Anesthesiology
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Postoperative hemodynamic deterioration among cardiac surgical patients can indicate or lead to adverse outcomes. Whereas prediction models for such events using electronic health records or physiologic waveform data are previously described, their combined value remains incompletely defined. The authors hypothesized that models incorporating electronic health record and processed waveform signal data (electrocardiogram lead II, pulse plethysmography, arterial catheter tracing) would yield improved performance versus either modality alone. ⋯ Clinical deterioration prediction models combining electronic health record data and waveform data were superior to either modality alone, and performance of combined models was primarily driven by waveform data. Decreased performance of prediction models during temporal validation may be explained by data set shift, a core challenge of healthcare prediction modeling.
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Increasing wildfire activity worldwide has led to exposure to poor air quality and numerous detrimental health impacts. This study hypothesized an association between exposure to poor air quality from wildfire smoke and adverse respiratory events under general anesthesia in pediatric patients. ⋯ Pediatric patients with underlying risk factors for respiratory complications under general anesthesia had a greater incidence of adverse respiratory events during periods of unhealthy air quality caused by wildfire smoke. In this vulnerable patient population, postponing elective anesthetics should be considered when air quality is poor.