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Diabetes app reduces health care use, hospitalizations: Patients with type 2 diabetes who used the Dario Diabetes Solution had lower all-cause health care resource utilization and inpatient hospitalization rates over the course of a year than patients who received usual care, according to a presentation at the International Society for Pharmacoeconomics and Outcomes Research. The platform pairs a blood glucose meter with a mobile app so patients can monitor their glucose levels in real time.

Skin patch reduces peanut allergy in toddlers: Researchers have developed a skin patch to treat young children with severe peanut allergies. In a study of toddlers ages 1 to 3, about two-thirds of the children who wore the patch coated with a tiny amount of peanut protein could safely eat up to four peanuts after a year, according to the findings published in the New England Journal of Medicine.

Electronic chest tattoo may reduce heart disease risk: An electronic chest patch placed on the skin for round-the-clock monitoring of the heart’s mechanical capacity and electrical activity operates as both a seismocardiogram and electrocardiogram, according to a study published in Advanced Electronic Materials. The tool was designed to monitor high-risk patients, including those who have coronary heart disease with decreased blood flow to the heart and people who have undergone heart surgery, according to study author Nanshu Lu.

Positive results seen with urge urinary incontinence treatment: An implantable tibial neuromodulation system called BlueWind RENOVA iStim demonstrated efficacy and had a favorable safety profile among women with urge urinary incontinence. At six (6) months, 76.4% of study participants saw a 50% or more decrease in incontinence episodes, according to data presented at the annual meeting of the American Urological Association.

Closed-loop system helps improve glucose control in Type-1 Diabetes: A study in the journal Diabetes Technology & Therapeutics found that Diabeloop’s closed-loop system Accu-Chek Insight was associated with improved glycemic control among patients with type 1 diabetes without major side effects. The study included 62 patients in real-world settings.

FDA issues guidance on risk-based clinical trial monitoring: The FDA released a final guidance explaining risk-based strategies that can be used by drug and device developers to monitor clinical trials of biological products, drugs, medical devices and combination products. The Agency said the document, which comes in question-and-answer format, “contains recommendations on planning a monitoring approach, developing the content of a monitoring plan, and addressing and communicating monitoring results.”

Algorithm mines infants’ health data for autism risk: An algorithm that analyzes health records for data on infant health care visits for brain, sleeping and stomach issues is helping physicians at Duke University identify babies at risk for autism spectrum disorder in their first month of life. The tool, combined with conversations with parents and doctors, identified nearly half the babies with ASD within a few days of birth, which may give families early access to interventions and support

Parkinson’s gloves designed to reduce tremors: Gloves that were designed to reduce the hand tremors of patients with Parkinson’s disease have been launched by the Chulalongkorn University Communication Center. The gloves automatically deliver electrical stimulation to the hand muscles without the need for brain surgery or increased medication.

Researchers develop risk-scoring tool for Diabetes: A new assessment model that combines basic health data and a methylation analysis identified more people at high risk for type 2 Diabetes than standard methylation-free assessments. The new assessment model might someday be used as a risk-scoring tool for conditions other than type 2 Diabetes, researchers wrote in Nature Aging.

Machine Learning (ML) could help guide depression treatment: A machine learning algorithm accurately predicted antidepressant treatment outcomes based on EHRs, suggesting the algorithm could be developed as a “clinical decision-making tool for personalized management of depression,” according to a study published in Psychiatric Research and Clinical Practice. Researchers tested various models and found the gradient boosting decision tree algorithm produced the most accurate results.