Evidence map›Paper›PMID 37361261›Full record

ArticleAlzheimer's & dementia (Amsterdam, Netherlands)

Automated detection of progressive speech changes in early Alzheimer's disease.

Jessica Robin, Mengdan Xu, Aparna Balagopalan, Jekaterina Novikova, Laura Kahn, Abdi Oday, Mohsen Hejrati, Somaye Hashemifar, Mohammadreza Negahdar, William Simpson and 1 more

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's & dementia (Amsterdam, Netherlands). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
4.5field-weighted citation impact, top 5% of its field
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

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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  3. Review
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  5. Article
  6. Article
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  8. Review
  9. Article
  10. Review
  11. Speech patterns during memory recall relates to early tau burden across adulthood.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024
    Article
  12. Observational
  13. Article
  14. Article
  15. Review
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

11 authors at 2 institutions in 1 country.

Jessica RobinWinterlight Labs Inc. Toronto Ontario Canada.
Mengdan XuWinterlight Labs Inc. Toronto Ontario Canada.
Aparna BalagopalanWinterlight Labs Inc. Toronto Ontario Canada.
Jekaterina NovikovaWinterlight Labs Inc. Toronto Ontario Canada.
Laura KahnPresent address: Genentech, Inc. South San Francisco California USA.
Abdi OdayPresent address: Genentech, Inc. South San Francisco California USA.
Mohsen HejratiPresent address: Genentech, Inc. South San Francisco California USA.
Somaye HashemifarPresent address: Genentech, Inc. South San Francisco California USA.
Mohammadreza NegahdarPresent address: Genentech, Inc. South San Francisco California USA.
William SimpsonWinterlight Labs Inc. Toronto Ontario Canada.
Edmond TengPresent address: Genentech, Inc. South San Francisco California USA.
nLIGHT (United States) · USVyne Therapeutics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Speech and language changes occur in Alzheimer's disease (AD), but few studies have characterized their longitudinal course. We analyzed open-ended speech samples from a prodromal-to-mild AD cohort to develop a novel composite score to characterize progressive speech changes. Participant speech from the Clinical Dementia Rating (CDR) interview was analyzed to compute metrics reflecting speech and language characteristics. We determined the aspects of speech and language that exhibited significant longitudinal change over 18 months. Nine acoustic and linguistic measures were combined to create a novel composite score. The speech composite exhibited significant correlations with primary and secondary clinical endpoints and a similar effect size for detecting longitudinal change. Our results demonstrate the feasibility of using automated speech processing to characterize longitudinal change in early AD. Speech-based composite scores could be used to monitor change and detect response to treatment in future research. HIGHLIGHTS: Longitudinal speech samples were analyzed to characterize speech changes in early AD.Acoustic and linguistic measures showed significant change over 18 months.A novel speech composite score was computed to characterize longitudinal change.The speech composite correlated with primary and secondary trial endpoints.Automated speech analysis could facilitate remote, high frequency monitoring in AD.

Indexed as

Alzheimer's diseasedigital biomarkerslanguagemild cognitive impairmentnatural language processingspeech

Identifiers

PMID37361261
PMCPMC10286224
OpenAlexW4381930698

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.