ArticleHeart and vessels2019
Influence of chronic kidney disease on coronary plaque components in coronary artery disease patients with both diabetes mellitus and hypertension.
Article in Heart and vessels, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Gene polymorphism associated with angiotensinogen (M235T), endothelial lipase (584C/T) and susceptibility to coronary artery disease: a meta-analysis.Bioscience reports · 2020Pooled it
- Review
- Comprehensive Risk Assessment of LAD Disease Progression in CCTA: The CLAP Score Study.Journal of cardiovascular development and disease · 2024Article
- Article
- Unsupervised machine learning based on clinical factors for the detection of coronary artery atherosclerosis in type 2 diabetes mellitus.Cardiovascular diabetology · 2022Article
- Atherosclerotic Coronary Artery Disease in Patients With Cardiometabolic Syndrome.Cardiology research · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic kidney disease (CKD) is well known to be associated with an increased incidence of coronary artery disease (CAD). Diabetes mellitus (DM) and hypertension (HTN), both of which are traditional risk factors for CAD, are the two most common causes of CKD. However, the influence of CKD on coronary atherosclerosis in CAD patients who have both DM and HTN remains uncertain. In these patients, we examined the relationship between CKD and coronary plaque using integrated backscatter intravascular ultrasound (IB IVUS). Two hundred two CAD patients with both DM and HTN who underwent percutaneous coronary intervention using IB IVUS were included. The patients were divided into two groups: CKD group (n = 106) and non-CKD group (n = 96). Gray-scale and IB IVUS examinations were conducted for the non-culprit segment of a coronary artery. As a result, although there was no significant difference in the percentage of plaque volume, the percentage of lipid volume was significantly higher in the CKD group than in the non-CKD group [median (IQR): 56.7% (45.4-67.0%) vs. 52.0% (38.3-60.2%), p = 0.03]. In all of the patients, estimated glomerular filtration rate levels were negatively correlated with the percentage of lipid volume (r = - 0.15, p = 0.03) and positively correlated with the percentage of fibrosis volume (r = 0.15, p = 0.04). A multivariate regression analysis showed that CKD was an independent predictor associated with the increased lipid volume (β = 0.15, p = 0.047) and decreased fibrosis volume (β = - 0.16, p = 0.03) in coronary plaques. In conclusion, among CAD patients who had both DM and HTN, CKD was associated with lipid-rich coronary plaques. CKD may contribute to the vulnerability of coronary plaque in these very high-risk patients.
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.