Researchers report advances in materials and designs for skin-integrated devices capable of measuring acoustic signatures.

Advances in ultrathin, skin-like electronics lead to wearable devices for continuous, noninvasive blood flow monitoring.

Artificial intelligence (AI) has the potential to improve diagnostic accuracy. Yet people are often reluctant to trust automated systems, and some patient populations may be particularly distrusting. We sought to determine how diverse patient populations feel about the use of AI diagnostic tools, and whether framing and informing the choice affects uptake. To construct and pretest our materials, we conducted structured interviews with a diverse set of actual patients. We then conducted a pre-registered (osf.io/9y26x), randomized, blinded survey experiment in factorial design. A survey firm provided n = 2675 responses, oversampling minoritized populations. Clinical vignettes were randomly manipulated in eight variables with two levels each: disease severity (leukemia versus sleep apnea), whether AI is proven more accurate than human specialists, whether the AI clinic is personalized to the patient through listening and/or tailoring, whether the AI clinic avoids racial and/or financial biases, whether the Primary Care Physician (PCP) promises to explain and incorporate the advice, and whether the PCP nudges the patient towards AI as the established, recommended, and easy choice. Our main outcome measure was selection of AI clinic or human physician specialist clinic (binary, “AI uptake”). We found that with weighting representative to the U.S. population, respondents were almost evenly split (52.9% chose human doctor and 47.1% chose AI clinic). In unweighted experimental contrasts of respondents who met pre-registered criteria for engagement, a PCP’s explanation that AI has proven superior accuracy increased uptake (OR = 1.48, CI 1.24–1.77,p< .001), as did a PCP’s nudge towards AI as the established choice (OR = 1.25, CI: 1.05–1.50,p= .013), as did reassurance that the AI clinic had trained counselors to listen to the patient’s unique perspectives (OR = 1.27, CI: 1.07–1.52,p =.008). Disease severity (leukemia versus sleep apnea) and other manipulations did not affect AI uptake significantly. Compared to White respondents, Black respondents selected AI less often (OR = .73, CI: .55-.96,p= .023) and Native Americans selected it more often (OR: 1.37, CI: 1.01–1.87,p= .041). Older respondents were less likely to choose AI (OR: .99, CI: .987-.999,p= .03), as were those who identified as politically conservative (OR: .65, CI: .52-.81,p< .001) or viewed religion as important (OR: .64, CI: .52-.77,p< .001). For each unit increase in education, the odds are 1.10 greater for selecting an AI provider (OR: 1.10, CI: 1.03–1.18,p= .004). While many patients appear resistant to the use of AI, accuracy information, nudges and a listening patient experience may help increase acceptance. To ensure that the benefits of AI are secured in clinical practice, future research on best methods of physician incorporation and patient decision making is required.

As coronavirus disease 2019 (COVID-19) cases surge worldwide, an urgent need exists to enhance our understanding of the role of extracorporeal membrane oxygenation (ECMO) in the management of severely ill patients with COVID-19 who develop acute respiratory and cardiac compromise refractory to conventional therapy. The purpose of this manuscript is to review our initial clinical experience in 32 patients with confirmed COVID-19 treated with ECMO. A multi-institutional registry and database was created and utilized to assess all patients who were supported with ECMO provided by SpecialtyCare. Data captured included patient characteristics, pre-COVID-19 risk factors and comorbidities, confirmation of COVID-19 diagnosis, features of ECMO support, specific medications utilized to treat COVID-19, and short-term outcomes through hospital discharge. This analysis includes all of our patients with COVID-19 supported with ECMO, with an analytic window starting March 17, 2020, when our first COVID-19 patient was placed on ECMO, and ending April 9, 2020. During the 24 days of this study, 32 consecutive patients with COVID-19 were placed on ECMO at nine different hospitals. As of the time of analysis, 17 remain on ECMO, 10 died before or shortly after decannulation, and five are alive and extubated after removal from ECMO, with one of these five discharged from the hospital. Adjunctive medication in the surviving patients while on ECMO was as follows: four of five survivors received intravenous steroids, three of five survivors received antiviral medications (Remdesivir), two of five survivors were treated with anti-interleukin-6-receptor monoclonal antibodies (Tocilizumab or Sarilumab), and one of five survivors received hydroxychloroquine. Analysis of these 32 COVID-19 patients with severe pulmonary compromise supported with ECMO suggests that ECMO may play a useful role in salvaging select critically ill patients with COVID-19. Additional patient experience and associated clinical and laboratory data must be obtained to further define the optimal role of ECMO in patients with COVID-19 and acute respiratory distress syndrome (ARDS). These initial data may provide useful information to help define the best strategies to care for these challenging patients and may also provide a framework for much-needed future research about the use of ECMO to treat patients with COVID-19.