scholarly journals Trends in Premature Mortality From Acute Myocardial Infarction in the United States, 1999 to 2019

2021 ◽  
Author(s):  
Sourbha S. Dani ◽  
Ahmad N. Lone ◽  
Zulqarnain Javed ◽  
Muhammad S. Khan ◽  
Muhammad Zia Khan ◽  
...  
Keyword(s):  
United States ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Mortality Rate ◽  
The United States ◽  
Mortality Rates ◽  
Percentage Change ◽  
Annual Percentage Change ◽  
Rural Counties ◽  
Average Annual Percentage Change

Background Evaluating premature (<65 years of age) mortality because of acute myocardial infarction (AMI) by demographic and regional characteristics may inform public health interventions. Methods and Results We used the Centers for Disease Control and Prevention’s WONDER (Wide‐Ranging Online Data for Epidemiologic Research) death certificate database to examine premature (<65 years of age) age‐adjusted AMI mortality rates per 100 000 and average annual percentage change from 1999 to 2019. Overall, the age‐adjusted AMI mortality rate was 13.4 (95% CI, 13.3–13.5). Middle‐aged adults, men, non‐Hispanic Black adults, and rural counties had higher mortality than young adults, women, NH White adults, and urban counties, respectively. Between 1999 and 2019, the age‐adjusted AMI mortality rate decreased at an average annual percentage change of −3.4 per year (95% CI, −3.6 to −3.3), with the average annual percentage change showing higher decline in age‐adjusted AMI mortality rates among large (−4.2 per year [95% CI, −4.4 to −4.0]), and medium/small metros (−3.3 per year [95% CI, −3.5 to −3.1]) than rural counties (−2.4 per year [95% CI, −2.8 to −1.9]). Age‐adjusted AMI mortality rates >90th percentile were distributed in the Southern states, and those with mortality <10th percentile were clustered in the Western and Northeastern states. After an initial decline between 1999 and 2011 (−4.3 per year [95% CI, −4.6 to −4.1]), the average annual percentage change showed deceleration in mortality since 2011 (−2.1 per year [95% CI, −2.4 to −1.8]). These trends were consistent across both sexes, all ethnicities and races, and urban/rural counties. Conclusions During the past 20 years, decline in premature AMI mortality has slowed down in the United States since 2011, with considerable heterogeneity across demographic groups, states, and urbanicity. Systemic efforts are mandated to address cardiovascular health disparities and outcomes among nonelderly adults.

scholarly journals Trends in Cardiovascular Mortality Related to Atrial Fibrillation in the United States, 2011 to 2018

2021 ◽  
Author(s):  
Yoshihiro Tanaka ◽  
Nilay S. Shah ◽  
Rod Passman ◽  
Philip Greenland ◽  
Donald M. Lloyd‐Jones ◽  
...  
Keyword(s):  
United States ◽  
Atrial Fibrillation ◽  
Mortality Rate ◽  
Cause Of Death ◽  
Cardiovascular Mortality ◽  
The United States ◽  
Percentage Change ◽  
Annual Percentage Change ◽  
Cardiovascular Morbidity And Mortality ◽  
Average Annual Percentage Change

Background Prevalence of atrial fibrillation (AF) continues to increase and is associated with significant cardiovascular morbidity and mortality. To inform prevention strategies aimed at reducing the burden of AF, we sought to quantify trends in cardiovascular mortality related to AF in the United States. Methods and Results We performed serial cross‐sectional analyses of national death certificate data for cardiovascular mortality related to AF, whereby cardiovascular disease was listed as underlying cause of death and AF as multiple cause of death among adults aged 35 to 84 years using the Centers for Disease Control and Prevention's Wide‐Ranging Online Data for Epidemiologic Research. We calculated age‐adjusted mortality rates per 100 000 population and examined trends over time, estimating average annual percentage change using the Joinpoint Regression Program. Subgroup analyses were performed by race‐sex and across 2 age groups (younger: 35–64 years; older: 65–84 years). A total of 276 373 cardiovascular deaths related to AF were identified in the United States between 2011 and 2018 in decedents aged 35 to 84 years. Age‐adjusted mortality rate increased from 18.0 (95% CI, 17.8–18.2) to 22.3 (95% CI, 22.0–22.4) per 100 000 population between 2011 and 2018. The increase in age‐adjusted mortality rate (average annual percentage change) between 2011 and 2018 was greater among younger decedents (7.4% per year [95% CI, 6.8%–8.0%]) compared with older decedents (3.0% per year [95% CI, 2.6%–3.4%]). Conclusions Cardiovascular deaths related to AF are increasing, especially among younger adults, and warrant greater attention to prevention earlier in the life course.

