Evaluation of a Respiratory Monitor in Surgical Patients With a BMI>35

Plain-language summary

This study proposes to evaluate the clinical applicability of the ExSpiron Respiratory Volume Monitor (RVM, ExSpiron™, Respiratory Motion, Inc.; Waltham, MA) in obese surgical patients undergoing general anesthesia. Previous work has demonstrated the ability of the ExSpiron monitor to provide non-invasive, real-time, continuous measurements of respiratory parameters such as tidal volume (TV), minute ventilation (MV) and respiratory rate (RR) mostly in normal weight patients but those studies did not specifically look at obese subjects. Respiratory depression, in the postoperative setting due to residual anesthetics and/or opioid administration, continues to be a significant cause of adverse outcomes. Obese patients are at increased risk for respiratory complications. Currently, there is no objective measure of early respiratory indicators for developing respiratory compromise. Current respiratory assessment in non-intubated patients relies on oximetry data and subjective clinical assessment. Pulse oximetry has been extremely helpful in recognizing oxygen desaturations but it is a late indicator of respiratory decline. There is no current device capable of giving real time ventilatory information such as tidal volume and minute ventilation of a patient that is not mechanically ventilated. The ExSpiron system utilizes an impedance based technology and proprietary algorithms (Respiratory Motion Inc.) to obtain these measurements. The study hypotheses are that the non-invasive, impedance-based RVM monitor will accurately reflect TV, RR and MV in obese surgical patients before induction of general anesthesia, during controlled ventilation and following extubation; that ExSpiron will accurately reflect the post-extubation respiratory status of the patient; and that apnea and hypopnea episodes in the recovery room as detected by the ExSpiron monitor are correlated with the individual risk for obstructive sleep apnea as determined by the STOP-Bang risk stratification.

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