Heart Disease and Stroke Statistics—2018 Update: A Report From the American Heart Association

Benjamin, Emelia J.; Virani, Salim S.; Callaway, Clifton W.; Chamberlain, Alanna M.; Chang, Alexander R.; Cheng, Susan; Chiuve, Stephanie E; Cushman, Mary; Delling, Francesca N.; Deo, Rajat; Ferranti, Sarah D. de; Ferguson, Jane F.; Fornage, Myriam; Gillespie, Cathleen; Isasi, Carmen R.; Jiménez, Monik C.; Jordan, Lori Chaffin; Judd, Suzanne E.; Lackland, Daniel T.; Lichtman, Judith H.; Lisabeth, Lynda D.; Liu, Simin; Longenecker, Chris T.; Lutsey, Pamela L.; Mackey, Jason; Matchar, David B.; Matsushita, Kunihiro; Mussolino, Michael E.; Nasir, Khurram; O’Flaherty, Martin; Palaniappan, Latha; Pandey, Ambarish; Pandey, Dilip K.; Reeves, Mathew J.; Ritchey, Matthew D.; Rodríguez, Carlos J.; Roth, Gregory A.; Rosamond, Wayne D.; Sampson, Uchechukwu K.A.; Satou, Gary; Shah, Svati H.; Spartano, Nicole L.; Tirschwell, David; Tsao, Connie W.; Voeks, Jenifer H.; Willey, Joshua Z.; Wilkins, John T.; Wu, Jason; Alger, Heather M.; Wong, Sally S.; Muntner, Paul

doi:10.1161/cir.0000000000000558

Cited by 5,485 publications

(3,469 citation statements)

References 2,192 publications

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“…This relationship, however, has not been investigated for PAD. Not all patients with CHD have PAD, so risk factors associated with lower extremity atherosclerosis may be different than for those of CHD 9. Furthermore, the association between obesity and CLI has not been reported previously.…”

Section: Introductionmentioning

confidence: 92%

Associations of Obesity With Incident Hospitalization Related to Peripheral Artery Disease and Critical Limb Ischemia in the ARIC Study

Hicks

Yang

Ndumele

et al. 2018

JAHA

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BackgroundWe conducted an analysis of data from the ARIC (Atherosclerosis Risk in Communities) study to assess the independent association of obesity with peripheral artery disease (PAD) and critical limb ischemia (CLI).Methods and ResultsAll black and white ARIC participants without prevalent PAD at baseline (1987–1989) were included. We used Cox proportional hazards models adjusting for potential confounders and then potential mediators to quantify the association between body mass index (BMI) and incident hospitalizations related to PAD without CLI and with CLI through 2013. Our analysis included 13 988 men and women followed for a median of 24 years. Incident PAD without CLI and PAD with CLI occurred in 373 and 201 participants, respectively. After adjusting for potential confounders, higher BMI at baseline was associated with increased risk of PAD without CLI when BMI was modeled continuously (hazard ratio per 1‐SD increment in BMI: 1.23; 95% confidence interval, 1.11–1.37) and with PAD with CLI regardless of whether BMI was modeled categorically (P<0.05) or continuously (hazard ratio per 1‐SD increment in BMI: 1.51; 95% confidence interval, 1.34–1.69). The associations of BMI with PAD without CLI and with CLI were attenuated after further accounting for potential mediators but remained significant for PAD with CLI when BMI was linearly modeled (hazard ratio per 1‐SD increment in BMI: 1.19; 95% confidence interval, 1.04–1.36). The positive association between BMI and PAD with CLI was stronger than the association between BMI and PAD without CLI for all models (P<0.001).ConclusionsIn the general population, BMI is positively associated with incident hospitalized PAD after adjusting for potential confounders, particularly its most severe form of CLI. Maintaining an optimal weight, in addition to controlling other cardiovascular risk factors, may play a role in reducing risk of PAD with CLI.

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Section: Introductionmentioning

confidence: 92%

Associations of Obesity With Incident Hospitalization Related to Peripheral Artery Disease and Critical Limb Ischemia in the ARIC Study

Hicks

Yang

Ndumele

et al. 2018

JAHA

Self Cite

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“…However, STEMI remains a significant cause of morbidity and mortality in the United States. It is estimated that nearly $12.1 billion US dollars were spent in 2013 for hospital care of STEMI 3, 4. Despite efforts to provide prompt revascularization and optimal medical therapy for those presenting with STEMI, ≈20% of patients were readmitted within 30 days of hospitalization in earlier studies 5.…”

Section: Introductionmentioning

confidence: 99%

Thirty‐Day Readmission Rates, Timing, Causes, and Costs after ST‐Segment–Elevation Myocardial Infarction in the United States: A National Readmission Database Analysis 2010–2014

