Background: Infections occurring among outpatients having recent contact with the health-care system have been recently classified as health-care-associated infections to distinguish them from hospital- and community-acquired infections. Patients with bloodstream infections (BSIs) were studied to assess health-care-associated infections at admission in the ICU.
Methods: This work was a multicenter, prospective, observational study of all adult patients with BSI at ICU admission at 27 Spanish hospitals and one Argentine hospital. Cases of BSI were classified as community-acquired BSI (CAB), health-care-associated BSI (HCAB), or hospital-acquired BSI (HAB), and their characteristics were compared.
Results: Of 726 BSIs, 343 (47.2%) were CABs, 252 (34.7%) were HABs, and 131 (18.0%) were HCABs. Potentially antibiotic-resistant pathogens were more frequently isolated in HABs (34.8%) and HCABs (27.6%) than in CABs (10.3%) (P < .001). Logistic regression analysis revealed that HABs (OR, 4.6; 95% CI, 2.9-7.3), HCABs (OR, 3.1; 95% CI, 1.8-5.4), and BSIs of unknown origin (OR, 1.7; 95% CI, 1.0-2.8) were independently associated with the isolation of potentially antibiotic-resistant pathogens. The incidence of inappropriate treatment was significantly higher in HABs (OR, 3.4; 95% CI, 2.1-5.3) and in HCABs (OR, 1.8; 95% CI, 1.0-3.2) than in CABs.
Conclusions: One in five BSIs diagnosed at ICU admission is health-care-associated. The incidence of potentially drug-resistant pathogens in HCABs is more similar to that of HABs, and they should be treated as such until culture data are available.
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http://dx.doi.org/10.1378/chest.10-1715 | DOI Listing |
PLoS Negl Trop Dis
January 2025
Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, United Kingdom.
Salmonella enterica serovar Typhimurium is a prevalent food-borne pathogen that is usually associated with gastroenteritis infection. S. Typhimurium is also a major cause of bloodstream infections in sub-Saharan Africa, and is responsible for invasive non-typhoidal Salmonella (iNTS) disease.
View Article and Find Full Text PDFClin Exp Dermatol
January 2025
St John's Institute of Dermatology, Guy's and St Thomas' NHS Foundation Trust, London, UK.
Background: In recessive dystrophic epidermolysis bullosa (RDEB), complications like oesophageal strictures, hand contractures, cardiomyopathy and cutaneous squamous cell carcinoma (SCC) may develop, necessitating procedures such as oesophageal dilatation (OD), gastrostomy tube placement and hand surgery.
Objectives: To determine prevalence and age of onset of milestone events by RDEB subtype, specifically dysphagia, first OD, first gastrostomy tube, first hand surgery, cardiomyopathy, first SCC and death.
Methods: The Prospective Epidermolysis Bullosa Longitudinal Evaluation Study (PEBLES) is a register study of individuals with RDEB which records comprehensive EB- and non-EB-related health information.
Ann Intensive Care
January 2025
Department of Anesthesiology, Critical Care, and Surgery, Duke University School of Medicine, Durham, NC, USA.
Acta Parasitol
January 2025
Department of Biomedicine and Biotechnology, Faculty of Medicine, University of Alcala, Alcala de Henares, Spain.
Purpose: Malaria remains a major global health challenge, particularly in sub-Saharan Africa and low- and middle-income countries (LMICs), contributing substantially to mortality and morbidity rates. In resource-limited settings, access to specialized diagnostic tests is often restricted, making basic blood analysis a valuable diagnostic tool. This study investigated the correlation between malaria infection and full blood count values in a rural region of Ghana during the 2022 rainy season, aiming to highlight diagnostic insights available from routine blood analyses.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Department of Computer Science, Duke University, Durham, NC 27708, United States.
Objective: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these 2 categories by building on modern interpretable machine learning (ML) techniques to design interpretable mortality risk scores that are as accurate as black boxes.
Material And Methods: We developed a new algorithm, GroupFasterRisk, which has several important benefits: it uses both hard and soft direct sparsity regularization, it incorporates group sparsity to allow more cohesive models, it allows for monotonicity constraint to include domain knowledge, and it produces many equally good models, which allows domain experts to choose among them.
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