Evidence map›Paper›PMID 41510365›Full record

ArticleJournal of diabetes and metabolic disorders2026

Treatment of type 2 diabetes among medicare beneficiaries with and without alzheimer's disease: A retrospective cohort study.

Yingqi Wang, G Caleb Alexander, Hemalkumar B Mehta

Abstract read
In one paragraph

Article in Journal of diabetes and metabolic disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Yingqi WangCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
G Caleb AlexanderCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.
Hemalkumar B MehtaCenter for Drug Safety and Effectiveness, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: While Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) commonly co-occur in older adults, little is known regarding whether and how the treatment of T2DM varies by AD status. This study aimed to compare and contrast T2DM treatment among individuals with and without AD. Methods: We conducted a retrospective cohort study using 20% Medicare Fee-for-Service claims data from 2016 to 2020. The primary outcome was initiation of any antidiabetic medication within one year of T2DM diagnosis, and we also examined initiation patterns across specific drug classes. We used multivariable logistic regression to estimate adjusted odds ratios for the association between AD and treatment initiation. Results: Among 388,359 beneficiaries newly diagnosed with T2DM, 9,584 had AD. Within one year, overall treatment initiation was lower for individuals with AD compared to those without. At initiation, individuals with AD were more likely to receive insulin and less likely to receive metformin, sodium-glucose cotransporter 2 (SGLT2) inhibitors, or glucagon-like peptide-1 (GLP-1) receptor agonists. In adjusted models, AD was associated with lower odds of antidiabetic treatment initiation, and among those initiating treatment, lower odds of initiating newer agents such as GLP-1 receptor agonists and SGLT2 inhibitors. Conclusion: Beneficiaries with AD were less likely to initiate antidiabetic therapy, particularly newer agents. Future work could explore the basis for these differences.

Indexed as

Alzheimer’s diseaseAntidiabetic medicationDrug useMedicareType 2 diabetes mellitus

Identifiers

PMID41510365
PMCPMC12775190

What OpenQuestion holds

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Registered trials

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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.