scholarly journals 1221Baseline Global DNA Hypermethylation Increase the Risk of Cerebrovascular Disease Mortality in Japanese Population

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Yoshiki Tsuboi ◽  
Hiroya Yamada ◽  
Eiji Munetsuna ◽  
Ryosuke Fujii ◽  
Mirai Yamazaki ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Cerebrovascular Disease ◽  
Methylation Status ◽  
Predictive Marker ◽  
Ischemic Heart ◽  
Dna Hypermethylation ◽  
Disease Mortality ◽  
Cvd Mortality

Abstract Background DNA methylation plays an important role in progression of cardiovascular disease (CVD). The methylation status of long interspersed nuclear element-1 (LINE-1) reflects the global DNA methylation level and is associated with lipid profiles and glycemia. We conducted a longitudinal study to examine the association between LINE-1 DNA methylation and CVD mortality in a Japanese elderly population. Methods We targeted for 357 subjects (143 men and 214 women) who were more than 60 years, participated in the health checkup in 1990, and had no clinical history of cancer, stroke, or ischemic heart disease. During 29 years of follow-up period, total 69 subjects were died from CVD, and died of cerebrovascular disease (CBD) and ischemic heart disease (IHD) were 25 and 13, respectively. LINE-1 DNA methylation was measured using PBMCs. We defined the hypermethylation group as greater than median of the LINE-1 DNA methylation levels and hypomethylation group as others. Multivariable Hazard ratios (HRs) for each disease mortality were calculated by the Cox proportional hazard model. We adjusted for age, sex, smoking habits, and alcohol consumption. Results Significantly higher HRs for CVD and CBD mortality were observed in the hypermethylation group compared to the hypomethylation group (CVD: HR 1.67 [95%CI 1.02-2.73], CBD: HR 3.29 [95%CI 1.29-8.40]). However, IHD mortality did not associated with LINE-1 DNA methylation. Conclusions We found that LINE-1 DNA hypermethylation in PBMCs was associated with high CVD mortality, especially CBD mortality. Key messages Higher levels of LINE-1 methylation in PBMCs can be a predictive marker for CBD risk

Trends in Ischemic Heart Disease and Cerebrovascular Disease Mortality in Europe

2021 ◽  
Vol 77 (13) ◽  
pp. 1697-1698
Author(s):  
Matthew Hammond-Haley ◽  
Adam Hartley ◽  
Mohammed Essa ◽  
Augustin J. DeLago ◽  
Dominic C. Marshall ◽  
...  
Keyword(s):  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Cerebrovascular Disease ◽  
Ischemic Heart ◽  
Disease Mortality

Social Vulnerability and Premature Cardiovascular Mortality Among US Counties, 2014 to 2018

Circulation ◽  
2021 ◽  
Vol 144 (16) ◽  
pp. 1272-1279
Author(s):  
Safi U. Khan ◽  
Zulqarnain Javed ◽  
Ahmad N. Lone ◽  
Sourbha S. Dani ◽  
Zahir Amin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Social Vulnerability ◽  
Ischemic Heart ◽  
Relative Risks ◽  
Control And Prevention ◽  
Us Counties ◽  
Social Vulnerabilities ◽  
Cvd Mortality

