Evidence map›Paper›PMID 26017789›Full record

ArticleClinics (Sao Paulo, Brazil)2015

Computed tomography imaging of early coronary artery lesions in stable individuals with multiple cardiovascular risk factors.

Xi Yang, Hong Huang, Hong Liu, Zhi-Yu Zeng, Jie Zhang

Open access · goldAbstract read
In one paragraph

Article in Clinics (Sao Paulo, Brazil), 2015. 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
–field-weighted citation impact, top 87% 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

5 authors at 1 institution in 1 country.

Xi YangDivision of Geriatrics Endocrinology, Guangxi Medical University, Nanning, China.
Hong HuangDivision of Geriatrics Endocrinology, Guangxi Medical University, Nanning, China.
Hong LiuDivision of Geriatrics Endocrinology, Guangxi Medical University, Nanning, China.
Zhi-Yu ZengDivision of Geriatrics Endocrinology, Guangxi Medical University, Nanning, China.
Jie ZhangDivision of Geriatrics Endocrinology, Guangxi Medical University, Nanning, China.
Guangxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the prevalence, extent, severity, and features of coronary artery lesions in stable patients with multiple cardiovascular risk factors.

methodsSeventy-seven patients with more than 3 cardiovascular risk factors were suspected of having coronary artery disease. Patients with high-risk factors and 39 controls with no risk factors were enrolled in the study. The related risk factors included hypertension, impaired glucose tolerance, dyslipidemia, smoking history, and overweight. The characteristics of coronary lesions were identified and evaluated by 64-slice coronary computed tomography angiography.

resultsThe incidence of coronary atherosclerosis was higher in the high-risk group than in the no-risk group. The involved branches of the coronary artery, the diffusivity of the lesion, the degree of stenosis, and the nature of the plaques were significantly more severe in the high-risk group compared with the no-risk group (all p < 0.05).

conclusionAmong stable individuals with high-risk factors, early coronary artery lesions are common and severe. Computed tomography has promising value for the early screening of coronary lesions.

Indexed as

AgedChinaCoronary AngiographyCoronary Artery DiseaseCoronary StenosisDiabetes ComplicationsDyslipidemiasEpidemiologic MethodsFemaleHumansHypertensionMaleMiddle AgedMultidetector Computed TomographyOverweightRisk Factors

Identifiers

PMID26017789
PMCPMC4418353
OpenAlexW2231450533

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.