Heart Failure After Myocardial Infarction Is Associated With Increased Risk of Cancer

BACKGROUND

Heart failure (HF) is associated with excess morbidity and mortality for which noncardiac causes are increasingly recognized. The authors previously described an increased risk of cancer among HF patients compared with community controls.

OBJECTIVES

This study examined whether HF was associated with an increased risk of subsequent cancer among a homogenous population of first myocardial infarction (MI) survivors.

METHODS

A prospective cohort study was conducted among Olmsted County, Minnesota, residents with incident MI from 2002 to 2010. Patients with prior cancer or HF diagnoses were excluded.

RESULTS

A total of 1,081 participants (mean age 64 ± 15 years; 60% male) were followed for 5,327 person-years (mean 4.9 ± 3.0 years). A total of 228 patients developed HF, and 98 patients developed cancer (excluding nonmelanoma skin cancer). Incidence density rates for cancer diagnosis (per 1,000 person-years) were 33.7 for patients with HF and 15.6 for patients without HF (p = 0.002). The hazard ratio (HR) for cancer associated with HF was 2.16 (95% confidence interval [CI]: 1.39 to 3.35); adjusted for age, sex, and Charlson comorbidity index; HR: 1.71 (95% CI: 1.07 to 2.73). The HRs for mortality associated with cancer were 4.90 (95% CI: 3.10 to 7.74) for HF-free and 3.91 (95% CI: 1.88 to 8.12) for HF patients (p for interaction = 0.76).

CONCLUSIONS

Patients who develop HF after MI have an increased risk of cancer. This finding extends our previous report of an elevated cancer risk after HF compared with controls, and calls for a better understanding of shared risk factors and underlying mechanisms.

Epidemiology of heart failure with preserved ejection fraction

Heart failure (HF) with preserved ejection fraction (HFpEF) is a clinical syndrome associated with poor quality of life, substantial health-care resource utilization, and premature mortality. We summarize the current knowledge regarding the epidemiology of HFpEF with a focus on community-based studies relevant to quantifying the population burden of HFpEF. Current data regarding the prevalence and incidence of HFpEF in the community as well as associated conditions and risk factors, risk of morbidity and mortality after diagnosis, and quality of life are presented. In the community, approximately 50% of patients with HF have HFpEF. Although the age-specific incidence of HF is decreasing, this trend is less dramatic for HFpEF than for HF with reduced ejection fraction (HFrEF). The risk of HFpEF increases sharply with age, but hypertension, obesity, and coronary artery disease are additional risk factors. After adjusting for age and other risk factors, the risk of HFpEF is fairly similar in men and women, whereas the risk of HFrEF is much lower in women. Multimorbidity is common in both types of HF, but slightly more severe in HFpEF. A majority of deaths in patients with HFpEF are cardiovascular, but the proportion of noncardiovascular deaths is higher in HFpEF than HFrEF.

Skilled Nursing Facility Use and Hospitalizations in Heart Failure: A Community Linkage Study

OBJECTIVES

To examine the effect of skilled nursing facility (SNF) use on hospitalizations in patients with heart failure (HF) and to examine predictors of hospitalization in patients with HF admitted to a SNF.

PATIENTS AND METHODS

Olmsted County, Minnesota, residents with first-ever HF from January 1, 2000, through December 31, 2010, were identified, and clinical data were linked to SNF utilization data from the Centers for Medicare and Medicaid Services. Andersen-Gill models were used to determine the association between SNF use and hospitalizations and to determine predictors of hospitalization.

RESULTS

Of 1498 patients with incident HF (mean ± SD age, 75±14 years; 45% male), 605 (40.4%) were admitted to a SNF after HF diagnosis (median follow-up, 3.6 years; range, 0-13.0 years). Of those with a SNF admission, 225 (37%) had 2 or more admissions. After adjustment for age, sex, ejection fraction, and comorbidities, SNF use was associated with a 50% increased risk of hospitalization compared with no SNF use (adjusted hazard ratio, 1.52; 95% CI, 1.31-1.76). In SNF users, arrhythmia, asthma, chronic kidney disease, and the number of activities of daily living requiring assistance were independently associated with an increased risk of hospitalization.

