Evidence map›Paper›PMID 37400639›Full record

ArticleNature medicine2023

Wearable movement-tracking data identify Parkinson's disease years before clinical diagnosis.

Ann-Kathrin Schalkamp, Kathryn J Peall, Neil A Harrison, Cynthia Sandor

Abstract read
PubMed Publisher
In one paragraph

Article in Nature medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

99 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Digital Outcomes as Biomarkers of Disease Progression in Early Parkinson's Disease: A Systematic Review.Movement disorders : official journal of the Movement Disorder Society · 2025
    Pooled it
  6. Pooled it
  7. Article
  8. Article
  9. Article
  10. Wearable Movement-Tracking for Prodromal Parkinson's Disease Detection: A Cross-Country Validation Study.Movement disorders : official journal of the Movement Disorder Society · 2026
    Article
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Review

39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ann-Kathrin SchalkampDivision of Psychological Medicine and Clinical Neuroscience, UK Dementia Research Institute, Cardiff University, Cardiff, UK.ORCID http://orcid.org/0000-0002-8609-9165
Kathryn J PeallDivision of Psychological Medicine and Clinical Neurosciences, Neuroscience and Mental Health Innovation Institute, Cardiff, UK.
Neil A HarrisonDivision of Psychological Medicine and Clinical Neurosciences, Neuroscience and Mental Health Innovation Institute, Cardiff, UK.ORCID http://orcid.org/0000-0002-9584-3769
Cynthia SandorDivision of Psychological Medicine and Clinical Neuroscience, UK Dementia Research Institute, Cardiff University, Cardiff, UK. SandorC@cardiff.ac.uk.

Funding

HCRW_ HS-20-11Medical Research Council MR/P008593/1Medical Research Council MR/V036084/1
6 · The paper itself

Abstract

Parkinson's disease is a progressive neurodegenerative movement disorder with a long latent phase and currently no disease-modifying treatments. Reliable predictive biomarkers that could transform efforts to develop neuroprotective treatments remain to be identified. Using UK Biobank, we investigated the predictive value of accelerometry in identifying prodromal Parkinson's disease in the general population and compared this digital biomarker with models based on genetics, lifestyle, blood biochemistry or prodromal symptoms data. Machine learning models trained using accelerometry data achieved better test performance in distinguishing both clinically diagnosed Parkinson's disease (n = 153) (area under precision recall curve (AUPRC) 0.14 ± 0.04) and prodromal Parkinson's disease (n = 113) up to 7 years pre-diagnosis (AUPRC 0.07 ± 0.03) from the general population (n = 33,009) compared with all other modalities tested (genetics: AUPRC = 0.01 ± 0.00, P = 2.2 × 10

Indexed as

Parkinson DiseaseWearable Electronic DevicesBiomarkersHumansMovementProdromal SymptomsBiomarkers

Identifiers

PMID37400639

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.