Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation
Li et al.
The finding, in our words
A wireless, battery-free pathogenic infection diagnosis system achieved 100% accuracy for diagnosing SARS-CoV-2 infection and 92% accuracy for evaluating symptom severity in 42 participants using blow and breath samples within 110 s and 350 s respectively, offering rapid decentralised diagnostics for respiratory infections.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
This review establishes that microsampling across blood, saliva, urine and stool matrices offers validated workflows and regulatory recognition for human biomonitoring comparable to conventional methods. It finds that these decentralised approaches enhance participant acceptability and enable screening in remote or low-resource settings.
A direct-to-participant, multichannel recruitment strategy enrolled 34,244 older adults into a virtual trial testing an Apple Watch based heart health programme with electrocardiogram and irregular rhythm notification features, achieving broad geographic and gender diversity but under-representing non-White ethnic groups.
In progressive multiple sclerosis, higher serum neurofilament light chain levels were associated with reduced daily step counts from wearables, while higher step counts were linked to lower sNfL. A ten percent increase in steps corresponded to a 0.015 decrease in sNfL z-score, suggesting rising sNfL may predict subsequent mobility decline.
Wearable-derived digital biomarkers have been accepted by regulatory agencies as endpoints in clinical trials for Duchenne muscular dystrophy, showing their potential to support decentralised diagnostics through patient-centric monitoring. This matters because it enables more sensitive and continuous assessment of disease progression outside clinical settings.
This study found that a decentralised approach using home-based sleep apnoea screening, heart rhythm monitoring and activity tracking in patients with atrial fibrillation is feasible, with high data completeness and low drop-out rates. The results support the use of patient-centric digital tools in decentralised trials for chronic cardiac conditions.