Anesthesiology
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Observational Study
Using Activity Trackers to Quantify Postpartum Ambulation: A Prospective Observational Study of Ambulation after Regional Anesthesia and Analgesia Interventions.
Early postoperative ambulation is associated with enhanced functional recovery, particularly in the postpartum population, but ambulation questionnaires are limited by recall bias. This observational study aims to objectively quantify ambulation after neuraxial anesthesia and analgesia for cesarean delivery and vaginal delivery, respectively, by using activity tracker technology. The hypothesis was that vaginal delivery is associated with greater ambulation during the first 24 h postdelivery, compared to cesarean delivery. ⋯ This study objectively demonstrates that vaginal delivery is associated with greater early ambulation and functional recovery compared to cesarean delivery. It also establishes the feasibility of using activity trackers to evaluate early postoperative ambulation after neuraxial anesthesia and analgesia.
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This study tests the hypothesis that sevoflurane blocks long-term potentiation only if it is present during the high-frequency stimulation that induces long-term potentiation. ⋯ Sevoflurane blocks long-term potentiation formation if present during the high-frequency stimulation; this blockage of long-term potentiation does not persist if sevoflurane is discontinued before the high-frequency stimulation. These results may explain why short periods of insufficient sevoflurane anesthesia may lead to recall of painful or traumatic events during surgery.
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The discrepancy between predicted effect-site concentration and measured bispectral index is problematic during intravenous anesthesia with target-controlled infusion of propofol and remifentanil. We hypothesized that bispectral index during total intravenous anesthesia would be more accurately predicted by a deep learning approach. ⋯ The deep learning model-predicted bispectral index during target-controlled infusion of propofol and remifentanil more accurately compared to the traditional model. The deep learning approach in anesthetic pharmacology seems promising because of its excellent performance and extensibility.
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When tracheal intubation is difficult or unachievable before surgery or during an emergent resuscitation, this is a critical safety event. Consensus algorithms and airway devices have been introduced in hopes of reducing such occurrences. However, evidence of improved safety in clinical practice related to their introduction is lacking. Therefore, we selected a large perioperative database spanning 2002 to 2015 to look for changes in annual rates of difficult and failed tracheal intubation. ⋯ An online visual overview is available for this article at http://links.lww.com/ALN/B635.