Kim

Yeo

Cheung

et al. 2018

JAHA

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BackgroundReadmission after ST‐segment–elevation myocardial infarction (STEMI) poses an enormous economic burden to the US healthcare system. Efforts to prevent readmissions should be based on understanding the timing and causes of these readmissions. This study aimed to investigate contemporary causes, timing, and cost of 30‐day readmissions after STEMI.Methods and ResultsAll STEMI hospitalizations were selected in the Nationwide Readmissions Database (NRD) from 2010 to 2014. The 30‐day readmission rate as well as the primary cause and cost of readmission were examined. Multivariate regression analysis was performed to identify the predictors of 30‐day readmission and increased cumulative cost. From 2010 to 2014, the 30‐day readmission rate after STEMI was 12.3%. Within 7 days of discharge, 43.9% were readmitted, and 67.3% were readmitted within 14 days. The annual rate of 30‐day readmission decreased by 19% from 2010 to 2014 (P<0.001). Female sex, AIDS, anemia, chronic kidney disease, collagen vascular disease, diabetes mellitus, hypertension, pulmonary hypertension, congestive heart failure, atrial fibrillation, and increased length of stay were independent predictors of 30‐day readmission. A large proportion of patients (41.6%) were readmitted for noncardiac reasons. After multivariate adjustment, 30‐day readmission was associated with a 47.9% increase in cumulative cost (P<0.001).ConclusionsTwo thirds of patients were readmitted within the first 14 days after STEMI, and a large proportion of patients were readmitted for noncardiac reasons. Thirty‐day readmission was associated with an ≈50% increase in cumulative hospitalization costs. These findings highlight the importance of closer surveillance of both cardiac and general medical conditions in the first several weeks after STEMI discharge.

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“…The ongoing increase in prevalence of type 2 diabetes mellitus (T2DM), affecting 9% of US adults,1, 2 has impeded public health efforts to slow the incidence of cardiovascular disease (CVD) 3, 4, 5. Individuals with T2DM but without prior CVD are at similar risk for myocardial infarction as those with current CVD but without T2DM,6 such that in prompting treatment with lipid‐lowering agents, T2DM has been considered a coronary heart risk equivalent 7.…”

Section: Introductionmentioning

confidence: 99%

Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores

Gurka

Filipp

Pearson

et al. 2018

JAHA

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BackgroundType 2 diabetes mellitus (T2DM) is considered a cardiovascular disease (CVD) risk equivalent, thereby linking assessment of cardiometabolic risk with that of CVD risk over time. Our goal was to determine how commonly used CVD risk scores and metabolic syndrome (MetS) severity performed in predicting T2DM with and without ultimate CVD.Methods and ResultsWe assessed data from 8273 participants of the ARIC (Atherosclerosis Risk in Communities) Study, using the pooled cohort atherosclerotic CVD risk score, the Framingham Risk Score, and a MetS severity Z score to assess their association with future risk for CVD alone, T2DM alone, or both over 20 years of follow‐up. Baseline levels of all scores were significantly associated with isolated incident T2DM (odds ratios [ORs] for each 1‐SD increase: atherosclerotic CVD=1.7, Framingham risk score=1.7, MetS Z score=5.1). All 3 baseline scores were also significantly associated with isolated incident CVD (atherosclerotic CVD OR=2.4, Framingham risk score OR=2.3, MetS Z‐score OR=1.8), with the 2 CVD scores remaining significant independent of MetS severity. MetS severity was strongly associated with future T2DM leading to CVD (MetS Z‐score OR=7.0, atherosclerotic CVD OR=3.9, Framingham risk score OR=3.5). Furthermore, changes in MetS severity were independently associated with future T2DM‐CVD progression.Conclusions CVD risk scores are associated with risk for future isolated T2DM in addition to isolated CVD. However, MetS severity (both baseline and changes over time) was more strongly associated with T2DM, including T2DM ultimately leading to CVD. Following MetS severity within patients over time may identify those at greatest risk of combined cardiometabolic disease.

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Heart Disease and Stroke Statistics—2018 Update: A Report From the American Heart Association

Cited by 5,485 publications

References 2,192 publications

Associations of Obesity With Incident Hospitalization Related to Peripheral Artery Disease and Critical Limb Ischemia in the ARIC Study

Associations of Obesity With Incident Hospitalization Related to Peripheral Artery Disease and Critical Limb Ischemia in the ARIC Study

Thirty‐Day Readmission Rates, Timing, Causes, and Costs after ST‐Segment–Elevation Myocardial Infarction in the United States: A National Readmission Database Analysis 2010–2014

Assessing Baseline and Temporal Changes in Cardiometabolic Risk Using Metabolic Syndrome Severity and Common Risk Scores

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