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Objectives: This study aims to identify infection etiology in febrile neutropenia (FN) is vital. This study explores different microbiological approaches and their impact on diagnosing infections in patients with hematologic malignancies and FN. Methods: This is a retrospective analysis conducted at the Hospital Clinic of Barcelona details microbiological testing strategies used to diagnose infections at FN onset between January 2020 and July 2022. Results: A total of 4520 microbiological tests were ordered in 462 FN episodes, achieving a 10% test positivity rate, with 200 (43.3%) episodes showing microbiological documentation of infection. Blood cultures (40.4%), non-culture blood tests (21.2%), and respiratory tract samples (16.2%) were the most requested. Blood cultures exhibited the highest (16.9%) test positivity rates, whereas non-culture blood tests showed the lowest (3.3%). Bacterial infections were present in 149 of 462 (32.3%) FN episodes. Viral infections (66 of 462, 14.3%)—notably, respiratory viruses—were also frequent. Mortality rate at 60 days was 9.1%; documented infections were associated with a higher risk (15%). Conclusions: In the current landscape of antimicrobial diagnostics, our findings revealed the highest reported rate of microbiologically documented infections at FN onset. Bacterial infections are common; however, our data reiterate the significance of viral infections in causing fever. Optimizing FN management during respiratory viral infections remains a challenge for antimicrobial de-escalation. The low positivity rates observed in certain diagnostic tests emphasize the need for cost-effective diagnostic stewardship.

Objectives To describe the management of haematological patients experiencing prolonged SARS-CoV-2 viral shedding, as the optimal management strategy for this condition remains undetermined. Methods We conducted a retrospective evaluation of our prospectively followed cohort of haematological patients treated with remdesivir for more than 10 days. Starting January 2023, upon COVID-19 diagnosis, the treatment strategy was based on symptoms and PCR cycle threshold (Ct) as follows: (i) when Ct was 25 or less or if the patient had symptoms, a course of remdesivir for at least 10 days, nirmatrelvir/ritonavir for 5 days (whenever possible) and convalescent plasma was administered; and (ii) when the patient was asymptomatic and had a PCR Ct of more than 25, when possible, a course of 5 days of nirmatrelvir/ritonavir was administered. The patient was considered to have achieved viral clearance and, thus, remdesivir was stopped, in either of these cases: (i) PCR negativity, or (ii) subgenomic RNA negativity. Results From January to November 2023, 18 patients benefited from a safe extended remdesivir administration, resulting in detection of SARS-CoV-2 viral clearance in a median time of 3.5 weeks (IQR 2.6–3.9) (min–max 1.6–8.0). No clinical or biological side effects were detected. No patient died or needed further treatment for their COVID-19 episode. Conclusions The extended course of remdesivir, combined with other active therapies for COVID-19 infection, was well tolerated. Cure and virus negativity were obtained in all these high-risk patients. [ABSTRACT FROM AUTHOR]

RESUMEN La neurofibromatosis tipo 1 es una entidad poco frecuente, pero con gran cantidad de complicaciones que pueden ocasionar un gran impacto en la calidad de vida. Los neurofibromas plexiformes son característicos de esta, siendo su diagnóstico fundamentalmente clínico. ABSTRACT Neurofibromatosis type 1 is a rare entity, but with a large number of complications that can have a great impact on quality of life. Plexiform neurofibromas are characteristic of this, and its diagnosis is fundamentally clinical.

