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.

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.

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.

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.

Natural history and prognostic factors of candidemia in kidney transplant recipients: A retrospective, multinational study.

BACKGROUND: The natural history of candidemia in kidney transplant recipients (KTR) remains poorly understood. This study aimed to evaluate mortality, prognostic factors and overall graft loss after candidemia in KTRs. METHODS: This is a retrospective multicentre study enrolling all KTRs ≥15 years old with candidemia diagnosed at hospitals in Brazil, Spain and Italy from 2010 to 2020. Primary endpoints were mortality rates at 14 and 30 days. Secondary endpoints were prognostic factors of 14-day mortality and overall graft loss. RESULTS: We enrolled 93 KTRs of which 75 were from Brazil. The mean time interval from transplantation to the onset of candidemia was 45.2 ± 61.5 months. 42% of all patients were on haemodialysis, 31.3% had an episode of sepsis and 39% underwent surgery within 30 days before fungemia. European patients were more likely to receive echinocandin (32 vs. 72%, p < .001). 22.7% of Brazilian patients did not receive any antifungal before death. All-cause mortality at 14 days was higher in Brazil (41.3 vs. 11.1%, p = .016). Candida colonisation (OR 6.91 [95% CI: 1.08-44.3], p = .042) and hypotension (OR 4.87 [95% CI: 1.62-14.66], p = .005) were associated with 14-day mortality. Echinocandin treatment had a protective effect (OR 0.19 [95% CI: 0.05-0.73], p = .015). Graft loss at 90 days occurred in 48% of patients (70.7 in Brazil vs. 22.2% in Europe, p < .01). CONCLUSIONS: Candidemia in KTR is usually documented late after engraftment in patients requiring HD, surgical procedures and dysbiosis secondary to antibiotic use. Mortality was higher in Brazil. Echinocandin therapy was associated with improved survival.

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.

Neutralizing monoclonal antibodies for the prevention of severe COVID-19: a retrospective study during Omicron BA.1 variant surge.

Among treatment options for Coronavirus disease 2019 (COVID-19), monoclonal antibodies (mAbs) showed to be effective in preventing disease progression, but real-world data during the Omicron variant surge are still lacking. Multicentre retrospective study evaluating the effectiveness of sotrovimab and casirivimab-imdevimab in fragile patients with mild SARS-CoV-2 infection between November 2021 and March 2022. Unfavourable outcome was defined as increased need for oxygen supplementation and/or death. Of 268 study-participants, 12 (4.48%) previously needed supplemental oxygen, while 6 (2.24%) had active solid neoplasia (2.24%); 186 (69%) have previously received SARS-CoV-2 vaccination. Overall, 22 (8%) had unfavourable outcomes (42% versus 6% of patients with and without previous oxygen need and 50% versus 7% of patients with and without active solid neoplasia). Both supplemental oxygen therapy before SARS-CoV-2 infection and solid malignant tumour have shown to be risk factors for treatment failure. Log-rank test did not identify differences between sotrovimab and casirivimab-imdevimab treatment. Despite diffusion of Omicron variant, the rate of unfavourable outcome was higher than expected. The presence of underlying risk factors, including solid cancer and previous oxygen therapy are independently associated with risk of COVID-19 progression, suggesting the need for antiviral treatments not limited to mAbs and implementation of vaccine campaign.

Explainable artificial intelligence and machine learning: novel approaches to face infectious diseases challenges.

Artificial intelligence (AI) and machine learning (ML) are revolutionizing human activities in various fields, with medicine and infectious diseases being not exempt from their rapid and exponential growth. Furthermore, the field of explainable AI and ML has gained particular relevance and is attracting increasing interest. Infectious diseases have already started to benefit from explainable AI/ML models. For example, they have been employed or proposed to better understand complex models aimed at improving the diagnosis and management of coronavirus disease 2019, in the field of antimicrobial resistance prediction and in quantum vaccine algorithms. Although some issues concerning the dichotomy between explainability and interpretability still require careful attention, an in-depth understanding of how complex AI/ML models arrive at their predictions or recommendations is becoming increasingly essential to properly face the growing challenges of infectious diseases in the present century.

