A machine learning algorithm for detecting abnormal patterns in continuous capnography and pulse oximetry monitoring.

Continuous capnography monitors patient ventilation but can be susceptible to artifact, resulting in alarm fatigue. Development of smart algorithms may facilitate accurate detection of abnormal ventilation, allowing intervention before patient deterioration. The objective of this analysis was to use machine learning (ML) to classify combined waveforms of continuous capnography and pulse oximetry as normal or abnormal.

Cost savings through continuous vital sign monitoring in the medical-surgical unit.

Objective: This study aimed to determine the potential cost-savings for implementing continuous vital sign monitoring in a hospital's medical-surgical units.

Methods: A cost-savings analysis was designed to calculate potential cost-savings for an average-sized U.S.

Identification of Sleep Medicine and Anesthesia Core Topics for Anesthesia Residency: A Modified Delphi Technique Survey.

Background: Sleep disorders affect up to 25% of the general population and are associated with increased risk of adverse perioperative events. The key sleep medicine topics that are most important for the practice of anesthesiology have not been well-defined. The objective of this study was to determine the high-priority sleep medicine topics that should be included in the education of anesthesia residents based on the insight of experts in the fields of anesthesia and sleep medicine.

Frequency and Temporal Distribution of Postoperative Respiratory Depressive Events.

Background: The frequency and temporal distribution of postoperative respiratory depression (RD) events are not completely understood. This study determined the temporal distribution and frequency of RD episodes in postsurgical patients continuously monitored by bedside capnography and pulse oximetry.

Methods: This was a post hoc study of a subset of postsurgical patients enrolled in The PRediction of Opioid-induced respiratory Depression In patients monitored by capnoGraphY (PRODIGY) trial from 2 sites in the United States.