Background This study aimed to describe documented infections associated with postinfusion fever after CAR T-cell therapy and to evaluate daily changes in vital signs, laboratory results, and the National Early Warning Score (NEWS) in patients with and without confirmed bacterial infections following fever onset, with the objective of assisting in antibiotic stewardship. Methods This was a retrospective, observational study including all consecutive adult patients who received CAR T-cell therapy. Documented infection in the first fever episode after infusion, and clinical and analytic trend comparison of patients with bacterial documented infections and those without documented infections, are described. Results Among 152 patients treated with CAR T-cell therapy, 87 (57.2%) had fever within 30 days of infusion, with a median time from infusion to fever of 3 (interquartile range, 2–5) days. Of these 87 patients, 82 (94.3%) received broad-spectrum antibiotics. Infection was documented in 9 (10.3%) patients and only 4 (4.6%) had bacterial infections. Clinical signs and biomarkers were similar in patients with bacterial documented infection and in those without documented infection at fever onset. Fever, tachycardia, and high C-reactive protein levels remained high during the first 3 days after CAR T-cell infusion, even when no infection was documented. Conclusions Fever is a common symptom following CAR T-cell infusion and is largely treated with broad-spectrum antibiotics. However, confirmed bacterial documented infections after the first fever post–CAR T-cell infusion are very unusual. Because clinical parameters and biomarkers are not useful for identifying infectious fever, other methods should be assessed to ensure the proper use of antibiotics. [ABSTRACT FROM AUTHOR]

Aim: This study addresses the challenge of predicting the course of Adult‐onset Still's disease (AoSD), a rare systemic autoinflammatory disorder of unknown origin. Precise prediction is crucial for effective clinical management, especially in the absence of specific laboratory indicators. Methods: We assessed the effectiveness of combining traditional biomarkers with the k‐medoids unsupervised clustering algorithm in forecasting the various clinical courses of AoSD—monocyclic, polycyclic, or chronic articular. This approach represents an innovative strategy in predicting the disease's course. Results: The analysis led to the identification of distinct patient profiles based on accessible biomarkers. Specifically, patients with elevated ferritin levels at diagnosis were more likely to experience a monocyclic disease course, while those with lower erythrocyte sedimentation rate could present with any of the clinical courses, monocyclic, polycyclic, or chronic articular, during follow‐up. Conclusion: The study demonstrates the potential of integrating traditional biomarkers with unsupervised clustering algorithms in understanding the heterogeneity of AoSD. These findings suggest new avenues for developing personalized treatment strategies, though further validation in larger, prospective studies is necessary. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) and machine learning (ML) have the potential to revolutionize the management of febrile neutropenia (FN) and drive progress toward personalized medicine. In this review, we detail how the collection of a large number of high-quality data can be used to conduct precise mathematical studies with ML and AI. We explain the foundations of these techniques, covering the fundamentals of supervised and unsupervised learning, as well as the most important challenges, e.g. data quality, 'black box' model interpretation and overfitting. To conclude, we provide detailed examples of how AI and ML have been used to enhance predictions of chemotherapy-induced FN, detection of bloodstream infections (BSIs) and multidrug-resistant (MDR) bacteria, and anticipation of severe complications and mortality. There is promising potential of implementing accurate AI and ML models whilst managing FN. However, their integration as viable clinical tools poses challenges, including technical and implementation barriers. Improving global accessibility, fostering interdisciplinary collaboration, and addressing ethical and security considerations are essential. By overcoming these challenges, we could transform personalized care for patients with FN. [ABSTRACT FROM AUTHOR]

