Evidence map›Paper›PMID 42119996›Full record

ArticleDiabetes, obesity & metabolism2026

Patterns and Trends of Glucose-Lowering Therapy in Alzheimer's Disease and Related Dementias.

Huilin Tang, Bingyu Zhang, Yiwen Lu, Ying Lu, Anastassia Amaro, Yuan Lu, David A Wolk, Yong Chen

Abstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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

8 authors.

Huilin TangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0002-5814-6657
Bingyu ZhangThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0001-7176-249X
Yiwen LuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Ying LuThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Anastassia AmaroPenn Metabolic Medicine, Division of Endocrinology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Yuan LuSection of Cardiovascular Medicine, Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
David A WolkDepartment of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.
Yong ChenThe Center for Health AI and Synthesis of Evidence (CHASE), University of Pennsylvania, Philadelphia, Pennsylvania, USA.ORCID https://orcid.org/0000-0003-0835-0788

Funding

TRiPOD: Toward Reusable Phenotypes in Observational Data for AD/ADRD - managing definitions and correcting biasR01AG073435 · UNIVERSITY OF PENNSYLVANIA · 2025 to 2025
$760k
NIH HHS R01AG073435NIH HHS R56AG074604NIH HHS RF1AG077820
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

antidiabetic drugcohort studydatabase researchelderlyglycaemic control

Identifiers

PMID42119996
PMCPMC13341381

What Socratic 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 Socratic graph.