AI and ML are revolutionizing human activities in various fields, and infectious diseases are not exempt from their rapid and exponential growth.Despite some notable challenges, explainable AI/ML could provide insights into the decision-making process, making the outcomes of models more transparent.Improved transparency can help to build trust among healthcare professionals, policymakers, and the general public in leveraging AI/ML-based systems to face the growing challenges of infectious diseases in the present century.

Early diagnosis of candidemia with explainable machine learning on automatically extracted laboratory and microbiological data: results of the AUTO-CAND project.

BACKGROUND: Candidemia is associated with a heavy burden of morbidity and mortality in hospitalized patients. The availability of blood culture results could require up to 48-72 h after blood draw; thus, early treatment decisions are made in the absence of a definite diagnosis. METHODS: In this retrospective study, we assessed the performance of different supervised machine learning algorithms for the early differential diagnosis of candidemia and bacteremia in adult patients on a large dataset automatically extracted within the AUTO-CAND project. RESULTS: Overall, 12,483 episodes of candidemia (1275; 10%) or bacteremia (11,208; 90%) were included in the analysis. A random forest classifier achieved the best diagnostic performance for candidemia, with sensitivity 0.98 and specificity 0.65 on the training set (true skill statistic [TSS] = 0.63) and sensitivity 0.74 and specificity 0.57 on the test set (TSS = 0.31). Then, the random classifier was trained in the subgroup of patients with available serum ß-D-glucan (BDG) and procalcitonin (PCT) values by exploiting the feature ranking learned in the entire dataset. Although no statistically significant differences were observed from the performance measures obtained by employing BDG and PCT alone, the performance measures of the classifier that included the features selected in the entire dataset, plus BDG and PCT, were the highest in most cases. CONCLUSIONS: Random forest classifiers trained on large datasets of automatically extracted data have the potential to improve current diagnostic algorithms for candidemia. However, further development through implementation of automatically extracted clinical features may be necessary to achieve crucial improvements.

Antibiotic therapy for nonfermenting Gram-negative bacilli infections: future perspectives.

PURPOSE OF REVIEW: Serious infections caused by nonfermenting Gram-negative bacteria (NF-GNB) pose a significant challenge for clinicians due to the limited treatment options available, which are frequently associated with issues of toxicity and unfavourable pharmacokinetic profiles. The aim of this review is to provide a brief overview of the existing data concerning the ongoing development of antiinfective agents targeting NF-GNB. RECENT FINDINGS: Several agents exhibiting efficacy against NF-GNB are under clinical investigation. Durlobactam-sulbactam and cefepime-taniborbactam emerge as promising therapeutic avenues against carbapenem-resistant Acinetobacter baumanii . Cefepime-zidebactam may serve as a suitable treatment option for urinary tract infections caused by a wide range of NF-GNB. Cefepime-enmetazobactam demonstrates potent in vitro activity against various NF-GNB strains; however, its role as an anti- Pseudomonal agent is inadequately substantiated by available data. Xeruborbactam is a wide ß-lactamase inhibitor that can be associated with a range of agents, enhancing in-vitro activity of these against many NF-GNB, including those resistant to newer, broader spectrum options. Lastly, murepavadin appears to be a potential pathogen-specific solution for severe Pseudomonas infections; however, additional investigation is necessary to establish the safety profile of this compound. SUMMARY: Each of the novel molecules reviewed possesses an interesting range of in-vitro activity against NF-GNB. In addition, some of them have already been proved effective in vivo, underscoring their potential as future treatment options.

Defining a Preprocessing Pipeline for the MULTI-SITA Project and General Medical Italian Natural Language Data.

The application of Natural Language Processing (NLP) to medical data has revolutionized different aspects of health care. The benefits obtained from the implementation of this technique spill over into several areas, including in the implementation of chatbots, which can provide medical assistance remotely. Every possible application of NLP depends on one first main step: the pre-processing of the corpus retrieved. The raw data must be prepared with the aim to be used efficiently for further analysis. Considerable progress has been made in this direction for the English language but for other languages, such as Italian, the state of the art is not equivalently advanced, especially for texts containing technical medical terms. The aim of this work is to identify and develop a preprocessing pipeline suitable for medical data written in Italian. The pipeline has been developed in Python environment, employing Enchant, ntlk modules and Hugging Face's BERT and BART-based models. Then, it has been tested on real conversations typed between patients and physicians regarding medical questions. The algorithm has been developed within the MULTI-SITA project of the Italian Society of Anti-Infective Therapy (SITA), but shows a flexible structure that can adapt to a large variety of data.

