ArticleCardiovascular diagnosis and therapy2015
Diabetes and cardiovascular disease: let's push forward with translational research.
Article in Cardiovascular diagnosis and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Albeit advances in therapy have reduced morbidity and mortality in patients with diabetes, cardiovascular (CV) risk is far to be eradicated. This is partially due to the fact that breakthrough therapies have yet to be approved to counteract the atherosclerotic burden in this setting. Therefore, it is very important to understand the molecular mechanisms underpinning diabetes-related CV complications. Growing evidence is supporting the concept that translational research is perhaps the best approach to unveil novel insights into disease etiology and its link with CV phenotypes. The recent employment of high throughput "omics" (i.e., metabolomics, transcriptomics, proteomics) is a clinically relevant approach which may provide insightful interpretations of diabetes-related biological signals. The possibility to analyse thousands or more molecules simultaneously has given "omics" the ability to generate enormous quantities of data which may somehow offer a precious "window on the disease". In the present article, we critically discuss the importance of translational research in diabetes, including potential difficulties which may arise in the implementation and development of promising technologies from the laboratory to the marketplace.
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.