Articles: sepsis.
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Multicenter Study
Characteristics, predictors and outcomes of new-onset QT prolongation in sepsis: a multicenter retrospective study.
Sepsis-induced myocardial injury is a serious complication of sepsis. QT prolongation is a proarrhythmic state which reflects myocardial injury in a group of heterogeneous disorders. However, the study on the clinical value of QT prolongation in sepsis is limited. ⋯ New-onset QT prolongation in sepsis was associated with increased mortality as well as atrial and ventricular arrhythmias, which was predicted by disease severity and organ dysfunction.
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The incidence of sepsis-induced coagulopathy (SIC) is high, leading to increased mortality rates and prolonged hospitalization and intensive care unit (ICU) stays. Early identification of SIC patients at risk of in-hospital mortality can improve patient prognosis. The objective of this study is to develop and validate machine learning (ML) models to dynamically predict in-hospital mortality risk in SIC patients. ⋯ Anion gap and age emerged as the most significant features for predicting the mortality risk in SIC. In this study, an ML model was constructed that exhibited excellent performance in predicting in-hospital mortality risk in SIC patients. Specifically, the stacking ensemble model demonstrated superior predictive ability.
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Elevated central venous pressure (CVP) is deemed as a sign of right ventricular (RV) dysfunction. We aimed to characterize the echocardiographic features of RV in septic patients with elevated CVP, and quantify associations between RV function parameters and 30-day mortality. ⋯ Echocardiographic findings demonstrated a high prevalence of RV-related abnormalities (RV enlargement, RV systolic dysfunction and PVR increase) in septic patients with elevated CVP. Among those echocardiographic parameters, TAPSE and PVR were independently associated with 30-day mortality in these patients.
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Intensive care medicine · Apr 2024
Multicenter Study Clinical TrialAchievement of therapeutic antibiotic exposures using Bayesian dosing software in critically unwell children and adults with sepsis.
Early recognition and effective treatment of sepsis improves outcomes in critically ill patients. However, antibiotic exposures are frequently suboptimal in the intensive care unit (ICU) setting. We describe the feasibility of the Bayesian dosing software Individually Designed Optimum Dosing Strategies (ID-ODS™), to reduce time to effective antibiotic exposure in children and adults with sepsis in ICU. ⋯ Dosing software may reduce the time to achieve target antibiotic exposures. It should be evaluated further in trials to establish its impact on clinical outcomes.