CONCLUSION

Approximately 40% of patients with HF were admitted to a SNF at some point after diagnosis. Compared with SNF nonusers, SNF users were more likely to be hospitalized. Characteristics associated with hospitalization in SNF users were mostly noncardiovascular, including reduced ability to perform activities of daily living. These findings underscore the effect of physical functioning on hospitalizations in patients with HF in SNFs and the importance of strategies to improve physical functioning.

Burden and Timing of Hospitalizations in Heart Failure: A Community Study

OBJECTIVE

To study the temporal distribution and causes of hospitalizations after heart failure (HF) diagnosis.

PATIENTS AND METHODS

Hospitalizations were studied in 1972 Olmsted County, Minnesota, residents with incident HF from January 1, 2000, to December 31, 2011. All hospitalizations were examined for the 2 years following incident HF, and each was categorized as due to HF, other cardiovascular causes, or noncardiovascular causes. Negative binomial regression examined associations between time periods (0-30, 31-182, 183-365, and 366-730 days after diagnosis) and hospitalizations.

RESULTS

During the 2 years after diagnosis, 3495 hospitalizations were observed among 1336 of the 1972 patients with HF. The age- and sex-adjusted rates of hospitalizations were highest in the first 30 days after diagnosis (3.33 per person-year vs 1.33, 1.07, and 1.00 per person-year for 31-182 days, 183-365 days, and 366-730 days, respectively). The rates of hospitalizations were similar across sex, presentation of HF (inpatient or outpatient), and type of HF (preserved or reduced ejection fraction). Patients diagnosed as inpatients who had long hospital stays (>5 days) experienced more than a 30% increased risk of rehospitalization within 30 days of dismissal. Importantly, most hospitalizations (2222 of 3495 [63.6%]) were due to noncardiovascular causes, and a minority (440 of 3495 [12.6%]) were due to HF. The rates of noncardiovascular hospitalizations were higher than those for HF or other cardiovascular hospitalizations across all follow-up for all time periods after HF.

CONCLUSION

Patients with HF experience high rates of hospitalizations, particularly within the first 30 days, and mostly for noncardiovascular causes. To reduce hospitalizations in patients with HF, an integrated approach focusing on comorbidities is required.

No decline in the risk of heart failure after incident atrial fibrillation: A community study assessing trends overall and by ejection fraction

BACKGROUND

Patients with atrial fibrillation (AF) experience an increased risk of heart failure (HF). However, data are lacking on current trends in the risk of HF after AF.

OBJECTIVE

The purpose of this study was to describe the temporal trends in HF occurrence after AF in a community cohort of patients with incident AF from 2000 to 2013.

METHODS

Cox regression was used to examine the association of year of AF diagnosis with HF and the predictors of developing HF after AF.

RESULTS

Among 3491 AF patients without prior HF, 750 (21%) developed incident HF over mean follow-up of 3.7 years. Among those with an echocardiogram, 422 (61%) had HF with preserved ejection fraction (HFpEF), and 270 (39%) had HF with reduced ejection fraction (HFrEF). After adjusting for demographics and comorbidities, the risk of developing HF did not change over time (hazard ratio [HR] (95% confidence interval [CI]) per year of AF diagnosis: 1.01 (0.98-1.03) overall; 1.00 (0.98-1.03) for HFpEF; 1.00 (0.96-1.03) for HFrEF). Increasing age, obesity, smoking, diabetes, chronic pulmonary disease, and renal disease were predictors of developing HF. Compared to the Olmsted County, Minnesota, population, a substantial excess risk of developing HF was observed after AF diagnosis [standardized morbidity ratio (95% CI): 9.60 (7.44-12.19), 2.13 (1.56-2.84), and 1.70 (1.34-2.14) at 90 days, 1 year, and 3 years after diagnosis].

CONCLUSION

In the community, HF is a frequent adverse outcome among patients with AF, and HFpEF is more common than HFrEF. The rates of HF after AF have not declined, thus highlighting the importance of continued efforts to improve outcomes in AF.

Comorbid Depression and Heart Failure: A Community Cohort Study

Objective

To examine the association between depression and clinical outcomes in heart failure (HF) in a community cohort.

