Realize, Analyze, Engage (RAE): A Digital Tool to Support Recovery from Substance Use Disorder

Background: Substance use disorders are a highly prevalent group of chronic diseases with devastating individual and public health consequences. Current treatment strategies suffer from high rates of relapse, or return to drug use, and novel solutions are desperately needed. Realize Analyze Engage (RAE) is a digital, mHealth intervention that focusses on real time, objective detection of high-risk events (stress and drug craving) to deploy just-in-time supportive interventions. The present study aims to (1) evaluate the accuracy and usability of the RAE system and (2) evaluate the impact of RAE on patient centered outcomes. Methods: The first phase of the study will be an observational trial of N = 50 participants in outpatient treatment for SUD using the RAE system for 30 days. Accuracy of craving and stress detection algorithms will be evaluated, and usability of RAE will be explored via semi-structured interviews with participants and focus groups with SUD treatment clinicians. The second phase of the study will be a randomized controlled trial of RAE vs usual care to evaluate rates of return to use, retention in treatment, and quality of life. Anticipated findings and future directions: The RAE platform is a potentially powerful tool to de-escalate stress and craving outside of the clinical milieu, and to connect with a support system needed most. RAE also aims to provide clinicians with actionable insight to understand patients\u27 level of risk, and contextual clues for their triggers in order to provide more personalized recovery support

Contactless Monitoring System Versus Gold Standard for Respiratory Rate Monitoring in Emergency Department Patients: Pilot Comparison Study

Background: Respiratory rate is a crucial indicator of disease severity yet is the most neglected vital sign. Subtle changes in respiratory rate may be the first sign of clinical deterioration in a variety of disease states. Current methods of respiratory rate monitoring are labor-intensive and sensitive to motion artifacts, which often leads to inaccurate readings or underreporting; therefore, new methods of respiratory monitoring are needed. The PulsON 440 (P440; TSDR Ultra Wideband Radios and Radars) radar module is a contactless sensor that uses an ultrawideband impulse radar to detect respiratory rate. It has previously demonstrated accuracy in a laboratory setting and may be a useful alternative for contactless respiratory monitoring in clinical settings; however, it has not yet been validated in a clinical setting. Objective: The goal of this study was to (1) compare the P440 radar module to gold standard manual respiratory rate monitoring and standard of care telemetry respiratory monitoring through transthoracic impedance plethysmography and (2) compare the P440 radar to gold standard measurements of respiratory rate in subgroups based on sex and disease state. Methods: This was a pilot study of adults aged 18 years or older being monitored in the emergency department. Participants were monitored with the P440 radar module for 2 hours and had gold standard (manual respiratory counting) and standard of care (telemetry) respiratory rates recorded at 15-minute intervals during that time. Respiratory rates between the P440, gold standard, and standard telemetry were compared using Bland-Altman plots and intraclass correlation coefficients. Results: A total of 14 participants were enrolled in the study. The P440 and gold standard Bland-Altman analysis showed a bias of –0.76 (–11.16 to 9.65) and an intraclass correlation coefficient of 0.38 (95% CI 0.06-0.60). The P440 and gold standard had the best agreement at normal physiologic respiratory rates. There was no change in agreement between the P440 and the gold standard when grouped by admitting diagnosis or sex. Conclusions: Although the P440 did not have statistically significant agreement with gold standard respiratory rate monitoring, it did show a trend of increased agreement in the normal physiologic range, overestimating at low respiratory rates, and underestimating at high respiratory rates. This trend is important for adjusting future models to be able to accurately detect respiratory rates. Once validated, the contactless respiratory monitor provides a unique solution for monitoring patients in a variety of settings

Nobody Wants to Be Narcan\u27d: A Pilot Qualitative Analysis of Drug Users\u27 Perspectives on Naloxone