Abstract 223: National and Regional Trends in Hospitalizations for Hemorrhagic Stroke after Acute Myocardial Infarction in the United States: 1999-2010

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Ruizhi Shi ◽  
Yun Wang ◽  
Judith H Lichtman ◽  
Kumar Dharmarajan ◽  
Frederick A Masoudi ◽  
...  
Keyword(s):  
United States ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Hemorrhagic Stroke ◽  
Temporal Trends ◽  
The United States ◽  
Mortality Rates ◽  
Hospitalization Rates ◽  
One Year ◽  
Stroke Belt

Background: Elderly survivors of acute myocardial infarction (AMI) are at elevated risk for hemorrhagic stroke, which has a mortality rate of approximately 50%. Increasing use of warfarin for arterial fibrillation and anti-platelet agents for AMI combined with an increasing aging population may have influenced the risk of post-AMI strokes. We sought to characterize temporal trends in the risk for and mortality from hemorrhagic stroke over 12 years among older AMI survivors of different age, sex, race, revascularization status, and region within the US. Methods: We used 100% of Medicare inpatient claims data to identify all fee-for-service (FFS) patients aged> 64 years who were hospitalized for AMI in 1999-2010. We excluded patients who died during the hospitalization or were transferred. Revascularization procedures were identified during the index admission. We used a Cox proportional-hazards regression model to estimate the risk-adjusted annual changes in one-year hemorrhagic stroke hospitalization after AMI, overall and by subgroups. Changes were adjusted by age, gender, race, medical history and comorbidities. We calculated the 30-day mortality among patients readmitted for hemorrhagic stroke. Stroke belt regions were defined as the states with high stroke hospitalization rates in the southeast United States. Results: Among 2,433,036 AMI hospitalizations and 4,852 hemorrhagic stroke readmissions, the risk-adjusted one-year post-AMI hemorrhagic stroke rate remained stable from 1999 to 2010 (range, 0.2% to 0.3%). No significant trends were found for post-AMI stroke rates across all age-sex-race groups and all treatment groups (Figure). Thirty-day mortality rates for stroke after AMI did not show significant changes (1999, 46.7%, 95% CI 39.9%-53.7%; 2010, 50.7%, 95% CI 45.3%-56.1%; range: 46.5% to 54.6%). No difference was found in post-AMI hemorrhagic stroke rates between the stroke belt and non-stroke belt regions. Conclusions: From 1999 to 2010, the overall hospitalization rates of hemorrhagic stroke after AMI were relatively stable without significant changes across all subgroups. Thirty-day mortality rates remained largely unchanged over time. Stroke risk in the stroke belt was not found significantly higher comparing with non-stroke belt states.

Abstract 14: Regional Cardiologist Density and 30-Day and 1-Year Mortality in Acute Myocardial Infarction and Heart Failure

2013 ◽  
Vol 6 (suppl_1) ◽  
Author(s):  
Vivek T Kulkarni ◽  
Joseph S Ross ◽  
Yongfei Wang ◽  
Brahmajee K Nallamothu ◽  
John A Spertus ◽  
...  
Keyword(s):  
United States ◽  
Myocardial Infarction ◽  
Heart Failure ◽  
Acute Myocardial Infarction ◽  
The United States ◽  
Mortality Rates ◽  
Lower Mortality ◽  
Administrative Claims ◽  
Physician Density ◽  
Hospital Referral