Patients and Methods

HF patients in Minnesota, United States completed depression screening using the 9-item Patient Health Questionnaire (PHQ-9) between 1^st Oct 2007 and 1^st Dec 2011; patients with PHQ-9≥5 were labelled “depressed”. We calculated the risk of death and first hospitalization within 2 years using Cox regression. Results were adjusted for 10 commonly used prognostic factors (age, sex, systolic blood pressure, estimated glomerular filtration rate, serum sodium, ejection fraction, blood urea nitrogen, brain natriuretic peptide, presence of diabetes and ischaemic aetiology). Area under the curve (AUC), integrated discrimination improvement (IDI) and net reclassification improvement (NRI) compared depression as a predictor against the aforementioned factors.

Results

425 patients (mean age 74, 57.6% males) were included in the study; 179 (42.1%) had PHQ-9≥5. The adjusted hazard ratio of death was 2.02 (95% CI 1.34–3.04) and of hospitalization was 1.42 (95% CI 1.13–1.80) for those with compared to those without depression. Adding depression to the models did not appreciably change the AUC but led to statistically significant improvements in both the IDI (p = 0.001 and p = 0.005 for death and hospitalization, respectively) and NRI (for death and hospitalization, 35% (p = 0.002) and 27% (p = 0.007) were reclassified correctly, respectively).

Conclusion

Depression is frequent among community patients with HF and associated with increased risk of hospitalizations and death. Risk prediction for death and hospitalizations in HF patients can be improved by considering depression.

Frailty Trajectories in an Elderly Population-Based Cohort

OBJECTIVES

To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all-cause mortality.

DESIGN

Population-based cohort study.

SETTING

Olmsted County, Minnesota.

PARTICIPANTS

Olmsted County, Minnesota residents aged 60-89 in 2005.

MEASUREMENTS

Longitudinal changes in frailty between 2005 and 2012 were measured by constructing a yearly Rockwood frailty index incorporating body mass index, 17 comorbidities, and 14 activities of daily living. The frailty index measures variation in health status as the proportion of deficits present of the 32 considered (range 0-1).

RESULTS

Of the 16,443 Olmsted County residents aged 60-89 in 2005, 12,270 (74.6%) had at least 3 years of frailty index measures and were retained for analysis. The median baseline frailty index increased with age (0.11 for 60-69, 0.14 for 70-79, 0.19 for 80-89). Three distinct frailty trajectories were identified in individuals aged 60-69 at baseline and two trajectories in those aged 70-79 and 80-89. Within each decade of age, increasing frailty trajectories were associated with greater risks of emergency department visits, hospitalization, and all-cause mortality, even after adjustment for baseline frailty index.

CONCLUSION

The number of frailty trajectories differed according to age. Within each age group, those in the highest frailty trajectory had greater healthcare use and worse survival. Frailty trajectories may offer a way to target aging individuals at high risk of hospitalization or death for therapeutic or preventive interventions.

Multimorbidity in Heart Failure: Effect on Outcomes

OBJECTIVES

To investigate the effect of the number and type of comorbid conditions on death and hospitalizations in individuals with incident heart failure (HF).

DESIGN

Population-based cohort study.

SETTING

Olmsted County, Minnesota.

PARTICIPANTS

Olmsted County, Minnesota, residents with incident HF from 2000 to 2010 (mean age 76 ± 14, 56% female) (N = 1,714).

MEASUREMENTS

The prevalence of 16 chronic conditions obtained at HF diagnosis classified into three groups: cardiovascular (CV) related, other physical, and mental.

RESULTS

The mean number of conditions per participant was 2.6 ± 1.5 for CV-related conditions, 1.3 ± 1.1 for other physical conditions, and 0.30 ± 0.61 for mental conditions. After a mean follow-up of 4.2 years, 1,073 deaths and 6,306 hospitalizations had occurred. After adjustment for age, sex, ejection fraction, in- or outpatient status, and number of other conditions, an increase of one other physical condition was associated with a 14% (HR = 1.14, 95% CI = 1.08-1.20) greater risk of death and a 26% (HR = 1.26, 95% CI = 1.20-1.32) greater risk of hospitalization, and an increase of one mental condition was associated with a 31% (HR = 1.31, 95% CI = 1.19-1.44) greater risk of death and an 18% (HR = 1.18, 95% CI = 1.07-1.29) greater risk of hospitalization. In contrast, an increase of one CV-related condition was not associated with greater risk of death and was associated with a 10% (HR = 1.10, 95% CI = 1.06-1.15) greater risk of hospitalization.

