Adequate data on the pharmacokinetics of once-daily administration of ertapenem in critically ill patients are largely lacking. This single-centre, prospective, open-label study was performed on a cohort of eight critically ill patients with severe sepsis with normal renal function treated with 1g of ertapenem once daily. Samples of venous blood and urine were collected before infusion and at specific time points in the 24-h post-infusion period. Plasma and urine ertapenem levels were determined by reverse-phase high-performance liquid chromatography (HPLC) with ultraviolet detection. The non-protein-bound fraction was determined in the filtrate by HPLC using a Centrifree device. The current study showed a lower maximum plasma concentration (C(max)) (52.3.0mg/L vs. 253 mg/L) and area under the concentration-time curve from 0 h to infinity (AUC(0-infinity)) (188 mg h/L vs. 817 mg h/L) but higher volume of distribution at steady state (V(ss)) (26.8L vs. 5.7 L) compared with those observed in young healthy volunteers. For unbound ertapenem, geometric means of C(max) and AUC(0-infinity) were 29.5mg/L and 103.5 mg h/L, respectively, and correlated negatively with hypoalbuminaemia. Unbound levels failed to exceed a minimum inhibitory concentration of 1mg/L for more than 7.1h (30%) of the dosing interval in two patients. The highly variable and unpredictable intersubject pharmacokinetic parameters documented in this study resulted in suboptimal unbound concentrations in some patients. This raises the question as to whether ertapenem is an appropriate agent for initial use in critically ill patients with severe sepsis.
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http://dx.doi.org/10.1016/j.ijantimicag.2008.10.005 | DOI Listing |
J Crit Care
January 2025
Department of Critical Care, School of Medicine, University of Melbourne, Parkville, Victoria, Australia; Department of Intensive Care, Royal Melbourne Hospital, Parkville, Victoria, Australia; Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Victoria, Australia; Data Analytics Research and Evaluation, Austin Hospital, Melbourne, Australia. Electronic address:
Background: Hypernatremia is relatively common in acutely ill patients and associated with mortality. Guidelines recommend a slow rate of correction (≤ 0.5 mmol/L per hour).
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December 2024
Hacettepe University, Department of Internal Medicine, Division of Geriatric Medicine, Ankara, Turkey.
Background And Aim: Malnutrition is strongly related to mortality in intensive care unit (ICU) patients. The Patient- and Nutrition-Derived Outcome Risk Assessment Score (PANDORA) is a novel mortality prediction tool encompassing nutritional assessment. Since there is limited evidence regarding the power of PANDORA in predicting mortality in critically ill patients, we aimed to evaluate the benefit of adding PANDORA to the Global Leadership Initiative on Malnutrition (GLIM) for mortality prediction in the ICU setting by comparing it with the other valid mortality predictors.
View Article and Find Full Text PDFBest Pract Res Clin Anaesthesiol
September 2024
Department of Anaesthesiology, University Hospitals Leuven (BE), Department of Cardiovascular Sciences, KU Leuven (BE), Herestraat 49, B-3000, Leuven, Belgium.
Critical illness during pregnancy poses significant challenges driven by complex interactions between physiological changes, pre-existing conditions, and healthcare disparities. In high-income countries, increasing maternal age and comorbidities complicate obstetric care by triggering an unprecedented rise in cardiac disease during pregnancy, while infections like influenza and COVID-19 are important causes of maternal adult respiratory distress syndrome. Extracorporeal membrane oxygenation (ECMO) gained prominence as a vital intervention, providing respiratory and/or cardiac support, for varying indications between antenatal and postpartum periods.
View Article and Find Full Text PDFEClinicalMedicine
December 2024
Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Background: Infant alertness and neurologic changes can reflect life-threatening pathology but are assessed by physical exam, which can be intermittent and subjective. Reliable, continuous methods are needed. We hypothesized that our computer vision method to track movement, pose artificial intelligence (AI), could predict neurologic changes in the neonatal intensive care unit (NICU).
View Article and Find Full Text PDFJ Intensive Care Soc
January 2025
Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.
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