Evaluation of Remote Monitoring Device for Monitoring Vital Parameters against Reference Standard: A Diagnostic Validation Study for COVID-19 Preparedness

Rapid systematic review of respiratory rate as a vital sign of clinical deterioration in COVID-19

OBJECTIVES

This meta-analysis aimed to establish a clinical evidence base for respiratory rate (RR) as a single predictor of early-onset COVID-19. The review also looked to determine the practical implementation of mobile respiratory rate measuring devices where information was available.

METHODS

We focused on domestic settings with older adults. Relevant studies were identified through MEDLINE, Embase, and CENTRAL databases. A snowballing method was also used. Articles published from the beginning of the COVID-19 pandemic (2019) until Feb 2022 were selected. Databases were searched for terms related to COVID-19 and respiratory rate measurements in domestic patients.

RESULTS

A total of 2,889 articles were screened for relevant content, of which 60 full-text publications were included. We compared the Odds Ratios and statistically significant results of both vital signs.

CONCLUSION

Multinational studies across dozens of countries have shown respiratory rate to have predictive accuracy in detecting COVID-19 deterioration. However, considerable variability is present in the data, making it harder to be sure about the effects. There is no meaningful difference in data quality in terms of variability (95% CI intervals) between vital signs as predictors of decline in COVID-19 patients. Contextual and economic factors will likely determine the choice of measurement used.

Detection and Monitoring of Viral Infections via Wearable Devices and Biometric Data

Mounting clinical evidence suggests that viral infections can lead to detectable changes in an individual's normal physiologic and behavioral metrics, including heart and respiration rates, heart rate variability, temperature, activity, and sleep prior to symptom onset, potentially even in asymptomatic individuals. While the ability of wearable devices to detect viral infections in a real-world setting has yet to be proven, multiple recent studies have established that individual, continuous data from a range of biometric monitoring technologies can be easily acquired and that through the use of machine learning techniques, physiological signals and warning signs can be identified. In this review, we highlight the existing knowledge base supporting the potential for widespread implementation of biometric data to address existing gaps in the diagnosis and treatment of viral illnesses, with a particular focus on the many important lessons learned from the coronavirus disease 2019 pandemic.

Biodegradable Molybdenum (Mo) and Tungsten (W) Devices: One Step Closer towards Fully-Transient Biomedical Implants

Close monitoring of vital physiological parameters is often key in following the evolution of certain medical conditions (e.g., diabetes, infections, post-operative status or post-traumatic injury). The allocation of trained medical staff and specialized equipment is, therefore, necessary and often translates into a clinical and economic burden on modern healthcare systems. As a growing field, transient electronics may establish fully bioresorbable medical devices capable of remote real-time monitoring of therapeutically relevant parameters. These devices could alert remote medical personnel in case of any anomaly and fully disintegrate in the body without a trace. Unfortunately, the need for a multitude of biodegradable electronic components (power supplies, wires, circuitry) in addition to the electrochemical biosensing interface has halted the arrival of fully bioresorbable electronically active medical devices. In recent years molybdenum (Mo) and tungsten (W) have drawn increasing attention as promising candidates for the fabrication of both energy-powered active (e.g., transistors and integrated circuits) and passive (e.g., resistors and capacitors) biodegradable electronic components. In this review, we discuss the latest Mo and W-based dissolvable devices for potential biomedical applications and how these soluble metals could pave the way towards next-generation fully transient implantable electronic systems.

Integration of mobile sensors in a telemedicine hospital system: remote-monitoring in COVID-19 patients

Aim

The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability.

Subject and methods

Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work.

Results

Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system's integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine.

Conclusion

Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique.

Hacking Covid-19 with Technology

The development, implementation and advancement of technology solutions aimed at combating the COVID-19 outbreak are rapidly taking shape in India. Governments, Venture Capitalists, Academic Institutions, Incubators, Start-ups, and businesses large and small are all doing their part to deploy new innovative solutions as quickly as possible. Various databases were searched to look for different advancements in technology during the current coronavirus pandemic. It is seen that on one end nonpharmacological measure (social distancing, self-isolation, clean hands, and face masks) are time-tested and low-tech ways to help mitigate the viral spread. On the other end, Science and technology sector constituting of data science, machine learning, rapid diagnostic tests, mobile-first telehealth and computational simulation systems for drug development, artificial intelligence, virtual collaboration, and data tracking are complex ways of using the technology that have strengthened our pandemic response.