CONCLUSION

CV-related conditions are the most common type of comorbid conditions in individuals with HF, but other physical and mental conditions are more strongly associated with death and hospitalizations. This underscores the effect of non-CV conditions on outcomes in HF.

No Decline in the Risk of Stroke Following Incident Atrial Fibrillation Since 2000 in the Community: A Concerning Trend

Background

While atrial fibrillation is a recognized risk factor for stroke, contemporary data on trends in stroke incidence after the diagnosis of atrial fibrillation are scarce.

Methods and Results

Olmsted County, MN residents with incident atrial fibrillation or atrial flutter (collectively referred to as AF) from 2000 to 2010 were identified. Cox regression determined associations of year of AF diagnosis with ischemic stroke and transient ischemic attack (TIA) occurring through 2013. Among 3247 AF patients, 321 (10%) had an ischemic stroke/TIA over a mean of 4.6 years (incidence rate [95% CI] per 100 person‐years: 2.14 [1.91–2.38]). Two hundred thirty‐nine (7%) of 3265 AF patients experienced an ischemic stroke (incidence rate: 1.54 [1.35–1.75]). The risk of both outcomes remained unchanged over time after adjusting for demographics and comorbidities (hazard ratio [95% CI] per year of AF diagnosis: 1.00 [0.96–1.04] for ischemic stroke/TIA; 1.01 [0.96–1.06] for ischemic stroke only). In analyses restricted to patients with prescription information, the rates of anticoagulation use did not change over time, reaching 50.8% at 1 year after AF diagnosis. Further adjustment for anticoagulation use did not alter the temporal trends in stroke incidence (hazard ratio [95% CI] per year of AF diagnosis: 1.06 [0.97–1.15] for ischemic stroke/TIA; 1.08 [0.98–1.20] for ischemic stroke only).

Conclusions

Strokes/TIAs are frequent after AF, occurring in 10% of patients after 5 years of follow‐up. The occurrence of stroke/TIA did not decline over the last decade, which may be influenced by a leveling off of anticoagulation use. This concerning trend has major public health implications.

Sauver JL, Jacobson DJ, Manemann SM, Fan C, Roger VL, Yawn BP, Finney Rutten LJ. Social and behavioural factors associated with frailty trajectories in a population-based cohort of older adults

OBJECTIVE

The goal of this study was to identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an ageing population and to determine social and behavioural factors associated with frailty trajectories.

DESIGN

Population-based cohort study.

SETTING

Olmsted County, Minnesota.

PARTICIPANTS

Olmsted County, Minnesota residents aged 60-89 in 2005.

PRIMARY OUTCOME MEASURE

Changes in frailty over an 8-year period from 2005 to 2012, measured by constructing a yearly frailty index. Frailty trajectories by decade of age were determined using k-means cluster modelling for longitudinal data.

RESULTS

After adjustment for age and sex, all social and behavioural factors (education, marital status, living arrangements, smoking status and alcohol use) were significantly associated with frailty trajectories in those aged 60-69 and 70-79 years. After further adjustment for baseline frailty, the likelihood of being in the high frailty trajectory was greatest among those reporting concerns from relatives/friends about alcohol consumption (OR (95% CI) 2.26 (1.19 to 4.29)) and those with less than a high school education (OR (95% CI) 1.98 (1.32 to 2.96)) in the 60-69 year olds. In the 70-79 year olds, the largest associations were observed among those with concerns from oneself about alcohol consumption (OR (95% CI) 1.92 (1.23 to 3.00)), those with less than a high school education (OR (95% CI) 1.57 (1.12 to 2.22)), and those living with family (vs spouse; OR (95% CI) 1.76 (1.05 to 2.94)). No factors remained associated with frailty trajectories in the 80-89 year olds after adjustment for baseline frailty.

CONCLUSIONS

Social and behavioural factors are associated with frailty, with stronger associations observed in younger ages. Recognition of social and behavioural factors associated with increasing frailty may inform interventions for individuals at risk of worsening frailty, specifically when targeted at younger individuals.