Background: Substantial differences exist between United States counties with regards to premature (<65 years of age) cardiovascular disease (CVD) mortality. Whether underlying social vulnerabilities of counties influence premature CVD mortality is uncertain. Methods: In this cross-sectional study (2014–2018), we linked county-level CDC/ATSDR SVI (Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry Social Vulnerability Index) data with county-level CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiological Research) mortality data. We calculated scores for overall SVI and its 4 subcomponents (ie, socioeconomic status; household composition and disability; minority status and language; and housing type and transportation) using 15 social attributes. Scores were presented as percentile rankings by county, further classified as quartiles on the basis of their distribution among all US counties (1st [least vulnerable] = 0 to 0.25; 4th [most vulnerable = 0.75 to 1.00]). We grouped age-adjusted mortality rates per 100 000 person-years for overall CVD and its subtypes (ischemic heart disease, stroke, hypertension, and heart failure) for nonelderly (<65 years of age) adults across SVI quartiles. Results: Overall, the age-adjusted CVD mortality rate per 100 000 person-years was 47.0 (ischemic heart disease, 28.3; stroke, 7.9; hypertension, 8.4; and heart failure, 2.4). The largest concentration of counties with more social vulnerabilities and CVD mortality were clustered across the southwestern and southeastern parts of the United States. The age-adjusted CVD mortality rates increased in a stepwise manner from 1st to 4th SVI quartiles. Counties in the 4th SVI quartile had significantly higher mortality for CVD (rate ratio, 1.84 [95% CI, 1.43–2.36]), ischemic heart disease (1.52 [1.09–2.13]), stroke (2.03 [1.12–3.70]), hypertension (2.71 [1.54–4.75]), and heart failure (3.38 [1.32–8.61]) than those in the 1st SVI quartile. The relative risks varied considerably by demographic characteristics. For example, among all ethnicities/races, non-Hispanic Black adults in the 4th SVI quartile versus the 1st SVI quartile exclusively had significantly higher relative risks of stroke (1.65 [1.07–2.54]) and heart failure (2.42 [1.29–4.55]) mortality. Rural counties with more social vulnerabilities had 2- to 5-fold higher mortality attributable to CVD and subtypes. Conclusions: In this analysis, US counties with more social vulnerabilities had higher premature CVD mortality, varied by demographic characteristics and rurality. Focused public health interventions should address the socioeconomic disparities faced by underserved communities to curb the growing burden of premature CVD.

Abstract 325: Readmission among Hospitalized Patients with Non-Valvular Atrial Fibrillation

2012 ◽  
Vol 5 (suppl_1) ◽  
Author(s):  
Karen E Smoyer-Tomic ◽  
Kimberly Siu ◽  
Barbara Johnson ◽  
David R Walker ◽  
Stephen Sander ◽  
...  
Keyword(s):  
Risk Factors ◽  
Atrial Fibrillation ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Cerebrovascular Disease ◽  
Readmission Rate ◽  
Ischemic Heart ◽  
Index Admission ◽  
Readmission Rates ◽  
Diagnosis Codes

Background: An important goal of healthcare reform is reducing the need for hospital readmissions. This study examined readmission rates, reasons for readmissions, and risk factors associated with readmissions in non-valvular atrial fibrillation (NVAF) patients, which may facilitate identification of potential gaps in care. Methods: Patients with AF hospitalizations in any diagnostic position in 2004-2009 were extracted from a large, national commercial and Medicare supplemental administrative claims database. Patients with valvular or transient causes of AF, under the age of 18 years, pregnant, or dead at discharge were excluded from the study. All patients had at least 30 days follow up from the index hospitalization discharge date. Readmission rate within 30 days of discharge date was calculated. Reasons for readmission were reported by ICD-9 diagnosis codes in the primary position. ICD-9 diagnosis codes were grouped into common acute conditions (e.g., ischemic heart disease, cerebrovascular disease) and reported. Logistic regression analyses were conducted to identify risk factors for readmission, controlling for patients’ demographic and clinical characteristics. Results: A total of 6439 patients met the study criteria. The overall 30-day readmission rate was 18.0%. Readmission rates for patients with AF as primary or secondary diagnosis in index admissions were 11.8% and 20.3%, respectively (p<0.001). Readmissions on average occurred 9.7 (SD 9.0) days from index admission discharge, with a mean readmission length of stay (LOS) of 7.4 (SD 8.0) days. The 4 most common grouped diagnoses for readmissions were AF (ICD-9 code 427.31, 10.2% of all readmissions), ischemic heart disease (IHD; 410.xx - 414.xx, 7.2%), heart failure (HF; 428.xx, 7.1%), and cerebrovascular disease (CVD; 430.xx - 438.xx, 6.0%). Longer LOS in the index admission, higher Charlson comorbidity index, and emergency room admission for the index admission all significantly increased the likelihood of having a readmission (p<0.001 in all cases). Patients discharged to home from index admission, patients with AF as primary diagnosis in index admissions, and patients living in the South region were less likely to be readmitted (p<0.01 in all cases). Conclusions: Almost one fifth of patients with NVAF were readmitted within 30 days of discharge. AF, IHD, HF, and CVD were the most common reasons for readmission. Identification of risk factors for readmission may assist healthcare providers in targeting good clinical practice aimed at improving quality of care and reducing the need for readmissions.

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