Evidence map›Paper›PMID 22649373›Full record

ArticleFrontiers in endocrinology2011

Approach to lipid screening as a risk marker for cardiovascular disease in pediatric patients with diabetes.

Jennifer Rachel Law, Shipra Patel, Anna Spagnoli

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Jennifer Rachel LawDivision of Pediatric Endocrinology, Department of Pediatrics, University of North Carolina at Chapel Hill Chapel Hill, NC, USA.
Shipra Patel
Anna Spagnoli
University of North Carolina at Chapel Hill · US

Funding

TRAINING PROGRAM IN ENDOCRINOLOGY &METABOLISMT32DK007129 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RUBIN, JANET E · 1986 to 2009
$2.9M
NIDDK NIH HHS T32 DK007129
6 · The paper itself

Abstract

Cardiovascular disease (CVD) is a well-known complication of diabetes mellitus (DM), and patients with DM are at an increased risk for early onset of CVD. Hyperglycemia is believed to be the primary mediator in premature development of atherosclerosis in patients with DM, but there are also derangements in cholesterol levels and inflammatory markers beyond the explanation of hyperglycemia. Although clinicians often screen for dyslipidemia as part of routine care for children and adolescents with DM, many do not feel comfortable treating this condition. Multiple guidelines exist to help clinicians with the prevention, screening, and treatment of CVD risk factors in pediatric patients with DM, but the guidelines do not always agree on screening intervals or medical treatment. Furthermore, the cost-effectiveness of medication use in this population has not been established. Research has advanced our understanding of the role of other biomarkers and radiologic studies of CVD risk, but these studies do not currently have a place in routine clinical practice. It is evident that the increased CVD risk in pediatric patients with DM is complex in origin and the optimal approach to managing dyslipidemia remains unclear. Therefore, an algorithm designed at the University of North Carolina (UNC), Division of Pediatric Endocrinology, is presented to help guide clinicians through screening and treatment of dyslipidemia in youth with DM.

Indexed as

cardiovascular diseasecholesteroldiabetesdyslipidemiastatin

Identifiers

PMID22649373
PMCPMC3355998
OpenAlexW2047648343

What OpenQuestion 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 OpenQuestion graph.