ABSTRACT
INTRODUCTION: A recent finding of a deep venous thrombosis during spaceflight has prompted the need to clarify mechanisms and risks of venous thromboembolism (VTE). In turn, mitigation countermeasures, diagnostic modalities, and treatment options must be explored. The objective of this review was to synthesize current evidence on VTE in spaceflight.METHODS: A literature review was performed from inception to April 2023 pertaining to VTE in the context of spaceflight or ground-based analogs with human participants. PubMed was searched for papers written in English using the terms "spaceflight" or "weightlessness" and "thrombotic" or "embolism" or "thromboembolism" in "venous" or "veins". Papers using cellular or animal models were excluded.RESULTS: There were 63 papers captured; 7 original scientific studies, 3 narrative reviews, 2 systematic reviews, and 3 commentaries discussed VTE in spaceflight. Reference lists were screened. Important themes included: altered venous hemodynamics, increased fibrinogen and coagulation markers, hypoalbuminemia, and immune dysfunction. Additional risk factors may be seen in women, such as the use of oral contraceptives.DISCUSSION: Venous stasis and decreased shear stress secondary to fluid shifts may induce inflammatory changes in the venous system, resulting in endothelial damage and upregulation of the coagulation cascade. Additionally, women in space are subject to physiological factors increasing their VTE risk, such as the use of oral contraceptives, inducing increased blood viscosity and hypoalbuminemia. Efforts should also be placed in optimizing sensitivity and specificity of imaging markers, payload, and training ability, notably the use of vector flow imaging, and improving point-of-testing biomarkers, such as albumin and p-selectin.Levasseur S, Purvis N, Trozzo S, Chung SH, Ades M, Drudi LM. Venous thromboembolism in exploration class human spaceflight. Aerosp Med Hum Perform. 2024; 95(1):45-53.
Subject(s)
Hypoalbuminemia , Space Flight , Thrombosis , Venous Thromboembolism , Animals , Humans , Female , Venous Thromboembolism/chemically induced , Hypoalbuminemia/chemically induced , Contraceptives, Oral/adverse effects , Thrombosis/chemically inducedABSTRACT
[This corrects the article DOI: 10.2196/41209.].
ABSTRACT
BACKGROUND: Voice-assisted artificial intelligence-based systems may streamline clinical care among patients with heart failure (HF) and caregivers; however, randomized clinical trials are needed. We evaluated the potential for Amazon Alexa (Alexa), a voice-assisted artificial intelligence-based system, to conduct screening for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a HF clinic. METHODS AND RESULTS: We enrolled 52 participants (patients and caregivers) from a HF clinic who were randomly assigned with a subsequent cross-over to receive a SARS-CoV-2 screening questionnaire via Alexa or health care personnel. The primary outcome was overall response concordance, as measured by the percentage of agreement and unweighted kappa scores between groups. A postscreening survey evaluated comfort with using the artificial intelligence-based device. In total, 36 participants (69%) were male, the median age was 51 years (range 34-65 years) years and 36 (69%) were English speaking. Twenty-one participants (40%) were patients with HF. For the primary outcome, there were no statistical differences between the groups: Alexa-research coordinator group 96.9% agreement and unweighted kappa score of 0.92 (95% confidence interval 0.84-1.00) vs research coordinator-Alexa group 98.5% agreement and unweighted kappa score of 0.95 (95% confidence interval 0.88-1.00) (P value for all comparisons > .05). Overall, 87% of participants rated their screening experience as good or outstanding. CONCLUSIONS: Alexa demonstrated comparable performance to a health care professional for SARS-CoV-2 screening in a group of patients with HF and caregivers and may represent an attractive approach to symptom screening in this population. Future studies evaluating such technologies for other uses among patients with HF and caregivers are warranted. NCT04508972.
ABSTRACT
BACKGROUND: The COVID-19 pandemic has disrupted the health care system, limiting health care resources such as the availability of health care professionals, patient monitoring, contact tracing, and continuous surveillance. As a result of this significant burden, digital tools have become an important asset in increasing the efficiency of patient care delivery. Digital tools can help support health care institutions by tracking transmission of the virus, aiding in the screening process, and providing telemedicine support. However, digital health tools face challenges associated with barriers to accessibility, efficiency, and privacy-related ethical issues. OBJECTIVE: This paper describes the study design of an open-label, noninterventional, crossover, randomized controlled trial aimed at assessing whether interactive voice response systems can screen for SARS-CoV-2 in patients as accurately as standard screening done by people. The study aims to assess the concordance and interrater reliability of symptom screening done by Amazon Alexa compared to manual screening done by research coordinators. The perceived level of comfort of patients when interacting with voice response systems and their personal experience will also be evaluated. METHODS: A total of 52 patients visiting the heart failure clinic at the Royal Victoria Hospital of the McGill University Health Center, in Montreal, Quebec, will be recruited. Patients will be randomly assigned to first be screened for symptoms of SARS-CoV-2 either digitally, by Amazon Alexa, or manually, by the research coordinator. Participants will subsequently be crossed over and screened either digitally or manually. The clinical setup includes an Amazon Echo Show, a tablet, and an uninterrupted power supply mounted on a mobile cart. The primary end point will be the interrater reliability on the accuracy of randomized screening data performed by Amazon Alexa versus research coordinators. The secondary end point will be the perceived level of comfort and app engagement of patients as assessed using 5-point Likert scales and binary mode responses. RESULTS: Data collection started in May 2021 and is expected to be completed in fall 2022. Data analysis is expected to be completed in early 2023. CONCLUSIONS: The use of voice-based assistants could improve the provision of health services and reduce the burden on health care personnel. Demonstrating a high interrater reliability between Amazon Alexa and health care coordinators may serve future digital tools to streamline the screening and delivery of care in the context of other conditions and clinical settings. The COVID-19 pandemic occurs during the first digital era using digital tools such as Amazon Alexa for disease screening, and it represents an opportunity to implement such technology in health care institutions in the long term. TRIAL REGISTRATION: ClinicalTrials.gov NCT04508972; https://clinicaltrials.gov/ct2/show/NCT04508972. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/41209.
