Trials
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As of December, 1st, 2020, coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2, resulted in more than 1 472 917 deaths worldwide and death toll is still increasing exponentially. Many COVID-19 infected people are asymptomatic or experience moderate symptoms and recover without medical intervention. However, older people and those with comorbid hypertension, diabetes, obesity, or heart disease are at higher risk of mortality. Because current therapeutic options for COVID-19 patients are limited specifically for this elderly population at risk, Biophytis is developing BIO101 (20-hydroxyecdysone, a Mas receptor activator) as a new treatment option for managing patients with SARS-CoV-2 infection at the severe stage. The angiotensin converting enzyme 2 (ACE2) serves as a receptor for SARS-CoV-2. Interaction between ACE2 and SARS-CoV2 spike protein seems to alter the function of ACE2, a key player in the renin-angiotensin system (RAS). The clinical picture of COVID-19 includes acute respiratory distress syndrome (ARDS), cardiomyopathy, multiorgan dysfunction and shock, all of which might result from an imbalance of the RAS. We propose that RAS balance could be restored in COVID-19 patients through MasR activation downstream of ACE2 activity, with 20-hydroxyecdysone (BIO101) a non-peptidic Mas receptor (MasR) activator. Indeed, MasR activation by 20-hydroxyecdysone harbours anti-inflammatory, anti-thrombotic, and anti-fibrotic properties. BIO101, a 97% pharmaceutical grade 20-hydroxyecdysone could then offer a new therapeutic option by improving the respiratory function and ultimately promoting survival in COVID-19 patients that develop severe forms of this devastating disease. Therefore, the objective of this COVA study is to evaluate the safety and efficacy of BIO101, whose active principle is 20-hydroxyecdysone, in COVID-19 patients with severe pneumonia.
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The aim of this study is to assess the effectiveness and safety of glucocorticoid infusion pulse therapy to improve the clinical outcomes of patients with COVID-19 pneumonia with elevated inflammatory biomarkers.
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Insomnia affects almost one in four military service members and veterans. The first-line recommended treatment for insomnia is cognitive-behavioral therapy for insomnia (CBTI). CBTI is typically delivered in-person or online over one-to-four sessions (brief versions) or five-to-eight sessions (standard versions) by a licensed doctoral or masters-level clinician with extensive training in behavioral sleep medicine. Despite its effectiveness, CBTI has limited scalability. Three main factors inhibit access to and delivery of CBTI including restricted availability of clinical expertise; rigid, resource-intensive treatment formats; and limited capacities for just-in-time monitoring and treatment personalization. Digital technologies offer a unique opportunity to overcome these challenges by providing scalable, personalized, resource-sensitive, adaptive, and cost-effective approaches for evidence-based insomnia treatment. ⋯ Digital health technologies and machine learning-assisted clinical decision support tools have substantial potential for scaling access to insomnia treatment. This can augment the scalability and cost-effectiveness of CBTI without compromising patient outcomes. Engaging providers, stakeholders, patients, and decision-makers is key in identifying strategies to support the deployment of digital health technologies that can promote quality care and result in clinically meaningful sleep improvements, positive systemic change, and enhanced readiness and health among service members.
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In this cluster-randomised controlled study (CoV-Surv Study), four different "active" SARS-CoV-2 testing strategies for general population surveillance are evaluated for their effectiveness in determining and predicting the prevalence of SARS-CoV-2 infections in a given population. In addition, the costs and cost-effectiveness of the four surveillance strategies will be assessed. Further, this trial is supplemented by a qualitative component to determine the acceptability of each strategy. Findings will inform the choice of the most effective, acceptable and affordable strategy for SARS-CoV-2 surveillance, with the most effective and cost-effective strategy becoming part of the local public health department's current routine health surveillance activities. Investigating its everyday performance will allow us to examine the strategy's applicability to real time prevalence prediction and the usefulness of the resulting information for local policy makers to implement countermeasures that effectively prevent future nationwide lockdowns. The authors would like to emphasize the importance and relevance of this study and its expected findings in the context of population-based disease surveillance, especially in respect to the current SARS-CoV-2 pandemic. In Germany, but also in many other countries, COVID-19 surveillance has so far largely relied on passive surveillance strategies that identify individuals with clinical symptoms, monitor those cases who then tested positive for the virus, followed by tracing of individuals in close contact to those positive cases. To achieve higher effectiveness in population surveillance and to reliably predict the course of an outbreak, screening and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic. To better control and manage the SARS-CoV-2 pandemic, current strategies therefore need to be complemented by an active surveillance of the wider population, i.e. routinely conducted testing and monitoring activities to identify and isolate infected individuals regardless of their clinical symptoms. Such active surveillance strategies will enable more effective prevention of the spread of the virus as they can generate more precise population-based parameters during a pandemic. This essential information will be required in order to determine the best strategic and targeted short-term countermeasures to limit infection spread locally.
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Acute kidney injury (AKI) is a common complication after thoracoscopic lobectomy in high-risk patients due to insufficient intraoperative infusion. Goal-directed fluid therapy (GDFT) is an individualized fluid infusion strategy; the fluid infusion strategy is adjusted according to the patient's fluid response. GDFT during operation can reduce the incidence of AKI after major surgery. Enhanced recovery after surgery (ERAS) protocol optimizes perioperative interventions to decrease the postoperative complications after surgery. In ERAS protocol of lobectomy, intraoperative restrictive fluid therapy is recommended. In this study, we will compare the effects of intraoperative GDFT with restrictive fluid therapy combined with an ERAS protocol on the incidence of AKI after thoracoscopic lobectomy in high-risk patients. ⋯ This is the first study to compare intraoperative GDFT with restrictive fluid therapy combined with an ERAS protocol on the incidence of AKI after thoracoscopic lobectomy in high-risk patients. The hypothesis is that the restrictive fluid therapy is noninferior to GDFT in reducing the incidence of AKI, but restrictive fluid therapy is simpler to apply than GDFT.