Management of nonfermenting gram-negative infections: a critique of the guidelines.

PURPOSE OF REVIEW: In the present narrative review, we discuss the characteristics and differences between the Infectious Diseases Society of America (IDSA) and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) guidelines in terms on their recommendations/suggestions for the treatment of Pseudomonas aeruginosa and Acinetobacter baumannii infections. RECENT FINDINGS: Treatment of severe infections caused by nonfermenting gram-negative bacteria (NF-GNB) is posing both novel hopes and novel challenges to physicians worldwide, and both the IDSA and the ESCMID have recently updated/released their guidelines or guidance documents, based on different philosophies and providing recommendations for the treatment of NF-GNB infections. In order to correctly exploit recent advances in the treatment of such infections, IDSA and ESCMID approaches should be viewed as complementary and evolving, and should not preclude further revision based on accumulating evidence on the use of novel ß-lactams and ß-lactam/ß-lactamase inhibitor combinations. SUMMARY: A joint consideration of both philosophies should leave the door opened for the wise use of novel agents, ultimately building precious experience on their use that could favorably influence future guidelines revisions.

Pneumocystis jirovecii pneumonia in intensive care units: a multicenter study by ESGCIP and EFISG.

BACKGROUND: Pneumocystis jirovecii pneumonia (PJP) is an opportunistic, life-threatening disease commonly affecting immunocompromised patients. The distribution of predisposing diseases or conditions in critically ill patients admitted to intensive care unit (ICU) and subjected to diagnostic work-up for PJP has seldom been explored. MATERIALS AND METHODS: The primary objective of the study was to describe the characteristics of ICU patients subjected to diagnostic workup for PJP. The secondary objectives were: (i) to assess demographic and clinical variables associated with PJP; (ii) to assess the performance of Pneumocystis PCR on respiratory specimens and serum BDG for the diagnosis of PJP; (iii) to describe 30-day and 90-day mortality in the study population. RESULTS: Overall, 600 patients were included in the study, of whom 115 had presumptive/proven PJP (19.2%). Only 8.8% of ICU patients subjected to diagnostic workup for PJP had HIV infection, whereas hematological malignancy, solid tumor, inflammatory diseases, and solid organ transplants were present in 23.2%, 16.2%, 15.5%, and 10.0% of tested patients, respectively. In multivariable analysis, AIDS (odds ratio [OR] 3.31; 95% confidence interval [CI] 1.13-9.64, p = 0.029), non-Hodgkin lymphoma (OR 3.71; 95% CI 1.23-11.18, p = 0.020), vasculitis (OR 5.95; 95% CI 1.07-33.22, p = 0.042), metastatic solid tumor (OR 4.31; 95% CI 1.76-10.53, p = 0.001), and bilateral ground glass on CT scan (OR 2.19; 95% CI 1.01-4.78, p = 0.048) were associated with PJP, whereas an inverse association was observed for increasing lymphocyte cell count (OR 0.64; 95% CI 0.42-1.00, p = 0.049). For the diagnosis of PJP, higher positive predictive value (PPV) was observed when both respiratory Pneumocystis PCR and serum BDG were positive compared to individual assay positivity (72% for the combination vs. 63% for PCR and 39% for BDG). Cumulative 30-day mortality and 90-day mortality in patients with presumptive/proven PJP were 52% and 67%, respectively. CONCLUSION: PJP in critically ill patients admitted to ICU is nowadays most encountered in non-HIV patients. Serum BDG when used in combination with respiratory Pneumocystis PCR could help improve the certainty of PJP diagnosis.

Mortality in KPC-producing Klebsiella pneumoniae bloodstream infections: a changing landscape.

