Critical care : the official journal of the Critical Care Forum
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Evidence supports therapeutic drug monitoring of polymyxin B, but clinical data for establishing an area under the concentration-time curve across 24 h at steady state (AUCss,24 h) threshold are still limited. This study aimed to examine exposure-response/toxicity relationship for polymyxin B to establish an AUCss,24 h threshold in a real-world cohort of patients. ⋯ For critically ill patients, AUCss,24 h threshold of 50-100 mg h/L was associated with decreased nephrotoxicity while assuring clinical efficacy. Therapeutic drug monitoring is recommended for individualizing polymyxin B dosing.
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Multicenter Study
Delivery decision in pregnant women rescued by ECMO for severe ARDS: a retrospective multicenter cohort study.
Although rarely addressed in the literature, a key question in the care of critically pregnant women with severe acute respiratory distress syndrome (ARDS), especially at the time of extracorporeal membrane oxygenation (ECMO) decision, is whether delivery might substantially improve the mother's and child's conditions. This multicenter, retrospective cohort aims to report maternal and fetal short- and long-term outcomes of pregnant women with ECMO-rescued severe ARDS according to the timing of the delivery decision taken before or after ECMO cannulation. ⋯ Continuation of the pregnancy on ECMO support carries a significant risk of fetal death while improving prematurity-related morbidity in alive newborns with no difference in maternal outcomes. Decisions regarding timing, place, and mode of delivery should be taken and regularly (re)assess by a multidisciplinary team in experienced ECMO centers.
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The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that supervised deep machine learning could be used to identify previously unknown microcirculatory alterations, and combination with algorithmically quantified functional variables increases the model's performance to differentiate critically ill COVID-19 patients from healthy volunteers. ⋯ We successfully trained a deep learning-based model to differentiate critically ill COVID-19 patients from heathy volunteers in sublingual HVM image sequences. Internally validated, deep learning was superior to the algorithmic approach. However, combining the deep learning method with an algorithm-based approach to quantify the functional state of the microcirculation markedly increased the sensitivity and specificity as compared to either approach alone, and enabled successful external validation of the identification of the presence of microcirculatory alterations associated with COVID-19 status.