MedTech News
Widely available nasal spray reduces risk of coronavirus infection by two-thirds, clinical study suggests
A research team at Saarland University has demonstrated in a clinical study that a widely used anti-allergy nasal spray containing the active ingredient azelastine can significantly reduce the risk of infection with the SARS-CoV-2 virus. The results of the placebo-controlled trial involving 450 healthy participants have now been published in JAMA Internal Medicine.
FDA grants 510(k) clearance to 4DMedical’s CT:VQ for respiratory diagnostics
The submission for CT:VQ was supported by a clinical validation package that spanned a variety of lung conditions.
Phraxis Announces First-Ever Commercial Case of EndoForce Anastomotic Connector
The technology is compatible with all PTFE grafts and was studied extensively in the company’s pivotal clinical trial
FDA clears Imperative Care Symphony thrombectomy system for pulmonary embolism
Imperative Care announced today that the FDA granted 510(k) clearance for its Symphony thrombectomy system to treat pulmonary embolism (PE).
Medtronic gets FDA nods for MiniMed 780G with Abbott Instinct sensor, expansion to type 2
Medtronic (NYSE: MDT)+
today announced major regulatory milestones for its MiniMed 780G automated insulin delivery system.
Combination of mini-camera and AI predicts recurrent heart attack
Measurements with a miniature camera inside the coronary arteries can accurately predict whether someone will suffer a recurrent heart attack. Until now, interpreting these images was so complex that only specialized laboratories could perform it.
Asthma chip reveals treatable subtype in 70% of patients
A simple blood test could make asthma treatment more precise, more effective—and potentially more affordable. Researchers from Karl Landsteiner University of Health Sciences (KL Krems) and the Medical University of Vienna (MedUni Vienna) have developed a molecular allergy chip that detects allergic asthma in individual patients.
Researchers train AI to diagnose heart failure in rural patients using low-tech electrocardiograms
Concerned about the ability of artificial intelligence models trained on data from urban demographics to make the right medical diagnoses for rural populations, West Virginia University computer scientists have developed several AI models that can identify signs of heart failure in patients from Appalachia.