: Novel ß-lactams and ß-lactam/ß-lactamase inhibitor combinations have led to a shift in the first-line approach to the treatment of severe CRE infections from polymyxin-based regimens to treatment with less toxic agents. This new scenario offers the opportunity to apply rapid molecular diagnostic tests for CRE infection to identify different types of carbapenemases. Herein, the authors provide an overview of this subject and follow it with their expert perspectives. EXPERT OPINION: When considering studies actually measuring the clinical impact of rapid molecular tests in real-life scenarios, high certainty evidence from randomized controlled trials is still limited and not focused on CRE infections. Nonetheless, it is indisputable that rapid molecular tests have been shown to impact early therapeutic choices (in terms of both escalation and de-escalation) when used in real-life settings, thus issues in the clinical interpretation of their results are already relevant. Overall, increased expertise is required for the appropriate interpretation of rapid molecular tests for personalized antibiotic selection by understanding their strengths and limitations.

Towards the automatic calculation of the EQUAL Candida Score: Extraction of CVC-related information from EMRs of critically ill patients with candidemia in Intensive Care Units.

OBJECTIVES: Candidemia is the most frequent invasive fungal disease and the fourth most frequent bloodstream infection in hospitalized patients. Its optimal management is crucial for improving patients' survival. The quality of candidemia management can be assessed with the EQUAL Candida Score. The objective of this work is to support its automatic calculation by extracting central venous catheter-related information from Italian text in clinical notes of electronic medical records. MATERIALS AND METHODS: The sample includes 4,787 clinical notes of 108 patients hospitalized between January 2018 to December 2020 in the Intensive Care Units of the IRCCS San Martino Polyclinic Hospital in Genoa (Italy). The devised pipeline exploits natural language processing (NLP) to produce numerical representations of clinical notes used as input of machine learning (ML) algorithms to identify CVC presence and removal. It compares the performances of (i) rule-based method, (ii) count-based method together with a ML algorithm, and (iii) a transformers-based model. RESULTS: Results, obtained with three different approaches, were evaluated in terms of weighted F1 Score. The random forest classifier showed the higher performance in both tasks reaching 82.35%. CONCLUSION: The present work constitutes a first step towards the automatic calculation of the EQUAL Candida Score from unstructured daily collected data by combining ML and NLP methods. The automatic calculation of the EQUAL Candida Score could provide crucial real-time feedback on the quality of candidemia management, aimed at further improving patients' health.

Treating influenza with neuraminidase inhibitors: an update of the literature.

INTRODUCTION: Influenza affects individuals of all ages and poses a significant threat during pandemics, epidemics, and sporadic outbreaks. Neuraminidase inhibitors (NAIs) are currently the first choice in the treatment and prevention of influenza, but their use can be hindered by viral resistance. AREAS COVERED: This review summarizes current NAIs pharmacological profiles, their current place in therapy, and the mechanisms of viral resistance and outlines possible new indications, ways of administration, and novel candidate NAIs compounds. EXPERT OPINION: NAIs represent a versatile group of compounds with diverse administration methods and pharmacokinetics. While the prevalence of influenza virus resistance to NAIs remains low, there is heightened vigilance due to the pandemic potential of influenza. Several novel NAIs and derivatives are currently under assessment at various stages of development for the treatment and prevention of influenza.

Cefepime-taniborbactam and CERTAIN-1: Can we treat carbapenem-resistant infections?

Wagenlehner and colleagues1 demonstrated non-inferiority and superiority with respect to a primary endpoint of composite success (microbiological plus clinical) of cefepime/taniborbactam vs. meropenem in treating complicated urinary tract infections and acute pyelonephritis caused by carbapenem-susceptible gram-negative bacteria in adults. A major area of interest in real-world application of cefepime/taniborbactam is its potential role in treating carbapenem-resistant infections, which deserves further investigation.

Explainable and Interpretable Machine Learning for Antimicrobial Stewardship: Opportunities and Challenges.

There is growing interest in exploiting the advances in artificial intelligence and machine learning (ML) for improving and monitoring antimicrobial prescriptions in line with antimicrobial stewardship principles. Against this background, the concepts of interpretability and explainability are becoming increasingly essential to understanding how ML algorithms could predict antimicrobial resistance or recommend specific therapeutic agents, to avoid unintended biases related to the "black box" nature of complex models. In this commentary, we review and discuss some relevant topics on the use of ML algorithms for antimicrobial stewardship interventions, highlighting opportunities and challenges, with particular attention paid to interpretability and explainability of employed models. As in other fields of medicine, the exponential growth of artificial intelligence and ML indicates the potential for improving the efficacy of antimicrobial stewardship interventions, at least in part by reducing time-consuming tasks for overwhelmed health care personnel. Improving our knowledge about how complex ML models work could help to achieve crucial advances in promoting the appropriate use of antimicrobials, as well as in preventing antimicrobial resistance selection and dissemination.

Amoebic Liver Abscess: Potential Application of New Diagnostic Techniques for an Old Pathogen.

