Background: The objective of this research is to clarify the impact of periodontitis on overall and cardiovascular-related death rates among hypertensive individuals.
Method: A total of 5665 individuals with hypertension were included from the National Health and Nutrition Examination Survey (NHANES) data spanning 2001-2004 and 2009-2014. These individuals were divided into two groups based on the presence or absence of periodontitis and further stratified by the severity of periodontitis. We employed weighted multivariate Cox proportional hazards regression and Kaplan-Meier curves (log-rank test) to evaluate the impact of periodontitis on all-cause and cardiovascular mortality. Additional analyses, including adjustments for various covariates, subgroups, and sensitivity analyses, were conducted to ensure the robustness and reliability of our results.
Result: Over an average follow-up duration of 10.22 years, there were 1,122 all-cause and 297 cardiovascular deaths. Individuals with periodontitis exhibited an elevated risk of all-cause mortality (HR = 1.33, 95% CI 1.18-1.51; p < 0.0001) and cardiovascular mortality (HR = 1.48, 95% CI 1.15-1.89; p = 0.002). Moreover, we observed a progressive increase in both all-cause mortality and cardiovascular mortality (p for trend are both lower than 0.001) and correlating with the severity of periodontitis. These associations remained consistent across various subgroup and sensitivity analyses.
Conclusion: Our findings suggest a significant association between periodontitis and increased risks of all-cause and cardiovascular mortality among hypertensive individuals. Notably, the severity of periodontitis appears to be a critical factor, with moderate to severe cases exerting a more pronounced impact on all-cause mortality. Additionally, cardiovascular disease mortality significantlly increases in individuals with varying degrees of periodontitis.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11328503 | PMC |
| http://dx.doi.org/10.1186/s12903-024-04708-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Association of frailty with cardiovascular and all-cause mortality in community-dwelling older adults: insights from the Chinese longitudinal healthy longevity survey.
Front Cardiovasc Med
December 2024
Department of Hypertension, Henan Provincial People's Hospital, Zhengzhou, China.
Background: Previous studies suggest that frailty increases the risk of mortality, but the risk of cardiovascular disease (CVD) and all-cause mortality in Chinese community-dwelling older adults remains understudied. Our aim was to explore the effect of frailty on cardiovascular and all-cause mortality in older adults based on a large-scale prospective survey of community-dwelling older adults in China.
Methods: We utilized the 2014-2018 cohort of the Chinese Longitudinal Healthy Longevity Survey and constructed a frailty index (FI) to assess frailty status.
A non-linear association of low-density lipoprotein cholesterol with all-cause and cardiovascular mortality among patients with hypertension.
Front Cardiovasc Med
December 2024
Department of Cardiovascular Medicine, Fengxian District Central Hospital, Shanghai, China.
Background: Although a few studies have examined the correlation between low-density lipoprotein cholesterol (LDL-C) and mortality, no study has explored these associations in hypertensive populations. This study aims to investigate the relationship between low-density lipoprotein cholesterol and cardiovascular and all-cause mortality in adults with hypertension.
Methods: Hypertensive participants aged ≥18 years from the National Health and Nutrition Examination Survey 1999-2018 with blood lipid testing data and complete follow-up data until 31 December 2019 were enrolled in the analysis.
Trustworthiness of a machine learning early warning model in medical and surgical inpatients.
JAMIA Open
February 2025
Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, United States.
Objectives: In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.
Materials And Methods: We assessed the scores of an EWS integrated into the electronic health record and calculated every 15 minutes to predict a composite adverse event (AE): all-cause mortality, transfer to intensive care, cardiac arrest, or rapid response team evaluation.
Differentiated service delivery (DSD) models in resource-limited settings have reduced strain on health services and improved client experience, retention and viral suppression, but little is known about the impact of HIV DSD models on quality of life (QoL), which is essential for optimizing person-centered care. This study assessed the impact of DSD models on QoL, loss to follow-up (LTFU), and mortality among persons living with HIV (PLHIV) on ART over time at a large urban HIV clinic in Uganda. We analyzed records of 1,000 PLHIV who had been on ART for 10 years and followed up for eight years, starting in 2014 or 2015 at the Infectious Diseases Institute clinic in Kampala, Uganda.
View Article and Find Full Text PDFAnalysis of the correlation between the serum triglyceride glucose index and the risk of death in patients on maintenance hemodialysis: a retrospective cohort study.
PeerJ
January 2025
Department of Nephrology, Blood Purification Research Center, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Background: Patients with end-stage renal disease (ESRD) have increased insulin resistance (IR). The triglyceride glucose (TyG) index is a marker of IR and is associated with the prognosis of patients on maintenance hemodialysis (MHD). The aim of this study was to examine the relationship between the TyG index and the risk of death in patients on MHD.
View Article and Find Full Text PDFWant 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!