Evidence map›Paper›PMID 28956084›Full record

ReviewDiabetologia2018

Biomarkers of cardiovascular disease: contributions to risk prediction in individuals with diabetes.

Katherine N Bachmann, Thomas J Wang

Abstract readReview
In one paragraph

Review in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Trial
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  18. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Katherine N BachmannVanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA. Katherine.n.bachmann@vanderbilt.edu.
Thomas J WangVanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, TN, USA.

Funding

Metabolomic predictors of insulin resistance and diabetesR01DK081572 · NIDDK · VANDERBILT UNIVERSITY · PI CLISH, CLARY B, GERSZTEN, ROBERT E · 2008 to 2025
$9.3M
Metabolite profiles and the risk of diabetes in AsiansR01DK108159 · NIDDK · VANDERBILT UNIVERSITY MEDICAL CENTER · PI GERSZTEN, ROBERT E, SHU, XIAO-OU · 2016 to 2019
$2.6M
NIDDK NIH HHS R01 DK081572NIDDK NIH HHS R01 DK108159NIH HHS R01 DK108159Vanderbilt University Medical Center Vanderbilt University Medical Center Faculty Resea
6 · The paper itself

Abstract

Cardiovascular disease is a leading cause of death, especially in individuals with diabetes mellitus, whose risk of morbidity and mortality due to cardiovascular disease is markedly increased compared with the general population. There has been growing interest in the identification of biomarkers of cardiovascular disease in people with diabetes. The present review focuses on the current and potential contributions of these biomarkers to predicting cardiovascular risk in individuals with diabetes. At present, certain biomarkers and biomarker combinations can lead to modest improvements in the prediction of cardiovascular disease in diabetes beyond traditional cardiovascular risk factors. Emerging technologies may enable the discovery of novel biomarkers and generate new information about known biomarkers (such as new combinations of biomarkers), which could lead to significant improvements in cardiovascular disease risk prediction. A critical question, however, is whether improvements in risk prediction will affect processes of care and decision making in clinical practice, as this will be required to achieve the ultimate goal of improving clinical outcomes in diabetes.

Indexed as

BiomarkersCardiovascular DiseasesClinical Trials as TopicDecision MakingDiabetes Mellitus, Type 2Diabetic NephropathiesHumansMultivariate AnalysisPrediabetic StateRisk FactorsTreatment OutcomeBiomarkersCardiac complicationsClinical diabetesClinical scienceEpidemiologyHumanMacrovascular diseaseReview

Identifiers

PMID28956084
PMCPMC5874155

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.