Evidence map›Paper›PMID 37747662›Full record

ArticleNeurology and therapy2023

Rule-Based Identification of Individuals with Mild Cognitive Impairment or Alzheimer's Disease Using Clinical Notes from the United States Veterans Affairs Healthcare System.

Byron J Aguilar, Donald Miller, Guneet Jasuja, Xuyang Li, Ekaterina Shishova, Maureen K O'Connor, Andrew Nguyen, Peter Morin, Dan Berlowitz, Raymond Zhang and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neurology and therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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.

Byron J AguilarGeriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
Donald MillerZuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
Guneet JasujaCenter for Healthcare Organization and Implementation, VA Bedford Healthcare System, Bedford, MA, USA.
Xuyang LiGeriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
Ekaterina ShishovaZuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
Maureen K O'ConnorGeriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
Andrew NguyenGeriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA.
Peter MorinDepartment of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
Dan BerlowitzZuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA.
Raymond ZhangAlzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
Amir Abbas Tahami MonfaredAlzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
Quanwu ZhangAlzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
Weiming XiaGeriatric Research Education and Clinical Center, VA Bedford Healthcare System, 200 Springs Road, Bedford, MA, USA. weiming.xia@va.gov.ORCID http://orcid.org/0000-0002-7463-3295

Funding

Big data and small molecules for Alzheimer's diseaseRF1AG063913 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI GOLDSTEIN, LEE E., XIA, WEIMING · 2019 to 2021
$2.9M
NIA NIH HHS RF1 AG063913NIH HHS RF1AG063913
6 · The paper itself

Abstract

backgroundEarly identification of individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a clinical and research imperative. Use of diagnostic codes for MCI and AD identification has limitations. We used clinical notes to supplement diagnostic codes in the Veterans Affairs Healthcare System (VAHS) electronic health records (EHR) to identify and establish cohorts of Veterans recorded with MCI or AD.

methodsTargeted keyword searches for MCI ("Mild cognitive impairment;" "MCI") and AD ("Alz*") were used to extract clinical notes from the VAHS EHR from fiscal year (FY) 2010 through FY 2019. Iterative steps of inclusion and exclusion were applied until searches achieved a positive predictive value ≥ 80%. MCI and AD cohorts were identified via clinical notes and/or diagnostic codes (i.e., including Veterans recorded by "Notes Only," "Notes + Code," or "Codes Only").

resultsA total of 2,134,661 clinical notes from 339,007 Veterans met the iterative search criteria for MCI due to any cause and 4,231,933 notes from 572,063 Veterans met the iterative search criteria for AD. Over the 10-year study period, the number of clinical notes recording AD was generally stable, whereas the number for MCI more than doubled. More Veterans were identified for the MCI or AD cohorts via clinical notes than by diagnostic codes, particularly in the AD cohort. Among Veterans identified by having "Notes + Code" for MCI, the number first recorded by a code was lower than the number first recorded by a note until FY 2015 and then gradually became comparable after FY 2015. Among Veterans identified by having "Notes + Code" for AD, the number first recorded by a note was more than double the number first recorded by a code AD in each of the FYs.

conclusionsClinical note-based identification captured more Veterans recorded with MCI and AD than diagnostic code-based identification.

Indexed as

Alzheimer’s diseaseMild cognitive impairmentRule-based processingVeteran

Identifiers

PMID37747662
PMCPMC10630261

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.