Evidence map›Paper›PMID 27612474›Full record

ReviewCurrent cardiology reports2016

Integrating Biomarkers and Imaging for Cardiovascular Disease Risk Assessment in Diabetes.

David M Tehrani, Nathan D Wong

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Review
  3. Review
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 at 2 institutions in 1 country.

David M TehraniDepartment of Medicine, University of Chicago Medical Center, Chicago, IL, USA.
Nathan D WongHeart Disease Prevention Program, Division of Cardiology, University of California, Irvine, Irvine, CA, USA. ndwong@uci.edu.
University of California, Irvine · USUniversity of Chicago Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease (CVD) risk assessment has changed substantially in recent years. While older guidelines considered diabetes a coronary disease risk equivalent, more recent guidelines recommend risk stratification on the basis of global risk scoring to target intensity of therapy. While patients with diabetes as a whole are at greater risk for CVD events, these patients may also benefit from risk stratification based on circulating biomarkers like high-sensitivity C-reactive protein, high-sensitivity cardiac troponin T, and N-terminal pro-B-type natriuretic peptide, as well as newer imaging modalities (coronary artery calcium, carotid intima-media thickness, and myocardial perfusion imaging). The addition of these CVD risk assessment modalities could play an important role for deciding how aggressive a physician should be with pharmacological therapy. Here, we discuss many of the current recommendations of CVD risk assessment in patients with diabetes including newer modalities for CVD risk assessment.

Indexed as

BiomarkersCalciumCardiovascular DiseasesCarotid Intima-Media ThicknessCoronary VesselsC-Reactive ProteinDiabetic AngiopathiesEchocardiographyHumansMyocardial Perfusion ImagingNatriuretic Peptide, BrainPeptide FragmentsPractice Guidelines as TopicRisk AssessmentRisk FactorsTroponin TBiomarkersCalciumC-Reactive ProteinNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)Troponin TCardiovascular diseaseCarotid intima-media thicknessCoronary artery calciumC-reactive proteinDiabetesMyocardial perfusion imaging

Identifiers

PMID27612474
OpenAlexW2518045962

What Socratic holds

Textmetadata
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 Socratic graph.