Amoebic liver abscess is a severe and potentially life-threatening infection requiring prompt diagnosis and early targeted treatment. Diagnosis is challenging because conventional diagnostic methods such as light microscopy and serology are often unreliable. Molecular techniques have emerged as an additional diagnostic tool, suddenly becoming the new diagnostic reference standard. More recently, commercial multiplex PCR panels, including FilmArray, have been introduced, which permit the simultaneous detection of several enteric pathogens including Entamoeba histolytica in stool samples. We report a case of an amoebic liver abscess promptly diagnosed by FilmArray gastrointestinal panel performed on liver drainage fluid.

Lower blood levels of isavuconazole in critically ill patients compared with other populations: possible need for therapeutic drug monitoring.

BACKGROUND: Isavuconazole is first-line treatment of invasive aspergillosis. Therapeutic drug monitoring (TDM) is deemed not necessary, since most patients reached therapeutic levels (>1 mg/L) in large studies. Low levels were reported in some critically ill patients admitted to the ICU. The aim was to compare isavuconazole levels between critically ill and non-critically ill patients. MATERIALS AND METHODS: Retrospective analysis of data from all patients treated with standard-dose isavuconazole between 1 January 2019 and 26 October 2022 was performed. The following data were collected: TDM results from the first 30 days of therapy; ward of admission; demographic and clinical characteristics; continuous renal replacement therapy; extracorporeal membrane oxygenation; and co-administered drugs. RESULTS: Seventy-two patients (median age 65 years) and 188 TDM measurements (mean number of samples per patient 2.6 ±â€Š1.7) were included; 33 (45.8%) were ICU patients (3 also had haematological disorders); 39 (54.2%) were non-ICU patients, of whom 31 had haematological disorders. In all patients, the mean isavuconazole blood level was 3.33 ±â€Š2.26 mg/L. Significantly lower levels were observed in the ICU versus the non-ICU population: mean 2.02 ±â€Š1.22 versus 4.15 ±â€Š2.31 mg/L (P < 0.001). Significantly higher rates of subtherapeutic levels were observed in ICU patients compared with the non-ICU population: all determinations <2 mg/L in 33.3% versus 7.7%, and all determinations <1 mg/L in 12.1% versus 0%, respectively. Predictors of lower isavuconazole levels were admission to the ICU, BMI > 25 kg/m2, bilirubin > 1.2 mg/dL and the absence of haematological disorder. CONCLUSIONS: ICU patients had significantly lower isavuconazole blood levels compared to non-ICU population. The TDM of isavuconazole for efficacy should be performed in ICU.

Emerging treatment options for skin and soft tissue infections tailoring drug selection to individual patients.

PURPOSE OF REVIEW: To provide a brief overview of drugs in Phase II and III of development for the treatment of acute bacterial skin and skin structure infections (ABSSSI), offering insights into potential customized treatment options. RECENT FINDINGS: Several drugs are currently in advanced stages of evaluation for the treatment of ABSSSI, and numerous molecules are entering in the early development phases. Notably, many of these drugs exhibit unique mechanisms of action and interesting antimicrobial spectrum. SUMMARY: Tailoring antibiotic therapy based on patient characteristics, likely pathogens, type, site and severity of ABSSSI is crucial. Given the inherent limitations of available treatments, the development of novel agents is a pivotal avenue. Such advancements hold promise for enhancing treatment efficacy and simplifying drug selection for ABSSSI in everyday clinical practice.

Laboratory and clinical management capacity for invasive fungal infections: the Italian landscape.

BACKGROUND: We assessed the laboratory diagnosis and treatment of invasive fungal disease (IFD) in Italy to detect limitations and potential for improvement. METHODS: The survey was available online at www.clinicalsurveys.net/uc/IFI management capacity/, and collected variables such as (a) institution profile, (b) perceptions of IFD in the respective institution, (c) microscopy, (d) culture and fungal identification, (e) serology, (f) antigen detection, (g) molecular tests, (h) susceptibility testing and (i) therapeutic drug monitoring (TDM). RESULTS: The laboratory capacity study received responses from 49 Italian centres, with an equitable geographical distribution of locations. The majority of respondents (n = 36, 73%) assessed the occurrence of IFD as moderate-high, with Aspergillus spp. being the pathogen of highest concern, followed by Candida spp. and Mucorales. Although 46 (94%) of the institutions had access to microscopy, less than half of them performed direct microscopy on clinical specimens always when IFD was suspected. Cultures were available in all assessed laboratories, while molecular testing and serology were available in 41 (83%), each. Antigen detection tests and antifungal drugs were also generally accessible (> 90%) among the participating institutions. Nevertheless, access to TDM was limited (n = 31, 63%), with a significant association established between therapeutic drug monitoring availability and higher gross domestic product per capita. CONCLUSIONS: Apart from TDM, Italy is adequately prepared for the diagnosis and treatment of IFD, with no significant disparities depending on gross domestic product. Future efforts may need to focus on enhancing the availability and application of direct microscopic methods, as well as TDM, to promote optimal treatment and better patient outcomes.