ArticleFrontiers in medicine2025
The US Deprescribing Research Network: a network to catalyze deprescribing science.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
Abstract
Deprescribing plays a critical role in ensuring safe and effective healthcare for older adults, including but not limited to those with vulnerabilities such as multimorbidity and dementia, which increase the risk of harm from unnecessary medications. However, much is unknown on how to safely and effectively stop medications. In response, the US Deprescribing Research Network (USDeN) was created with a mission of enhancing the quality, volume, and real-world impact of research aimed at optimizing medication use among older adults. This Perspective explores the rationale for its creation, the principles and ideas that animate its work, its impacts on research, and future directions for deprescribing research. By advancing research in this area, we aim to improve healthcare outcomes and reduce medication-related harm among older adults.
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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 Socratic graph.