OBJECTIVES: To assess the impact of carbapenem resistance on mortality in Klebsiella pneumoniae bloodstream infection (BSI) in the era of novel ß-lactam/ß-lactamase inhibitor combinations. MATERIAL AND METHODS: Retrospective study of patients with K. pneumoniae BSI between January and August 2020 in 16 centres (CARBANEW study within the MULTI-SITA project). RESULTS: Overall, 426 patients were included: 107/426 (25%) had carbapenem-resistant K. pneumoniae (CR-Kp) BSI and 319/426 (75%) had carbapenem-susceptible K. pneumoniae (CS-Kp) BSI. Crude cumulative 30 day mortality was 33.8% and 20.7% in patients with, respectively, CR-Kp BSI and CS-Kp BSI (P = 0.027). Carbapenemase production or carbapenemase-encoding genes were detected in 84/98 tested CR-Kp isolates (85.7%), mainly KPC (78/84; 92.9%). Ceftazidime/avibactam was the most frequently used appropriate therapy for CR-Kp BSI (80/107; 74.7%). In multivariable analyses, variables showing an unfavourable association with mortality after correction for multiple testing were age-adjusted Charlson comorbidity index (HR 1.20; 95% CI 1.10-1.31, P < 0.001) and Pitt score (HR 1.33; 95% CI 1.15-1.55, P < 0.001), but not carbapenem resistance (HR 1.28, 95% CI 0.74-2.22, P = 0.410). In a propensity score-matched analysis, there was no difference in mortality between patients appropriately treated with ceftazidime/avibactam for CR-Kp BSI and patients appropriately treated with other agents (mainly meropenem monotherapy or piperacillin/tazobactam monotherapy) for CS-Kp BSI (HR 1.07; 95% CI 0.50-2.29, P = 0.866). CONCLUSIONS: Our results suggest that the increased mortality in CR-Kp BSI compared with CS-Kp BSI is not (or no longer) dependent on the type of therapy in areas where ceftazidime/avibactam-susceptible KPC-producing isolates are the most prevalent type of CR-Kp.

Severe infections caused by difficult-to-treat Gram-negative bacteria.

PURPOSE OF REVIEW: Antimicrobial resistance (AMR) in Gram-negative bacteria (GNB) poses a significant global health concern, contributing to increased infections, mortality rates, and healthcare costs. This review discusses the main clinical manifestations, therapeutic options, and recent findings in managing antibiotic-resistant GNB, with a focus on difficult-to-treat infections. RECENT FINDINGS: Difficult-to-treat resistance (DTR) is a novel classification that identifies GNB exhibiting intermediate or resistant phenotypes to first-line agents in the carbapenem, beta-lactam, and fluoroquinolone categories. The main pathogens implicated in severe infections include DTR Enterobacterales, DTR Pseudomonas aeruginosa , and DTR Acinetobacter baumannii. Although the clinical implications of DTR strains are still under investigation, certain studies have linked them to prolonged hospital stays and poor patient outcomes. SUMMARY: Severe infections caused by DTR-GNB pose a formidable challenge for healthcare providers and represent a growing global health issue. The proper administration and optimization of novel antibiotics at our disposal are of paramount importance for combating bacterial resistance and improving patient prognosis.

Use of antibiotics in hospitalized patients with COVID-19: evolving concepts in a highly dynamic antimicrobial stewardship scenario.

INTRODUCTION: Excessive use of antibiotics has been frequently reported in hospitalized patients with COVID-19 worldwide, compared to the actual number of bacterial co-infections or super-infections. AREAS COVERED: In this perspective, we discuss the current literature on the use of antibiotics and antimicrobial stewardship interventions in hospitalized patients with COVID-19. A search was conducted in PubMed up to March 2023. EXPERT OPINION: The COVID-19 pandemic has witnessed an excessive use of antibiotics in hospitals worldwide, especially before the advent of COVID-19 vaccination, although according to the most recent data there is still an important disproportion between the prevalence of antibiotic use and that of proven bacterial coinfection or superinfections. An important reduction in the prevalence of antibiotic use in COVID-19 patients reported in the literature, from 70-100% to 50-60%, has been observed after successful vaccination campaigns, likely related to the reduced median disease severity of hospitalized COVID-19 patients and some successful interventions of antimicrobial and diagnostic stewardship. However, the disproportion between antibiotic use and the prevalence of bacterial infections (4-6%) is still uncomfortable from an antimicrobial stewardship perspective and requires further attention.