Aims: This cross-sectional analysis explored the relationships between periodontal disease (PD) and subclinical CVD in a cohort of patients with type 1 diabetes and non-diabetic controls.

Methods: Data were collected from adults enrolled in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study or enrolled through the Barbara Davis Center for Diabetes Adult Clinic. A clinical periodontal exam measured attachment loss and probing depth. Brachial artery distensibility (brachD), carotid intima-media thickness (cIMT), and pulse wave velocity (PWV) were assessed as measures of subclinical cardiovascular structure and function.

Results: 144 participants with T1D and 148 non-diabetics were enrolled. Compared to non-diabetic controls, T1D participants had a higher probing depth (2.6 mm vs. 2.5 mm; p = 0.04), higher attachment loss (2.7 mm vs. 2.4 mm; p < 0.01), lower brachD (mean 5.8 vs. 6.4 mmHg; p < 0.01), a higher cIMT (mean 0.68 vs. 0.64 mm; p < 0.01), and a higher PWV (mean 8.3 vs. 7.8 m/s; p < 0.01). There were no significant associations between PD and CVD metrics.

Conclusions: Periodontal and cardiovascular health was worse in participants with T1D compared to non-diabetics. No significant associations between PD measures and CVD were identified.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10601755PMC
http://dx.doi.org/10.1016/j.jdiacomp.2023.108494DOI Listing

Publication Analysis

Top Keywords

type diabetes
12
attachment loss
8
probing depth
8
periodontitis cardiovascular
4
cardiovascular risk
4
risk factors
4
factors subjects
4
subjects type
4
diabetes
4
diabetes cross
4

Similar Publications

Background: There are insufficient studies to determine whether sodium-glucose cotransporter type 2 inhibitors (SGLT2i) will help reduce early diabetic cardiomyopathy, especially in patients without documented cardiovascular disease.

Methods: We performed a single center, prospective observation study. A total of 90 patients with type 2 diabetes patients without established heart failure or atherosclerotic cardiovascular disease were enrolled.

View Article and Find Full Text PDF

Background: Obesity is a multifactorial disease reaching pandemic proportions with increasing healthcare costs, advocating the development of better prevention and treatment strategies. Previous research indicates that the gut microbiome plays an important role in metabolic, hormonal, and neuronal cross-talk underlying eating behavior. We therefore aim to examine the effects of prebiotic and neurocognitive behavioral interventions on food decision-making and to assay the underlying mechanisms in a Randomized Controlled Trial (RCT).

View Article and Find Full Text PDF

Background: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabetes mellitus (GDM) to type 2 diabetes mellitus (T2DM).

Methods: A comprehensive and systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science up to July 02, 2024. The quality of the studies included was assessed.

View Article and Find Full Text PDF

Improving 10-year cardiovascular risk prediction in patients with type 2 diabetes with metabolomics.

Cardiovasc Diabetol

January 2025

Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Im Neuenheimer Feld 581, 69120, Heidelberg, Germany.

Background: Existing cardiovascular risk prediction models still have room for improvement in patients with type 2 diabetes who represent a high-risk population. This study evaluated whether adding metabolomic biomarkers could enhance the 10-year prediction of major adverse cardiovascular events (MACE) in these patients.

Methods: Data from 10,257 to 1,039 patients with type 2 diabetes from the UK Biobank (UKB) and the German ESTHER cohort, respectively, were used for model derivation, internal and external validation.

View Article and Find Full Text PDF

Background: The prevalence of obesity and type 2 diabetes mellitus (T2DM) is rising globally, particularly among children exposed to adverse intrauterine environments, such as those associated with gestational diabetes mellitus (GDM). Epigenetic modifications, specifically DNA methylation, have emerged as mechanisms by which early environmental exposures can predispose offspring to metabolic diseases. This study aimed to investigate DNA methylation differences in children born to mothers with GDM compared to non-GDM mothers, using saliva samples, and to assess the association of these epigenetic patterns with early growth measurements.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!