Journal of critical care
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Journal of critical care · Dec 2024
Randomized Controlled Trial Multicenter StudyAntisense therapy to block the Kallikrein-kinin pathway in COVID-19: The ASKCOV randomized controlled trial.
To assess the effect of antisense therapy to block kallikrein-kinin pathway in COVID-19 patients. ⋯ NCT04549922.
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Journal of critical care · Dec 2024
Review Meta AnalysisFluid infusion prior to intubation or anesthesia: A meta-analysis of randomized controlled trials.
The results of current randomized controlled trials (RCTs) vary regarding the effectiveness of rehydration prior to anesthesia induction. Our objective was to determine the effectiveness of pre-induction rehydration in patients undergoing tracheal intubation or surgical procedures. ⋯ Pre-induction rehydration can reduce the occurrence of hypotensive events, but only in pre-surgical patients, and does not decrease the use of vasoactive medications.
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Journal of critical care · Dec 2024
Association of early changes in arterial carbon dioxide with acute brain injury in adult patients with extracorporeal membrane oxygenation: A ten-year retrospective study in a German tertiary care hospital.
To assess the association between fluctuations of arterial carbon dioxide early after start of extracorporeal membrane oxygenation (ECMO) with intracranial hemorrhage (ICH) or ischemic stroke (IS). ⋯ Irrespective of the indication for ECMO, we did not find a significant association between the relative change in PaCO2 early after ECMO initiation and acute brain injury. Aside from early PaCO2 decline at cannulation, future studies should address fluctuations of PaCO2 throughout the course of ECMO support and their effect on acute brain injury.
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Journal of critical care · Dec 2024
ReviewMachine learning for predicting mortality in adult critically ill patients with Sepsis: A systematic review.
Various Machine Learning (ML) models have been used to predict sepsis-associated mortality. We conducted a systematic review to evaluate the methodologies employed in studies to predict mortality among patients with sepsis. ⋯ ML models demonstrate a modest improvement in predicting sepsis-associated mortality. The certainty of these findings remains low due to the high risk of bias and significant heterogeneity. Studies should include comprehensive methodological details on calibration and hyperparameter selection, adopt a standardized definition of sepsis, and conduct multicenter prospective designs along with external validations.