Long-term risk of myocardial infarction and stroke in bipolar I disorder: A population-based Cohort Study

OBJECTIVES

To estimate the risk of fatal and non-fatal myocardial infarction (MI) and stroke in patients with bipolar I disorder compared to people without bipolar I disorder.

METHOD

Utilizing a records-linkage system spanning 30 years (1966-1996), a population-based cohort of 334 subjects with bipolar I disorder and 334 age and sex-matched referents from Olmsted County, Minnesota, U.S. was identified. Longitudinal follow-up continued until incident MI or stroke (confirmed by board-certified cardiologist/neurologist), death, or study end date (December 31, 2013). Cox proportional hazards models assessed the hazard ratio (HR) for MI or stroke, adjusting for potential confounders.

RESULTS

There was an increased risk of fatal or non-fatal MI or stroke (as a composite outcome) in patients with bipolar I disorder [HR 1.54, 95% confidence interval (CI) 1.02, 2.33; p=0.04]. However, after adjusting for baseline cardiovascular risk factors (alcoholism, hypertension, diabetes, and smoking), the risk was no longer significantly increased (HR 1.19, 95% CI 0.76, 1.86; p=0.46).

LIMITATIONS

Small sample size for the study design. Findings were not retained after adjustment for cardiovascular disease risk factors. Psychotropic medication use during the follow-up was not ascertained and was not included in the analyses.

CONCLUSION

This study in a geographically defined region in the U.S. demonstrated a significant increased risk of MI or stroke in bipolar I disorder, which was no longer significant after adjustment for cardiovascular risk factors.

Improvement in Cardiovascular Risk Prediction with Electronic Health Records

The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen's kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification.

Mortality Associated With Heart Failure After Myocardial Infarction: A Contemporary Community Perspective

BACKGROUND

Contemporary data are lacking on the prognostic importance of heart failure (HF) after myocardial infarction (MI). We evaluated the prognostic impact of HF post MI according to preserved/reduced ejection fraction and the timing of its occurrence.

METHODS AND RESULTS

All Olmsted County, Minnesota, residents (n=2596) with incident MI diagnosed in 1990 to 2010 and no prior HF were followed through March 2013. Cox models were used to examine (1) the hazard ratios for death associated with HF type and timing and (2) secular trends in survival by HF status. During a mean follow-up of 7.6 years, there were 1116 deaths, 634 in the 902 patients who developed HF (70%) and 482 in the 1694 patients who did not develop HF (28%). After adjustment for age and sex, HF as a time-dependent variable was strongly associated with mortality (hazard ratio =3.31, 95% confidence interval: 2.93-3.75), particularly from cardiovascular causes (hazard ratio =4.20, 95% confidence interval: 3.50-5.03). Further adjustment for MI severity and comorbidity, acute treatment, and recurrent MI moderately attenuated these associations (hazard ratio =2.49 and 2.94 for all-cause and cardiovascular mortality, respectively). Mortality did not differ by ejection fraction, but was higher for delayed- versus early-onset HF (P for heterogeneity =0.002). The age- and sex-adjusted 5-year survival estimates in 2001 to 2010 versus 1990 to 2000 were 82% and 81% among HF-free and 61% and 54% among HF patients, respectively (P for heterogeneity of trends =0.05).

CONCLUSIONS

HF markedly increases the risk of death after MI. This excess risk is similar regardless of ejection fraction but greater for delayed- versus early-onset HF. Mortality after MI declined over time, primarily as a result of improved HF survival.

Normal-Weight Central Obesity: Implications for Total and Cardiovascular Mortality

BACKGROUND

The relationship between central obesity and survival in community-dwelling adults with normal body mass index (BMI) is not well-known.

OBJECTIVE

To examine total and cardiovascular mortality risks associated with central obesity and normal BMI.

DESIGN

Stratified multistage probability design.

SETTING

NHANES III (Third National Health and Nutrition Examination Survey).

PARTICIPANTS

15,184 adults (52.3% women) aged 18 to 90 years.

MEASUREMENTS

Multivariable Cox proportional hazards models were used to evaluate the relationship of obesity patterns defined by BMI and waist-to-hip ratio (WHR) and total and cardiovascular mortality risk after adjustment for confounding factors.