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ABSTRACT The study aimed to describe the epidemiology of multidrug-resistant (MDR) bacteria among solid cancer (SC) patients with bloodstream infections (BSIs), evaluating inappropriate empiric antibiotic treatment (IEAT) use and mortality trends over a 25-year period. All BSI occurrences in adult SC patients at a university hospital were analyzed across five distinct five-year intervals. MDR bacteria were classified as extended-spectrum beta-lactamases (ESBL)-producing and/or Carbapenem-resistant Enterobacterales, non-fermenting Gram-negative bacilli (GNB) resistant to at least three antibiotic classes, methicillin-resistant Staphylococcus aureus (MRSA), and Vancomycin-resistant Enterococci. A multivariate regression model identified the risk factors for MDR BSI. Of 6,117 BSI episodes, Gram-negative bacilli (GNB) constituted 60.4% (3,695/6,117), being the most common are Escherichia coli with 26.8% (1,637/6,117), Klebsiella spp. with 12.4% (760/6,117), and Pseudomonas aeruginosa with 8.6% (525/6,117). MDR-GNB accounted for 644 episodes (84.8% of MDR or 644/759), predominantly ESBL-producing strains (71.1% or 540/759), which escalated significantly over time. IEAT was administered in 24.8% of episodes, mainly in MDR BSI, and was associated with higher mortality (22.9% vs. 14%, P < 0.001). Independent factors for MDR BSI were prior antibiotic use [odds ratio (OR) 2.93, confidence interval (CI) 2.34–3.67], BSI during antibiotic treatment (OR 1.46, CI 1.18–1.81), biliary (OR 1.84, CI 1.34–2.52) or urinary source (OR 1.86, CI 1.43–2.43), admission period (OR) 1.28, CI 1.18–1.38, and community-acquired infection (OR 0.57, CI 0.39–0.82). The study showed an increase in MDR-GNB among SC patients with BSI. A quarter received IEAT, which was linked to increased mortality. Improving risk assessment for MDR infections and the judicious prescription of empiric antibiotics are crucial for better outcomes.IMPORTANCEMultidrug-resistant (MDR) bacteria pose a global public health threat as they are more challenging to treat, and they are on the rise. Solid cancer patients are often immunocompromised due to their disease and cancer treatments, making them more susceptible to infections. Understanding the changes and trends in bloodstream infections in solid cancer patients is crucial, to help physicians make informed decisions about appropriate antibiotic therapies, manage infections in this vulnerable population, and prevent infection. Solid cancer patients often require intensive and prolonged treatments, including surgery, chemotherapy, and radiation therapy. Infections can complicate these treatments, leading to treatment delays, increased healthcare costs, and poorer patient outcomes. Investigating new strategies to combat MDR infections and researching novel antibiotics in these patients is of paramount importance to avoid these negative impacts.

Abstract Introduction The impact of remdesivir on mortality in patients with COVID-19 is still controversial. We aimed to identify clinical phenotype clusters of COVID-19 hospitalized patients with highest benefit from remdesivir use and validate these findings in an external cohort. Methods We included consecutive patients hospitalized between February 2020 and February 2021 for COVID-19. The derivation cohort comprised subjects admitted to Hospital Clinic of Barcelona. The validation cohort included patients from Hospital Universitari Mutua de Terrassa (Terrassa) and Hospital Universitari La Fe (Valencia), all tertiary centers in Spain. We employed K-means clustering to group patients according to reverse transcription polymerase chain reaction (rRT-PCR) cycle threshold (Ct) values and lymphocyte counts at diagnosis, and pre-test symptom duration. The impact of remdesivir on 60-day mortality in each cluster was assessed. Results A total of 1160 patients (median age 66, interquartile range (IQR) 55–78) were included. We identified five clusters, with mortality rates ranging from 0 to 36.7%. Highest mortality rate was observed in the cluster including patients with shorter pre-test symptom duration, lower lymphocyte counts, and lower Ct values at diagnosis. The absence of remdesivir administration was associated with worse outcome in the high-mortality cluster (10.5% vs. 36.7%; p

Clinical Decision Support Systems (CDSS) are computer-based tools that leverage the analysis of large volumes of health data to assist healthcare professionals in making clinical decisions, whether preventive, diagnostic, or therapeutic. This review examines the impact of CDSS on clinical practice, highlighting both their potential benefits and their limitations and challenges. We detail the experience of clinical medical professionals in the development of a virtual control center for COVID-19 patients (C3 COVID-19) in Spain during the SARS-CoV-2 pandemic. This tool enabled real-time monitoring of clinical data for hospitalized COVID-19 patients, optimizing personalized and informed medical decision-making. CDSS can offer significant advantages, such as improving the quality of inpatient care, promoting evidence-based clinical and therapeutic decision-making, facilitating treatment personalization, and enhancing healthcare system efficiency and productivity. However, the implementation of CDSS presents challenges, including the need for physicians to become familiar with the systems and software, and the necessity for ongoing updates and technical support of the systems., (©The Author 2024. Published by Sociedad Española de Quimioterapia. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)(https://creativecommons.org/licenses/by-nc/4.0/).)

