ReviewNPJ digital medicine2024
Digital biomarkers for precision diagnosis and monitoring in Parkinson's disease.
Review in NPJ digital medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
56 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Digital Technologies and Biomarkers for Locomotor Capacity Assessment in Older Adults: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Computer Vision Technologies in Movement Disorders: A Systematic Review.Movement disorders clinical practice · 2025Pooled it
- Actual Data on Essential Trace Elements in Parkinson's Disease.Nutrients · 2025Pooled it
- Effects of immersive virtual reality and adaptive cognitive training on cognition and function in parkinson's disease mild cognitive impairment: a randomized clinical trial.Scientific reports · 2026Trial
- Toward Interpretable Voice-Based Parkinson's Disease Screening via Joint Transfer Function-Feature-Classifier-Ensemble Selection.Bioengineering (Basel, Switzerland) · 2026Article
- Evaluating the Relationship Between Early Non-Motor Symptoms and Late Diagnosis of Parkinson's Disease Based on the PPMI Database From 2012 to 2018: A Retrospective Cross-Sectional Study.Health science reports · 2026Article
- Artificial Intelligence and Digital Biomarkers for Early Detection and Monitoring of Neurological Disorders: A Narrative Review.Diagnostics (Basel, Switzerland) · 2026Review
- Physical Activity and Exercise for People with Parkinson's Disease: The Past, Present, and Future.Movement disorders : official journal of the Movement Disorder Society · 2026Review
- What's in a name? reframing advanced Parkinson's disease as a multidimensional state.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- A Dual-Task Gait Fusion Framework for Classifying Parkinson's Disease Severity from Wearable Sensor Data.Diagnostics (Basel, Switzerland) · 2026Article
- Bridging the global Parkinson's divide: Technology as a structural solution for equitable and brain health-integrated care.Journal of Parkinson's disease · 2026Review
- Review
- Lactate dynamics in Parkinson's disease: striatal circuit vulnerability, biomarker potential, and therapeutic windows.Molecular medicine (Cambridge, Mass.) · 2026Review
- Field-Driven Activation of Solid-State Devices in Open Circuits for Energy Harvesting and Wireless Sensing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Digital diagnostics, biomarkers and therapeutics in an evolving healthcare system: From promise to practice.British journal of clinical pharmacology · 2026Review
- Mapping the Parkinson's pandemic: Unveiling and addressing the global burden.Journal of Parkinson's disease · 2026Review
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study.JMIR medical informatics · 2026Article
- PREDICT-PD: A Two-Stage Approach to Early Identification of Parkinson's Disease.Movement disorders clinical practice · 2026Article
- Urinary Biomarkers in Parkinson's Disease: A Structured Integrative Review of Pathophysiological Pathways.Medical sciences (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is a multifactorial neurodegenerative disorder with high prevalence among the elderly, primarily manifested by progressive decline in motor function. The aging global demographic and increased life expectancy have led to a rapid surge in PD cases, imposing a significant societal burden. PD along with other neurodegenerative diseases has garnered increasing attention from the scientific community. In PD, motor symptoms are recognized when approximately 60% of dopaminergic neurons have been damaged. The irreversible feature of PD and benefits of early intervention underscore the importance of disease onset prediction and prompt diagnosis. The advent of digital health technology in recent years has elevated the role of digital biomarkers in precisely and sensitively detecting early PD clinical symptoms, evaluating treatment effectiveness, and guiding clinical medication, focusing especially on motor function, responsiveness and sleep quality assessments. This review examines prevalent digital biomarkers for PD and highlights the latest advancements.
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.