Articles: critical-illness.
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Journal of critical care · Feb 2024
Review Meta AnalysisThe effect of intravenous milrinone in adult critically ill patients: A meta-analysis of randomized clinical trials.
Milrinone is widely used for enhancing myocardial contractility, however, there is inadequate data to suggest whether it is preferable to other inotropic agents in critically ill patients. To observe the effect of milrinone on prognosis in adult critically ill patients, we conducted this meta-analysis. ⋯ The meta-analysis showed when compared with control group, although no significant reduction in mortality and the incidence of myocardial infarction was found in the milrinone group, the incidence of ventricular arrhythmia decreased significantly in patients with cardiac surgery. More randomized controlled trials are needed to determine the reliable and conclusive evidence for milrinone's effects.
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Critical care medicine · Feb 2024
Multicenter StudyFluid Intake in Critically Ill Patients: The "Save Useless Fluids For Intensive Resuscitation" Multicenter Prospective Cohort Study.
Patients at risk of adverse effects related to positive fluid balance could benefit from fluid intake optimization. Less attention is paid to nonresuscitation fluids. We aim to evaluate the heterogeneity of fluid intake at the initial phase of resuscitation. ⋯ Fluids indisputably required for body fluid homeostasis represent the minority of fluid intake during the 24 hours after ICU admission. Center effect is the strongest factor associated with the volume of fluids. Heterogeneity in practices suggests that optimal strategies for volume and goals of common fluids administration need to be developed.
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Critical care medicine · Feb 2024
Does Reinforcement Learning Improve Outcomes for Critically Ill Patients? A Systematic Review and Level-of-Readiness Assessment.
Reinforcement learning (RL) is a machine learning technique uniquely effective at sequential decision-making, which makes it potentially relevant to ICU treatment challenges. We set out to systematically review, assess level-of-readiness and meta-analyze the effect of RL on outcomes for critically ill patients. ⋯ In this first systematic review on the application of RL in intensive care medicine we found no studies that demonstrated improved patient outcomes from RL-based technologies. All studies reported that RL-agent policies outperformed clinician policies, but such assessments were all based on retrospective off-policy evaluation.