Evidence map›Paper›PMID 40681567›Full record

Articlenpj aging2025

Identifying people with potentially undiagnosed dementia with Lewy bodies using natural language processing.

Mohamed Heybe, Lucy Gibson, Annabel C Price, Rudolf N Cardinal, John T O'Brien, Robert Stewart, Christoph Mueller

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in npj aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Observational
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mohamed HeybeInstitute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Lucy GibsonInstitute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Annabel C PriceDepartment of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Rudolf N CardinalDepartment of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
John T O'BrienDepartment of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
Robert StewartInstitute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
Christoph MuellerInstitute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. christoph.mueller@kcl.ac.uk.

Funding

UK Alzheimer's Society AS-PG-16-006 to JOB
6 · The paper itself

Abstract

Natural language processing (NLP) can expand the utility of clinical records data in dementia research. We deployed NLP algorithms to detect core features of dementia with Lewy bodies (DLB) and applied those to a large database of patients diagnosed with dementia in Alzheimer's disease (AD) or DLB. Of 14,329 patients identified, 4.3% had a diagnosis of DLB and 95.7% of dementia in AD. All core features were significantly commoner in DLB than in dementia in AD, although 18.7% of patients with dementia in AD had two or more DLB core features. In conclusion, NLP applications can identify core features of DLB in routinely collected data. Nearly one in five patients with dementia in AD have two or more DLB core features and potentially qualify for a diagnosis of probable DLB. NLP may be helpful to identify patients who may fulfil criteria for DLB but have not yet been diagnosed.

Identifiers

PMID40681567
PMCPMC12274350

What Socratic holds

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LicenceCC BY
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Registered trials

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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.