Evidence map›Paper›PMID 38057937›Full record

ArticleAlzheimer's research & therapy2023

The age-specific comorbidity burden of mild cognitive impairment: a US claims database study.

Gang Li, Nicola Toschi, Viswanath Devanarayan, Richard Batrla, Tommaso Boccato, Min Cho, Matteo Ferrante, Feride Frech, James E Galvin, David Henley and 3 more

Open access · goldAbstract read
In one paragraph

Article in Alzheimer's research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
4.0field-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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Observational
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

13 authors at 5 institutions in 3 countries.

Gang LiEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA. Gang_Li@eisai.com.
Nicola ToschiDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, 00133, Rome, Italy.
Viswanath DevanarayanEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA.
Richard BatrlaEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA.
Tommaso BoccatoDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, 00133, Rome, Italy.
Min ChoEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA.
Matteo FerranteDepartment of Biomedicine and Prevention, University of Rome Tor Vergata, Via Montpellier 1, 00133, Rome, Italy.
Feride FrechEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA.
James E GalvinMiller School of Medicine, University of Miami, 7700 W Camino Real, Suite 200, Boca Raton, FL, 33433, USA.
David HenleyResearch and Development, Janssen Pharmaceuticals, Inc., 1125 Bear Tavern Rd, Titusville, NJ, 08560, USA.
Soeren MattkeThe USC Brain Health Observatory, University of Southern California, 635 Downey Way, Los Angeles, CA, 90089, USA.
Susan De SantiEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA.
Harald HampelEisai Inc., 200 Metro Boulevard, Nutley, NJ, 07110, USA. harald_hampel@eisai.com.
Eisai (United States) · USUniversity of Rome Tor Vergata · ITJanssen (United States) · USUniversity of Miami · USUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease and related dementia disorders (ADRD) would facilitate the development of individualized prevention plans. We investigated the association between MCI and comorbidities of ADRD. We examined the predictive potential of these comorbidities for MCI risk determination using a machine learning algorithm.

methodsUsing a retrospective matched case-control design, 5185 MCI and 15,555 non-MCI individuals aged ≥50 years were identified from MarketScan databases. Predictive models included ADRD comorbidities, age, and sex.

resultsAssociations between 25 ADRD comorbidities and MCI were significant but weakened with increasing age groups. The odds ratios (MCI vs non-MCI) in 50-64, 65-79, and ≥ 80 years, respectively, for depression (4.4, 3.1, 2.9) and stroke/transient ischemic attack (6.4, 3.0, 2.1). The predictive potential decreased with older age groups, with ROC-AUCs 0.75, 0.70, and 0.66 respectively. Certain comorbidities were age-specific predictors.

conclusionsThe comorbidity burden of MCI relative to non-MCI is age-dependent. A model based on comorbidities alone predicted an MCI diagnosis with reasonable accuracy.

Indexed as

Alzheimer DiseaseCognitive DysfunctionAgedAge FactorsComorbidityDisease ProgressionHumansRetrospective StudiesSensitivity and SpecificityAge groupMCI comorbiditiesMCI risk predictionMild cognitive impairment (MCI)

Identifiers

PMID38057937
PMCPMC10701954
OpenAlexW4389379271

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.