ReviewDiabetologia2022
One size does not fit all: an historian's perspective on precision diabetes medicine.
Review in Diabetologia, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Healthcare analytics-A literature review and proposed research agenda.Frontiers in big data · 2023Review
- The role of mental disorders in precision medicine for diabetes: a narrative review.Diabetologia · 2022Review
- The PPARGC1A Is the Gene Responsible for Thrifty Metabolism Related Metabolic Diseases: A Scoping Review.Genes · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
This article offers an historical approach to exploring precision medicine's potential for reducing health disparities in diabetes. It examines case studies from the twentieth-century USA, from early twentieth-century beliefs that Jews were most at risk of developing diabetes to claims in the 1980s that Native Americans, African Americans, Hispanic Americans and Asian Americans had the greatest likelihood of developing the disease. These case studies reveal that attempts to understand perceived health disparities have long tended to focus on the biology and behaviours of the unwell, while paying less attention to food security, workplace hazards, access to quality healthcare and other social determinants of health. The precision medicine initiative, I argue, has an opportunity to right this imbalance by leveraging the tools of big data to learn more not only about biomarkers but also about the social and physical environments in which people live and work.
Indexed as
Identifiers
What OpenQuestion holds
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.