ArticleRambam Maimonides medical journal2014
Introduction to personalized medicine in diabetes mellitus.
Article in Rambam Maimonides medical journal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
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Who cites it
7 citing papers in PubMed, 26 citations in OpenAlex.
- Conditionally Reprogrammed Cells Preserve Cellular Diversity and Permit Genetic Manipulation: Implications for Cancer Heterogeneity and Tissue Regeneration.Serican journal of medicine · 2026Article
- Transform diabetes care with precision medicine.Health science reports · 2023Review
- DMTO: a realistic ontology for standard diabetes mellitus treatment.Journal of biomedical semantics · 2018Article
- Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.Clinical and translational medicine · 2017Article
- Older Adult Self-Efficacy Study of Mobile Phone Diabetes Management.Diabetes technology & therapeutics · 2015Article
- Meha 2014: a national seminar on diabetes mellitus.Journal of Ayurveda and integrative medicine · 2014Article
- Diabetic retinopathy: variations in patient therapeutic outcomes and pharmacogenomics.Pharmacogenomics and personalized medicine · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The world is facing an epidemic rise in diabetes mellitus (DM) incidence, which is challenging health funders, health systems, clinicians, and patients to understand and respond to a flood of research and knowledge. Evidence-based guidelines provide uniform management recommendations for "average" patients that rarely take into account individual variation in susceptibility to DM, to its complications, and responses to pharmacological and lifestyle interventions. Personalized medicine combines bioinformatics with genomic, proteomic, metabolomic, pharmacogenomic ("omics") and other new technologies to explore pathophysiology and to characterize more precisely an individual's risk for disease, as well as response to interventions. In this review we will introduce readers to personalized medicine as applied to DM, in particular the use of clinical, genetic, metabolic, and other markers of risk for DM and its chronic microvascular and macrovascular complications, as well as insights into variations in response to and tolerance of commonly used medications, dietary changes, and exercise. These advances in "omic" information and techniques also provide clues to potential pathophysiological mechanisms underlying DM and its complications.
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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 OpenQuestion graph.