Development and Clinical Application of Digital Biomarkers for Sarcopenia
Kim et al.
The finding, in our words
Wearable and remote digital biomarkers enable continuous, real-world monitoring of sarcopenia, capturing muscle strength, activity and fatigue beyond episodic clinic assessments. Machine learning fusion of these signals can build personalised digital twins for surgical and rehabilitation planning, but standardisation and large-scale clinical validation are required before these tools can support decentralised diagnostic criteria.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
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 ↗
Patients with metastatic cancer who recorded ≤3013 steps/day during the 14‑day post‑discharge period had substantially higher rates of 90‑day unplanned readmission (73% versus 13%) and mortality (47% versus 9%) than more active patients. Wearable‑derived mobility is a promising decentralised digital biomarker for risk stratification after hospital discharge, but requires external validation before guiding supportive care.
Akdogan et al., Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer (paywalled) · source ↗
Remote patient monitoring was feasible in pre-lung transplant candidates: 80 percent of participants entered data for at least four weeks, though adherence varied by modality (pulse oximetry 82 percent, spirometry 69 percent, activity tracking 31 percent). Daily step count declined during the median 11-week waiting period, and home-based walking distance was lower than on-site performance, indicating that remote monitoring can detect clinical changes but needs automated device integration to improve data capture and clinical utility.
Wickerson et al., Clinical transplantation · source ↗
In nursing home residents with dementia, longitudinal sensing using smartwatches and radar demonstrated high adherence (88% to 96%) and detected significant changes in nighttime movement and sleep metrics over one year. However, poor group-level reliability in acceleration metrics suggests digital biomarkers require careful validation before being used for individual clinical decision-making.
Digital biomarkers from smartphones and wearables correlated significantly with clinical scores for motor, cognitive and symptomatic domains in multiple sclerosis. Typing kinematics reflected upper limb dexterity, gait metrics reflected walking ability, and keystroke latency captured cognitive processing speed, while combined physiological and behavioural markers tracked fatigue, depression and sleep quality.
De Blasiis et al., Revue neurologique (paywalled) · source ↗