INTRODUCTION: Bystander naloxone distribution is an important component of public health initiatives to decrease opioid-related deaths. While there is evidence supporting naloxone distribution programs, the effects of increasing naloxone availability on the behavior of people who use drugs have not been adequately delineated. In this study we sought to 1) evaluate whether individuals\u27 drug use patterns have changed due to naloxone availability; and 2) explore individuals\u27 knowledge of, access to, experiences with, and perceptions of naloxone. METHODS: We conducted a pilot study of adults presenting to the emergency department whose medical history included non-medical opioid use. Semi-structured interviews were conducted with participants and thematic analysis was used to code and analyze interview transcripts. RESULTS: Ten participants completed the study. All were aware of naloxone by brand name (Narcan) and had been trained in its use, and all but one had either currently or previously possessed a kit. Barriers to naloxone administration included fear of legal repercussions, not having it available, and a desire to avoid interrupting another user\u27s high. Of the eight participants who reported being revived with naloxone at least once during their lifetime, all described experiencing a noxious physical response and expressed a desire to avoid receiving it again. Furthermore, participants did not report increasing their use of opioids when naloxone was available. CONCLUSIONS: Participants were accepting of and knowledgeable about naloxone, and were willing to administer naloxone to save a life. Participants tended to use opioids more cautiously when naloxone was present due to fears of experiencing precipitated withdrawal. This study provides preliminary evidence countering the unsubstantiated narrative that increased naloxone availability begets more high-risk opioid use and further supports increasing naloxone access

Syndromic Surveillance of Population-Level COVID-19 Burden With Cough Monitoring in a Hospital Emergency Waiting Room

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital\u27s electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value \u3c 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Aggregated cough counts and other data, such as people density collected from our platform, can be utilized to predict COVID-19 patient visits related metrics in a hospital waiting room, and SHAP and Gini feature importance-based metrics showed cough count as the important feature for these prediction models. Furthermore, we have shown that predictions based on cough counting outperform models based on fever detection (e.g., temperatures over 39°C), which require more intrusive engagement with the population. Our findings highlight that incorporating cough-counting based signals into syndromic surveillance systems can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics

Syndromic surveillance of population-level COVID-19 burden with cough monitoring in a hospital emergency waiting room

Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Aggregated cough counts and other data, such as people density collected from our platform, can be utilized to predict COVID-19 patient visits related metrics in a hospital waiting room, and SHAP and Gini feature importance-based metrics showed cough count as the important feature for these prediction models. Furthermore, we have shown that predictions based on cough counting outperform models based on fever detection (e.g., temperatures over 39°C), which require more intrusive engagement with the population. Our findings highlight that incorporating cough-counting based signals into syndromic surveillance systems can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics

Here Today, Gone Tomorrow…and Back Again? A Review of Herbal Marijuana Alternatives (K2, Spice), Synthetic Cathinones (Bath Salts), Kratom, Salvia divinorum, Methoxetamine, and Piperazines

Despite their widespread Internet availability and use, many of the new drugs of abuse remain unfamiliar to health care providers. The herbal marijuana alternatives, like K2 or Spice, are a group of herbal blends that contain a mixture of plant matter in addition to chemical grade synthetic cannabinoids. The synthetic cathinones, commonly called bath salts, have resulted in nationwide emergency department visits for severe agitation, sympathomimetic toxicity, and death. Kratom, a plant product derived from Mitragyna speciosa Korth, has opioid-like effects, and has been used for the treatment of chronic pain and amelioration of opioid-withdrawal symptoms. Salvia divinorum is a hallucinogen with unique pharmacology that has therapeutic potential but has been banned in many states due to concerns regarding its psychiatric effects. Methoxetamine has recently become available via the Internet and is marked as legal ketamine. Moreover, the piperazine derivatives, a class of amphetamine-like compounds that includes BZP and TMFPP, are making a resurgence as legal Ecstasy. These psychoactives are available via the Internet, frequently legal, and often perceived as safe by the public. Unfortunately, these drugs often have adverse effects, which range from minimal to life-threatening. Health care providers must be familiar with these important new classes of drugs. This paper discusses the background, pharmacology, clinical effects, detection, and management of synthetic cannabinoid, synthetic cathinone, methoxetamine, and piperazine exposures

Leveraging digital tools to support recovery from substance use disorder during the COVID-19 pandemic response

Treatment for substance use disorder (SUD) during the COVID-19 pandemic poses unique challenges, both due to direct effects from the illness, and indirect effects from the physical measures needed to flatten the curve. Stress, isolation, lack of structure, limited access to physical and mental health care, and changes in treatment paradigms all increase risk of return to drug use events and pose barriers to recovery for people with SUDs. The pandemic has forced treatment providers and facilities to rapidly adapt to address these threats while redesigning their structure to accommodate physical distancing regulations. Digital health interventions can function without the need for physical proximity. Clinicians can use digital health intervention, such as telehealth, wearables, mobile applications, and other remote monitoring devices, to convert in-person care to remote-based care, and they can leverage these tools to address some of the pandemic-specific challenges to treatment. The current pandemic provides the opportunity to rapidly explore the advantages and limitations of these technologies in the care of individuals with SUD

OpiTrack: A Wearable-based Clinical Opioid Use Tracker with Temporal Convolutional Attention Networks

