Assessment of a Wearable Device for Minute Ventilation in Detecting Different States of Ventilation

Introduction: Minute ventilation (MV) and breathing status are valuable vital signs to measure in patients clinically such as in detecting opioid induced respiratory depression. However, there are few devices capable of continuously monitoring MV in an accurate fashion. RTM Vital Signs, LLC and TJU are developing a non-invasive wearable Tracheal Sound Sensor to determine if a device can accurately and continuously measure respiratory rate (RR), tidal volume (TV), MV, and changes in ventilation patterns based on sound recordings of breathing. Methods: Tracheal breathing sounds were recorded in six researchers using a prototype sensor placed on the skin above the sternal notch. Simultaneously, researcher’s RR and MV were recorded in minute long intervals using a pneumotach. Researchers were asked to mimic various breathing patterns by adjusting breathing rate and breathing depth. A variety of signal processing methods and algorithms were used to analyze the data to produce RR, TV, and breathing pattern estimates. Results: Researchers tolerated use of the sensor and breathing apparatus system without difficulty and data was successfully obtained. Initial signal processing and analysis methods applied to this data were able to accurately measure the respiratory rate (~ 98% sensitivity/specificity), and accurately characterize normal breathing from hyperventilation and hypoventilation (~ 98% sensitivity/specificity). The sensor’s algorithm estimated tidal volume with ± 100 ml accuracy compared with the commercial pneumotach. Discussion: Based on the results, a non-invasive wearable device could obtain accurate measures of RR and classify breathing patterns based solely on measurements of breathing sounds. Although the TV results were not as accurate as we expected, this may be due in part to systematic error from the pneumotach device used for the reference TV. With the satisfactory sensor and data acquisition system, future trials are planned in volunteers and hospitalized patients using this system with more accurate pneumotach devices

Detecting Different States of Ventilation with a Wearable Device through Minute Ventilation

Introduction: Detecting changes in respiration are essential to monitoring a patient’s vital signs. Few devices accomplish this in a non-invasive manner. We are developing a wearable Trachea Sound Sensor that measures respiratory rate (RR), tidal volume (TV), minute ventilation (MV = RR x TV). A prototypical Trachea Sound Sensor (TSS) was created and compared to a reference pneumotachometer. Both were used to record the sounds of breathing with research team members. Methods:The TSS recording device was tested on six research team members and breath sounds were recorded. Simultaneously, the member’s RR and MV was recorded using a calibrated pneumotachometer. The researchers were instructed to adjust their breathing rate and depth while intervals were recorded. Signal processing techniques were used to analyze and produce measurements of RR, TV, and characterize hyperventilatory or hypoventilatory states. Results: Based on the results, we found that it is possible to obtain accurate measures of RR and identify breathing patterns through the TSS. Signal processing and analysis calculated RR, states of hyperventilation and hypoventilation with 98% sensitivity and specificity. Results obtained for measuring TV were less accurate (±100 mL). Discussion: Our results suggest that it is viable to obtain accurate measures of RR and classify breathing sounds solely on measurements of breathing sounds from the TSS. The inaccuracy in TV measurements may be partly due to the systematic error from the pneumotachometer used. The prototypical TSS are suitable for upcoming NIH-funded clinical trials to test the TSS in volunteers and hospitalized patients

Patient Perceptions and Expectations About Postoperative Analgesia

Introduction Opioid overdose deaths have nearly quadrupled since 1999. Nearly 2 out of 3 persons being prescribed medications are prescribed an opioid. Physicians may be prescribing opioids for more than what is required for postoperative pain control, leading to increased risk for opioid abuse and addiction. Patient perceptions of perioperative pain medications are poorly understood. Objective This survey aims to understand patient expectations of perioperative analgesics. Methods Following IRB approval, patients 18 years of age or older, were given a 13-question survey prior to their surgery at Thomas Jefferson University Hospital, to evaluate the perception of pain medications, medication efficacy, and risk profile. For this analysis, 503 patients were surveyed and only 5 questions were used. Results Overall, 100% of patients believed they would receive analgesics after surgery, with 76% of patients expecting opioids. Additionally, 94% of patients expecting to receive postoperative opioid prescriptions believed opioids would be effective in controlling their pain. Furthermore, 67.5% of patients not expecting to receive opioids postoperatively still believed opioids would be superior to non-opioid medications. Conclusion Patients expected to experience pain after surgery and be prescribed analgesics. Patients anticipated receiving analgesics they perceived most effective, which was most often an opioid. The perception of superior efficacy of opioids is worthy of further study as this is inconsistent with the literature, and education may be needed to bridge this gap. As the opioid crisis continues, cultural attitudes toward pain and medications will play a central role in reducing the prevalence of opioids in healthcare and society

Outcomes Reporting in Regional Anesthesia Patients: A Comparison of Manual Phone Calls Versus Automated Phone App Messaging

Automation of patient follow-up via mobile phone apps have the potential to save time for physicians, standardize responses from patients, and increase the patient response rate. Studies that assess the effectiveness of mobile phone-based surveys have been favorable, with completion rates of about 60% in the surgical population. The impact of mobile phone-based patient management in anesthesia deserves further study. This study examines the follow-up success rates of (1) manual phone calls (the current standard of care) vs. (2) automated patient outreach (APO) in patients who receive a regional anesthesia block procedure. As part of normal follow up, anesthesia team members contact surgical patients who have received a regional nerve block to assess for potential side effects or complications. This study is comparing two different modes patient outreach. Patients will be randomized to receive either a manual phone call from a member of the anesthesia care team or the APO treatment. Of patients randomized to the APO treatment, automated messages will request the patient to download the “JeffAnesthesia” app and answer post-care surveys. Both treatment arms will contain the same survey questions. The primary endpoint, the follow-up success rate defined by a patient completing a set of survey questions, will be compared. Secondary endpoints, such as patient satisfaction, will also be recorded from the survey responses. Patient enrollment is ongoing, and data to formulate preliminary results is forthcoming to understand the impact of outreach modalities on patient outcomes reporting and satisfaction