Evidence map›Paper›PMID 36221141›Full record

ArticleTrials2022

Digital detection of dementia (D

Michael J Kleiman, Abbi D Plewes, Arthur Owora, Randall W Grout, Paul Richard Dexter, Nicole R Fowler, James E Galvin, Zina Ben Miled, Malaz Boustani

Registry-linked trialOpen access · goldAbstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05231954 (Digital Detection of Dementia), which is not on this map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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.

NCT05231954 nacompletednot on this map

Digital Detection of Dementia (D Cubed) Studies: D2

TypeinterventionalSponsorIndiana UniversityRan2022 to 2024Enrolled5,325ConditionsAlzheimer Disease and Related Dementias (ADRD)ArmsPassive Digital Marker for screening for ADRD
3 · Its place in the literature

Who cites it

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. 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

9 authors at 5 institutions in 1 country.

Michael J Kleiman *Comprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, 7700 W Camino Real, Suite 200, Boca Raton, FL, 33433, USA. mjkleiman@miami.edu.ORCID http://orcid.org/0000-0002-7052-5502
Abbi D Plewes *Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
Arthur OworaIndiana University Bloomington School of Public Health, Bloomington, IN, 47405, USA.
Randall W GroutIndiana University School of Medicine, Indianapolis, IN, 46202, USA.
Paul Richard DexterIndiana University School of Medicine, Indianapolis, IN, 46202, USA.
Nicole R FowlerIndiana University School of Medicine, Indianapolis, IN, 46202, USA.
James E GalvinComprehensive Center for Brain Health, Department of Neurology, University of Miami Miller School of Medicine, 7700 W Camino Real, Suite 200, Boca Raton, FL, 33433, USA.
Zina Ben MiledIndiana University School of Medicine, Indianapolis, IN, 46202, USA.
Malaz BoustaniIndiana University School of Medicine, Indianapolis, IN, 46202, USA.
Regenstrief Institute · USUniversity of Miami · USIndiana Clinical and Translational Sciences Institute · USIndiana University Bloomington · USIndiana University School of Medicine

Funding

Multicultural Community Dementia ScreeningR01AG071514 · NIA · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI GALVIN, JAMES E · 2021 to 2025
$13.8M
Digital Detection of Dementia Studies (D cubed Studies).R01AG069765 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI BEN-MILED, ZINA, BOUSTANI, MALAZ · 2020 to 2024
$4.9M
NIA NIH HHS 5R01AG069765-03NIA NIH HHS R01 AG069765NIA NIH HHS R01 AG071514
6 · The paper itself

Abstract

backgroundEarly detection of Alzheimer's disease and related dementias (ADRD) in a primary care setting is challenging due to time constraints and stigma. The implementation of scalable, sustainable, and patient-driven processes may improve early detection of ADRD; however, there are competing approaches; information may be obtained either directly from a patient (e.g., through a questionnaire) or passively using electronic health record (EHR) data. In this study, we aim to identify the benefit of a combined approach using a pragmatic cluster-randomized clinical trial.

methodsWe have developed a Passive Digital Marker (PDM), based on machine learning algorithms applied to EHR data, and paired it with a patient-reported outcome (the Quick Dementia Rating Scale or QDRS) to rapidly share an identified risk of impairment to a patient's physician. Clinics in both south Florida and Indiana will be randomly assigned to one of three study arms: 1200 patients in each of the two populations will be administered either the PDM, the PDM with the QDRS, or neither, for a total of 7200 patients across all clinics and populations. Both incidence of ADRD diagnosis and acceptance into ADRD diagnostic work-up regimens is hypothesized to increase when patients are administered both the PDM and QDRS. Physicians performing the work-up regimens will be blind to the study arm of the patient. DISCUSSION: This study aims to test the accuracy and effectiveness of the two scalable approaches (PDM and QDRS) for the early detection of ADRD among older adults attending primary care practices. The data obtained in this study may lead to national early detection and management program for ADRD as an efficient and beneficial method of reducing the current and future burden of ADRD, as well as improving the annual rate of newly documented ADRD in primary care practices.

trial registrationClinicalTrials.gov Identifier: NCT05231954 . Registered February 9, 2022.

Indexed as

Alzheimer DiseaseDecision Support Systems, ClinicalAgedEarly DiagnosisHumansPatient Reported Outcome MeasuresPragmatic Clinical Trials as TopicRandomized Controlled Trials as TopicSurveys and QuestionnairesAlzheimer’s disease and related dementiasClinical decision supportElectronic health recordsMachine learningPatient reported outcome

Identifiers

PMID36221141
PMCPMC9552361
OpenAlexW4304187567

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.