Opioid use disorder is a medical condition with major social and economic consequences. While ubiquitous physiological sensing technologies have been widely adopted and extensively used to monitor day-to-day activities and deliver targeted interventions to improve human health, the use of these technologies to detect drug use in natural environments has been largely underexplored. The long-term goal of our work is to develop a mobile technology system that can identify high-risk opioid-related events (i.e., development of tolerance in the setting of prescription opioid use, return-to-use events in the setting of opioid use disorder) and deploy just-in-time interventions to mitigate the risk of overdose morbidity and mortality. In the current paper, we take an initial step by asking a crucial question: Can opioid use be detected using physiological signals obtained from a wrist-mounted sensor? Thirty-six individuals who were admitted to the hospital for an acute painful condition and received opioid analgesics as part of their clinical care were enrolled. Subjects wore a noninvasive wrist sensor during this time (1-14 days) that continuously measured physiological signals (heart rate, skin temperature, accelerometry, electrodermal activity, and interbeat interval). We collected a total of 2070 hours ( approximately 86 days) of physiological data and observed a total of 339 opioid administrations. Our results are encouraging and show that using a Channel-Temporal Attention TCN (CTA-TCN) model, we can detect an opioid administration in a time-window with an F1-score of 0.80, a specificity of 0.77, sensitivity of 0.80, and an AUC of 0.77. We also predict the exact moment of administration in this time-window with a normalized mean absolute error of 8.6% and R (2) coefficient of 0.85

Potential uses of naltrexone in emergency department patients with opioid use disorder

Introduction: Despite widespread recognition of the opioid crisis, opioid overdose remains a common reason for Emergency Department (ED) utilization. Treatment for these patients after stabilization often involves the provision of information for outpatient treatment options. Ideally, an ED visit for overdose would present an opportunity to start treatment for opioid use disorder (OUD) immediately. Although widely recognized as effective, opioid agonist therapy with methadone and buprenorphine commonly referred to as medication-assisted therapy but more correctly as medication for addiction treatment (MAT), can be difficult to access even for motivated individuals due to shortages of prescribers and treatment programs. Moreover, opioid agonist therapy may not be appropriate for all patients, as many patients who present after overdose are not opioid dependent. More treatment options are required to successfully match patients with diverse needs to an optimal treatment plan in order to avoid relapse. Naltrexone, a long-acting opioid antagonist, available orally and as a monthly extended-release intramuscular injection, may represent another treatment option. Methods: We conducted a literature search of MEDLINE and PubMed. We aimed to capture references related to naltrexone and is use as MAT for OUD, as well as manuscripts that discussed naltrexone in comparison toother agents used for MAT, opioid detoxification, and naltrexone metabolism. Our initial search logic returned a total of 618 articles. Following individual evaluation for relevance, we selected 65 for in-depthreview. Manuscripts meeting criteria were examined for citations meriting further review, leading to the addition of 30 manuscripts Conclusions: Here, we review the pharmacology of naltrexone as it relates to OUD, its history of use, and highlight recent studies and new approaches for use of the drug as MAT including its potential initiation after ED visit for opioid overdose

Federal Funding in Emergency Medicine: Demographics and Perspectives of Awardees

Introduction: Emergency physicians face multiple challenges to obtaining federal funding. The objective of this investigation was to describe the demographics of federally-funded emergency physicians and identify key challenges in obtaining funding.Methods: We conducted a retrospective database search of the National Institutes of Health (NIH) Research Portfolio Online Reporting Tool (NIH RePORTER) to collect data regarding the distribution and characteristics of federally-funded grants awarded to emergency medicine (EM) principal investigators between 2010-2017.  An electronic survey was then administered to the identified investigators to obtain additional demographic data, and information regarding their career paths, research environment, and perceived barriers to obtaining federal funding.Results: We identified 219, corresponding to 51 unique, mentored career development awardees and 105 independent investigators. Sixty-two percent of investigators responded to the electronic survey. Awardees were predominantly White males, although a larger portion of the mentored awardee group was female. Greater than half of respondents reported their mentor to be outside of the field of EM. The most common awarding institution was the National Heart Lung and Blood Institute. Respondents identified barriers in finding adequate mentorship, time to gather preliminary data, and the quality of administrative support.Conclusion: The last five years have showed a trend toward increasing grants awarded to EM investigators; however, we identified several barriers to funding. Initiatives geared toward support and mentorship of junior faculty, particularly to females, minorities, and those in less heavily funded areas of the country are warranted