The COVID-19 pandemic has created unprecedented challenges for the U.S. healthcare system due to the mismatch between healthcare system capacity and patient demand. The healthcare industry has been a slow adopter of digital innovation due to the conventional belief that humans need to be at the center of every healthcare delivery task. In the setting of the COVID-19 pandemic, however, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and allow clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare implemented an automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.
Biosensor systems are increasingly promoted for use in behavioral interventions. Portable biosensors might offer advancement over self-report use and can provide improved opportunity for detection and intervention in patients undergoing drug treatment programs. Fifteen participants wore a biosensor wristband capable of detecting multiple physiologic markers of sympathetic nervous system (SNS) arousal for 30 days. Urine drug screening and drug use self-report were obtained twice per week. A parameter trajectory description method was applied to capture abrupt changes in magnitude of three measures of SNS activity: Electrodermal activity (EDA), skin temperature and motion. Drug use events detected by the biosensor were verified using a triad of parameters: the biosensor data, urine drug screens, and patient self-report of substance use. Twelve positive cocaine urine screens were identified. Thirteen self-reported episodes of cocaine use were recorded. Distinct episodes with biometric parameters consistent with cocaine use were identified on biosensor data. Eleven potential cocaine use episodes were identified by biosensors that were missed by both self-report and drug screening. Study participants found mobile biosensors to be acceptable, and compliance with the protocol was high. Episodes of cocaine use, as measured by supraphysiologic changes in biophysiometric parameters, were detected by analysis of biosensor data in instances when self-report or drug screening or both failed. Biosensors have substantial potential in detecting substance abuse, in understanding the context of use in real time, and in evaluating the efficacy of behavioral interventions for drug abuse.
Introduction Opioid analgesic use is a major cause of morbidity and mortality in the US, yet effective treatment programs have a limited ability to detect relapse. The utility of current drug detection methods is often restricted due to their retrospective and subjective nature. Wearable biosensors have the potential to improve detection of relapse by providing objective, real time physiologic data on opioid use that can be used by treating clinicians to augment behavioral interventions. Methods Thirty emergency department (ED) patients who were prescribed intravenous opioid medication for acute pain were recruited to wear a wristband biosensor. The biosensor measured electrodermal activity, skin temperature and locomotion data, which was recorded before and after intravenous opioid administration. Hilbert transform analyses combined with paired t-tests were used to compare the biosensor data A) within subjects, before and after administration of opioids; B) between subjects, based on hand dominance, gender, and opioid use history. Results Within subjects, a significant decrease in locomotion and increase in skin temperature were consistently detected by the biosensors after opioid administration. A significant change in electrodermal activity was not consistently detected. Between subjects, biometric changes varied with level of opioid use history (heavy vs. nonheavy users), but did not vary with gender or type of opioid. Specifically, heavy users demonstrated a greater decrease in short amplitude movements (i.e. fidgeting movements) compared to non-heavy users. Conclusion A wearable biosensor showed a consistent physiologic pattern after ED opioid administration and differences between patterns of heavy and non-heavy opioid users were noted. Potential applications of biosensors to drug addiction treatment and pain management should be studied further.
NF-kappaB activation in bronchial epithelial cells is important for the development of allergic airway inflammation, and may control the expression of critical mediators of allergic inflammation such as thymic stromal lymphopoietin (TSLP) and the chemokine CCL20. Members of the caspase recruitment domain (CARD) family of proteins are differentially expressed in tissue and help mediate NF-kappaB activity in response to numerous stimuli. Here we demonstrate that CARMA3 (CARD10) is specifically expressed in human airway epithelial cells, and that expression of CARMA3 in these cells leads to activation of NF-kappaB. CARMA3 has recently been shown to mediate NF-kappaB activation in embryonic fibroblasts after stimulation with lysophosphatidic acid (LPA), a bioactive lipid-mediator that is elevated in the lungs of individuals with asthma. Consistent with this, we demonstrate that stimulation of airway epithelial cells with LPA leads to increased expression of TSLP and CCL20. We then show that inhibition of CARMA3 activity in airway epithelial cells reduces LPA-mediated NF-kappaB activity and the production of TSLP and CCL20. In conclusion, these data demonstrate that LPA stimulates TSLP and CCL20 expression in bronchial epithelial cells via CARMA3-mediated NF-kappaB activation.
Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre -including this research content -immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
While the COVID-19 pandemic has generated many new challenges for emergency departments (EDs) across the country, it has also created potential opportunities for the improvement of emergency care delivery, both during the pandemic and going forward. Certainly, in some hospitals, the lack of built-in reserve capacity that had previously led to chronic overcrowding and ED boarding resulted in even more unsafe crowding conditions during surges of COVID-19 patients [1]. However, in other hospitals, like ours, a fundamental shift in operations allowed for markedly improved ED flow despite a markedly increased volume of high acuity patients. As EDs across the country continue to face decreased overall volumes (with the associated financial pressures that result), the actions of health system leaders and policy makers will determine whether we learn from the initial COVID-19 surge and improve our emergency care capabilities, or return to a status quo that could worsen emergency capacity even as we face a potential second COVID-19 wave.In the last decade, overcrowding has become almost ubiquitous in EDs across the United States with many documented negative effects on both patients and healthcare workers [2]. In the pre-COVID-19 era, providing high acuity care in hallway stretchers and chairs was the norm in our own ED, and patients routinely waited many hours before receiving inpatient beds. Despite treating more COVID-19 patients than any other hospital in a state with one of the highest numbers of cases nationally [3], patient flow through our ED and hospital in the past three months has, in fact, been better than at any time in recent memory. We intubated 3-4 times more patients than usual every day during peak COVID-19 volumes, and our total number of ED-tohospital admissions remained similar to pre-COVID-19 levels, yet patients needing inpatient beds received them almost immediately and our hallway stretchers remained largely empty. Brisk ED outflow allowed us to safely manage our COVID-19 patient volumes in a manner that would have been previously impossible.This marked improvement in ED flow was made possible by major changes in usual hospital operations, most importantly a large expansion in functional hospital capacity and bed-use flexibility. Through
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