Background: Although the distribution of cardiologists and mortality for cardiovascular conditions are both known to vary across regions of the United States, no study has examined the relationship between regional cardiologist density and patient mortality for acute myocardial infarction (AMI) or heart failure (HF). Methods: We used 2010 Medicare administrative claims data for AMI and HF. Pneumonia (PN) was used as a control condition. Primary outcomes were death at 30 days and 1 year from admission. For each Hospital Referral Region (HRR), we used the 2010 Bureau of Health Professionals’ Area Resource File to define cardiologist density (number of cardiologists divided by population aged 65+) and 4 HRR characteristics: primary care physician density, total physician density, unemployment rate, and percent white race. We used 2-level hierarchical logistic regression models to examine the association between cardiologist density by tertile and mortality for each condition adjusting for (Model A) patient age, sex, and condition-specific comorbidities, and (Model B) patient and HRR characteristics. Results: Median (interquartile range) cardiologist density per 100,000 in the low, middle, and high tertiles of HRRs was 26.3 (22.9-29.9), 38.6 (36.5-43.1), and 64.5 (54.4-85.3), respectively. There were 171,126 admissions for AMI, 352,853 for HF, and 343,053 for PN. The 30-day mortality rates were 15.3% (26,290), 11.7% (41,121), and 11.9% (40,906), and 1-year mortality rates were 32.1% (55,292), 40.4% (142,612), and 35.2% (120,666), respectively (Table). For 30-day mortality, while model A showed lower mortality with higher cardiologist density for all conditions (odds ratios (ORs): 0.84-0.95), model B showed no associations. For 1-year mortality, while model A showed lower mortality in the high cardiologist density tertile for AMI (OR=0.93) and HF (OR=0.91) and no associations for PN, model B showed no associations for AMI or HF and higher mortality with higher cardiologist density for PN (ORs=1.04-1.06). Conclusion: After adjusting for patient and HRR characteristics, regional cardiologist density was not associated with 30-day or 1-year mortality for AMI or HF, suggesting that the uneven regional distribution of cardiologists across the United States does not affect patient outcomes.

scholarly journals Gender Differences in In-Hospital Mortality Rates among Hispanic Patients with Acute Myocardial Infarction

2017 ◽  
Vol 4 (r) ◽  
Author(s):  
Nawaf Ebrahim Al-Jeraisy ◽  
Abdullah M. Al-Sultan ◽  
Sami A. Aldaham
Keyword(s):  
United States ◽  
Myocardial Infarction ◽  
Acute Myocardial Infarction ◽  
Hospital Mortality ◽  
The United States ◽  
Mortality Rates ◽  
Hospital Death ◽  
P Value ◽  
Factors Associated ◽  
Hispanic Patients

Acute myocardial infarction (AMI) is a leading cause of death in the United States with over three million cases per year. Since the mid-1970s, the total number of deaths related to AMI in the United States has not declined. Studies suggest that women with AMI have worse outcomes compared to men. However, there is limited information regarding this topic among Hispanics. This study was a secondary analysis of the Puerto Rican Heart Attack Study, which reviewed the records of Hispanic patients of Puerto Rico hospitalized for AMI at 21 academic and/or non-teaching hospitals in 2007, 2009 and 2011. This study set examined the differences in in-hospital mortality rates between genders. A p-value of 0.2 was used to select possible confounders and the chi-square test was used to examine associations between categorical variables. Factors associated with in-hospital mortality rates were identified using logistic regression. Collinearity was assessed using Pearson correlation coefficients. The 95% confidence interval and a p-value of 0.05 were used to determine statistical significance of odds ratios. Analysis was restricted to patients with ICD-9-CM code 410-414 who are above 18 (n = 2265). In our sample, there were more men than women (1291 versus 974, respectively). Men were younger and smoked more compared to women. Compared to men, women were older and suffered more comorbidities, such as stroke and congestive heart failure (CHF). Women had higher rates of in-hospital mortality compared to men (OR = 1.4, p = 0.040). Factors associated with higher rates of in-hospital mortality included age and CHF (p<0.001). Patients with CHF showed higher rates of in-hospital deaths compared to patients who did not have CHF (OR = 1.6, p = 0.026). Patients over the age of 86 showed higher odds of in-hospital death compared to younger patients (OR = 10.5, p <0.001) Significant disparities existed by gender in this sample of Hispanic AMI patients, with women showing higher in-hospital mortality compared to men. Women over 50 should perform regular checkups and discuss hormone replacement therapy or follow other preventive measures as suggested by their healthcare provider.

scholarly journals Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Joshua J. Levy ◽  
Rebecca M. Lebeaux ◽  
Anne G. Hoen ◽  
Brock C. Christensen ◽  
Louis J. Vaickus ◽  
...  
Keyword(s):  
United States ◽  
Deep Learning ◽  
Mortality Rate ◽  
Satellite Images ◽  
The United States ◽  
Mortality Rates ◽  
Image Features ◽  
County Level ◽  
Crude Mortality Rate ◽  
Crude Mortality

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

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