Evidence map›Paper›PMID 30681435›Full record

ArticleAlzheimer disease and associated disorders

An Algorithm to Characterize a Dementia Population by Disease Subtype.

Jennifer S Albrecht, Maya Hanna, Rhonda L Randall, Dure Kim, Eleanor M Perfetto

Abstract read
In one paragraph

Article in Alzheimer disease and associated disorders. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 41% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Healthcare Resource Utilization Among Patients With Agitation in Alzheimer Dementia.Journal of health economics and outcomes research · 2024
    Article
  4. Article
  5. 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

5 authors at 3 institutions in 1 country.

Jennifer S AlbrechtDepartment of Epidemiology and Public Health, University of Maryland School of Medicine.
Maya HannaDepartment of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD.
Rhonda L RandallUnited Health Group, Minneapolis, MN.
Dure KimDepartment of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD.
Eleanor M PerfettoDepartment of Pharmaceutical Health Services Research, University of Maryland School of Pharmacy, Baltimore, MD.
University of Maryland, Baltimore · USNational Health Council · USUnitedHealth Group (United States) · US

Funding

Prioritizing Quality Improvement for the Treatment of Psychiatric Disturbances Following Traumatic Brain InjuryK01HS024560 · AHRQ · UNIVERSITY OF MARYLAND BALTIMORE · PI ALBRECHT, JENNIFER S. · 2016 to 2020
$735k
AHRQ HHS K01 HS024560
6 · The paper itself

Abstract

purposeIdentification of Alzheimer disease and related dementias (ADRD) subtypes is important for pharmacologic treatment and care planning, yet inaccuracies in dementia diagnoses make ADRD subtypes hard to identify and characterize. The objectives of this study were to (1) develop a method to categorize ADRD cases by subtype and (2) characterize and compare the ADRD subtype populations by demographic and other characteristics.

methodsWe identified cases of ADRD occurring during 2008 to 2014 from the OptumLabs Database using diagnosis codes and antidementia medication fills. We developed a categorization algorithm that made use of temporal sequencing of diagnoses and provider type.

resultsWe identified 36,838 individuals with ADRD. After application of our algorithm, the largest proportion of cases were nonspecific dementia (41.2%), followed by individuals with antidementia medication but no ADRD diagnosis (15.6%). Individuals with Alzheimer disease formed 10.2% of cases. Individuals with vascular dementia had the greatest burden of comorbid disease. Initial documentation of dementia occurred primarily in the office setting (35.1%). DISCUSSION: Our algorithm identified 6 dementia subtypes and three additional categories representing unique diagnostic patterns in the data. Differences and similarities between groups provided support for the approach and offered unique insight into ADRD subtype characteristics.

Indexed as

Administrative Claims, HealthcareAlgorithmsAgedAged, 80 and overDatabases, FactualDementiaDementia, VascularFemaleHumansLongitudinal StudiesMaleMedicare Part CUnited States

Identifiers

PMID30681435
PMCPMC6941141
OpenAlexW2912968405

What OpenQuestion holds

Textmetadata
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.