Smartphone tests quantify lower extremities dysfunction in multiple sclerosis
Jin et al.
The finding, in our words
Smartphone tests generated digital biomarkers that correlated strongly with traditional neurological assessments of gait and lower extremity function in MS patients (Spearman ρ up to 0.8). Machine learning models combining these biomarkers predicted physical disability accurately in an independent validation cohort, showing promise for remote, self-administered neurological monitoring.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
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.
Home spirometry gave slightly lower percent-predicted FEV1 values than office measurements cross-sectionally, but the three-month change in lung function did not differ significantly between settings. This suggests home spirometry can reliably detect treatment effects, supporting its use as an endpoint for decentralised cystic fibrosis trials.
Rosenfeld et al., Annals of the American Thoracic Society (paywalled) · source ↗
Analysis of six studies revealed that decentralised clinical trial elements enhanced data completeness by enabling direct access to medical records, although this introduced a significant burden for data abstraction. The results suggest that decentralised approaches are not a universal solution but provide specific metrics that can help design fit-for-purpose trials.
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.
Ma et al., Neurology and therapy (paywalled) · source ↗
The High-Definition Oncology feasibility study in 30 women with metastatic cancer demonstrated high adherence to biospecimen collection (97.4% plasma, 80.7% stool) and wearable monitoring (70–95% of days captured for activity, heart rate, sleep, and oxygen saturation). This establishes a viable framework for decentralised, multimodal data collection in oncology to support individualised treatment models.
Garma et al., JCO precision oncology (paywalled) · source ↗