ArticleDiabetes care2016
The Application of Genomics in Diabetes: Barriers to Discovery and Implementation.
Article in Diabetes care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 33 citations in OpenAlex.
- Bibliometric analysis of research on the utilization of nanotechnology in diabetes mellitus and its complications.Nanomedicine (London, England) · 2024Article
- Systems Biology to Address Unmet Medical Needs in Neurological Disorders.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review.International journal of environmental research and public health · 2021Review
- Social and behavioral science at the forefront of genomics: Discovery, translation, and health equity.Social science & medicine (1982) · 2021Article
- Effects of a Lifestyle-Modification Program on Blood-Glucose Regulation and Health Promotion in Diabetic Patients: A Randomized Controlled Trial.Journal of lifestyle medicine · 2020Article
- Recent advances and perspectives in next generation sequencing application to the genetic research of type 2 diabetes.World journal of diabetes · 2019Review
- The Continuing Evolution of Precision Health in Type 2 Diabetes: Achievements and Challenges.Current diabetes reports · 2019Review
- Precision medicine in diabetes prevention, classification and management.Journal of diabetes investigation · 2018Review
- Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.Clinical and translational medicine · 2017Article
- The Impact of Precision Medicine in Diabetes: A Multidimensional Perspective.Diabetes care · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
The emerging availability of genomic and electronic health data in large populations is a powerful tool for research that has drawn interest in bringing precision medicine to diabetes. In this article, we discuss the potential application of genomics to the prediction, prevention, and treatment of diabetes, and we use examples from other areas of medicine to illustrate some of the challenges involved in conducting genomics research in human populations and implementing findings in practice. At this time, a major barrier to the application of genomics in diabetes care is the lack of actionable genomic findings. Whether genomic information should be used in clinical practice requires a framework for evaluating the validity and clinical utility of this approach, an improved integration of genomic data into electronic health records, and the clinical decision support and educational resources for clinicians to use these data. Efforts to identify optimal approaches in all of these domains are in progress and may help to bring diabetes into the era of genomic medicine.
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.