In order to prevent in-hospital transmission and potential complications related to SARS-CoV-2 in the perioperative patient, most healthcare institutions require preoperative testing for SARS-CoV-2 prior to proceeding with elective surgery. The Centers for Disease Control and Prevention (CDC) recommends a time and symptom-based duration of isolation for the presumed infectious period. The guidance to avoid retesting of asymptomatic patients in the 90 days following a positive reverse transcription polymerase chain reaction (RT-PCR) test is because of the possibility of detection of non-infectious viral shedding. When to reschedule asymptomatic patients who test RT-PCR positive for SARS-CoV-2 preoperatively is of considerable debate, both from the perspective of ensuring a patient's full preoperative fitness, as well as reducing the risk of viral transmission within the hospital. We describe the novel perioperative use of a strand-specific assay to detect minus strand ribonucleic acid (RNA) in a clinical decision-making algorithm to determine optimal timing of elective surgery after a patient tests RT-PCR positive for SARS-CoV-2. This is the first description in the literature of an attempt to further stratify patients who repeatedly test positive for SARS-CoV-2 into infectious versus noninfectious for perioperative planning.
Background: Augmented reality (AR) and eye tracking are promising adjuncts for medical simulation, but they have remained distinct tools. The recently developed Chariot Augmented Reality Medical (CHARM) Simulator combines AR medical simulation with eye tracking. We present a novel approach to applying eye tracking within an AR simulation to assess anesthesiologists during an AR pediatric life support simulation. The primary aim was to explore clinician performance in the simulation. Secondary outcomes explored eye tracking as a measure of shockable rhythm recognition and participant satisfaction.Methods: Anesthesiology residents, pediatric anesthesiology fellows, and attending pediatric anesthesiologists were recruited. Using CHARM, they participated in a pediatric crisis simulation. Performance was scored using the Anesthesia-centric Pediatric Advanced Life Support (A-PALS) scoring instrument, and eye tracking data were analyzed. The Simulation Design Scale measured participant satisfaction.Results: Nine each of residents, fellows, and attendings participated for a total of 27. We were able to successfully progress participants through the AR simulation as demonstrated by typical A-PALS performance scores. We observed no differences in performance across training levels. Eye tracking data successfully allowed comparisons of time to rhythm recognition across training levels, revealing no differences. Finally, simulation satisfaction was high across all participants.Conclusions: While the agreement between A-PALS score and gaze patterns is promising, further research is needed to fully demonstrate the use of AR eye tracking for medical training and assessment. Physicians of multiple training levels were satisfied with the technology.
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