The study aimed to describe the epidemiology of multidrug-resistant (MDR) bacteria among solid cancer (SC) patients with bloodstream infections (BSIs), evaluating inappropriate empiric antibiotic treatment (IEAT) use and mortality trends over a 25-year period. All BSI occurrences in adult SC patients at a university hospital were analyzed across five distinct five-year intervals. MDR bacteria were classified as extended-spectrum beta-lactamases (ESBL)-producing and/or Carbapenem-resistant Enterobacterales, non-fermenting Gram-negative bacilli (GNB) resistant to at least three antibiotic classes, methicillin-resistant Staphylococcus aureus (MRSA), and Vancomycin-resistant Enterococci . A multivariate regression model identified the risk factors for MDR BSI. Of 6,117 BSI episodes, Gram-negative bacilli (GNB) constituted 60.4% (3,695/6,117), being the most common are Escherichia coli with 26.8% (1,637/6,117), Klebsiella spp. with 12.4% (760/6,117), and Pseudomonas aeruginosa with 8.6% (525/6,117). MDR-GNB accounted for 644 episodes (84.8% of MDR or 644/759), predominantly ESBL-producing strains (71.1% or 540/759), which escalated significantly over time. IEAT was administered in 24.8% of episodes, mainly in MDR BSI, and was associated with higher mortality (22.9% vs. 14%, P < 0.001). Independent factors for MDR BSI were prior antibiotic use [odds ratio (OR) 2.93, confidence interval (CI) 2.34-3.67], BSI during antibiotic treatment (OR 1.46, CI 1.18-1.81), biliary (OR 1.84, CI 1.34-2.52) or urinary source (OR 1.86, CI 1.43-2.43), admission period (OR) 1.28, CI 1.18-1.38, and community-acquired infection (OR 0.57, CI 0.39-0.82). The study showed an increase in MDR-GNB among SC patients with BSI. A quarter received IEAT, which was linked to increased mortality. Improving risk assessment for MDR infections and the judicious prescription of empiric antibiotics are crucial for better outcomes., Importance: Multidrug-resistant (MDR) bacteria pose a global public health threat as they are more challenging to treat, and they are on the rise. Solid cancer patients are often immunocompromised due to their disease and cancer treatments, making them more susceptible to infections. Understanding the changes and trends in bloodstream infections in solid cancer patients is crucial, to help physicians make informed decisions about appropriate antibiotic therapies, manage infections in this vulnerable population, and prevent infection. Solid cancer patients often require intensive and prolonged treatments, including surgery, chemotherapy, and radiation therapy. Infections can complicate these treatments, leading to treatment delays, increased healthcare costs, and poorer patient outcomes. Investigating new strategies to combat MDR infections and researching novel antibiotics in these patients is of paramount importance to avoid these negative impacts., Competing Interests: C.G.-V. has received honoraria for talks on behalf of Gilead Sciences, MSD, Novartis, Pfizer, Janssen, and Lilly, as well as a grant from Gilead Sciences, Pfizer, and MSD. P.P.-A. has received honoraria for talks on behalf of Merck Sharp & Dohme, Gilead, Lilly, ViiV Healthcare, and Gilead Sciences. A.S. has received honoraria for talks on behalf of Merck Sharp & Dohme, Pfizer, Novartis, Angelini, Menarini, and Gilead Sciences, as well as grant support from Pfizer and Gilead Sciences. O.P. has received honoraria for talks on behalf of MSD, Qiagen, and expertise for Sanofi.