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Obstructive sleep apnea poses as an anesthetic challenge, and it is a well-known risk factor for perioperative adverse events
This review summarizes and provides a comprehensive narrative synthesis of the current evidence on pediatric airway management during the COVID-19 pandemic.
Front-line staff routinely exposed to aerosol-generating procedures are at a particularly high risk of transmission of severe acute respiratory syndrome coronavirus. We aimed to assess the adequacy of respiratory protection provided by available N95/P2 masks to staff routinely exposed to aerosol-generating procedures.
Pediatric anesthesiology has been greatly impacted by COVID-19 in the delivery of care to patients and to the individual providers. With this study, we sought to survey pediatric centers and highlight the variations in care related to perioperative medicine during the COVID-19 pandemic, including the availability of protective equipment, the practice of pediatric anesthesia, and economic impact.
Obstructive sleep apnea is a risk factor for respiratory depression following opioid administration as well as opioid-induced hyperalgesia. Little is known on how obstructive sleep apnea status is associated with central ventilatory depression in pediatric surgical patients given a single dose of fentanyl.
The Perioperative Medicine team has developed a unique chewable tablet that gives the child the sensation of having a full stomach, without compromising their fasting regime.
Evidence regarding optimal management of the "Cannot Intubate, Cannot Oxygenate" (CICO) scenario in infants is scarce. When inserting a transtracheal cannula for front of neck access direct aspiration to confirm intratracheal location is standard practice.
Exposure to surgery and anesthesia in early childhood has been found to be associated with an increased risk of behavioral deficits. While the US Food and Drug Administration (FDA) has warned against prenatal exposure to anesthetic drugs, little clinical evidence exists to support this recommendation.
Britta Regli-von Ungern-Sternberg AM FAHMS MD, PhD, DEAA, FANZA Chair of Paediatric anaesthesia, University of Western Australia; Consultant
Processed electroencephalography (EEG) indices used to guide anesthetic dosing in adults are not validated in young infants. Raw EEG can be processed mathematically, yielding quantitative EEG parameters (qEEG). We hypothesized that machine learning combined with qEEG can accurately classify expired sevoflurane concentrations in young infants. Knowledge from this may contribute to development of future infant-specific EEG algorithms.