RESULTS

Persons with normal-weight central obesity had the worst long-term survival. For example, a man with a normal BMI (22 kg/m2) and central obesity had greater total mortality risk than one with similar BMI but no central obesity (hazard ratio [HR], 1.87 [95% CI, 1.53 to 2.29]), and this man had twice the mortality risk of participants who were overweight or obese according to BMI only (HR, 2.24 [CI, 1.52 to 3.32] and 2.42 [CI, 1.30 to 4.53], respectively). Women with normal-weight central obesity also had a higher mortality risk than those with similar BMI but no central obesity (HR, 1.48 [CI, 1.35 to 1.62]) and those who were obese according to BMI only (HR, 1.32 [CI, 1.15 to 1.51]). Expected survival estimates were consistently lower for those with central obesity when age and BMI were controlled for.

LIMITATIONS

Body fat distribution was assessed based on anthropometric indicators alone. Information on comorbidities was collected by self-report.

CONCLUSION

Normal-weight central obesity defined by WHR is associated with higher mortality than BMI-defined obesity, particularly in the absence of central fat distribution.

PRIMARY FUNDING SOURCE

National Institutes of Health, American Heart Association, European Regional Development Fund, and Czech Ministry of Health.

Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015

BACKGROUND

A 1.5-day interactive forum was convened to discuss critical issues in the acquisition, analysis, and sharing of data in the field of cardiovascular and stroke science. The discussion will serve as the foundation for the American Heart Association's (AHA's) near-term and future strategies in the Big Data area. The concepts evolving from this forum may also inform other fields of medicine and science.

METHODS AND RESULTS

A total of 47 participants representing stakeholders from 7 domains (patients, basic scientists, clinical investigators, population researchers, clinicians and healthcare system administrators, industry, and regulatory authorities) participated in the conference. Presentation topics included updates on data as viewed from conventional medical and nonmedical sources, building and using Big Data repositories, articulation of the goals of data sharing, and principles of responsible data sharing. Facilitated breakout sessions were conducted to examine what each of the 7 stakeholder domains wants from Big Data under ideal circumstances and the possible roles that the AHA might play in meeting their needs. Important areas that are high priorities for further study regarding Big Data include a description of the methodology of how to acquire and analyze findings, validation of the veracity of discoveries from such research, and integration into investigative and clinical care aspects of future cardiovascular and stroke medicine. Potential roles that the AHA might consider include facilitating a standards discussion (eg, tools, methodology, and appropriate data use), providing education (eg, healthcare providers, patients, investigators), and helping build an interoperable digital ecosystem in cardiovascular and stroke science.

CONCLUSION

There was a consensus across stakeholder domains that Big Data holds great promise for revolutionizing the way cardiovascular and stroke research is conducted and clinical care is delivered; however, there is a clear need for the creation of a vision of how to use it to achieve the desired goals. Potential roles for the AHA center around facilitating a discussion of standards, providing education, and helping establish a cardiovascular digital ecosystem. This ecosystem should be interoperable and needs to interface with the rapidly growing digital object environment of the modern-day healthcare system.

Association Between Atrial Fibrillation and Costs After Myocardial Infarction: A Community Study

BACKGROUND

The authors sought to estimate incremental economic impact of atrial fibrillation (AF) and the timing of its onset in myocardial infarction (MI) patients.

HYPOTHESIS

Concurrent AF and its timing are associated with higher costs in MI patients.

METHODS

This retrospective cohort study included incident MI patients from Olmsted County, Minnesota, treated between November 1, 2002, and December 31, 2010. We compared inflation-adjusted standardized costs accumulated between incident MI and end of follow-up among 3 groups by AF status and timing: no AF, new-onset AF (within 30 days after index MI), and prior AF. Multivariate adjustment of median costs accounted for right-censoring in costs.

RESULTS

The final study cohort had 1389 patients, with 989 in no AF, 163 in new-onset AF, and 237 in prior AF categories. Median follow-up times were 3.98, 3.23, and 2.55 years, respectively. Mean age at index was 67 years, with significantly younger patients in the no AF group (64 years vs 76 and 77 years, respectively; P < 0.001). New-onset and prior AF patients had more comorbid conditions (hypertension, heart failure, and chronic obstructive pulmonary disease). After accounting for differences in baseline characteristics, we found adjusted median (95% confidence interval) costs of $73 000 ($69 000-$76 000) for no AF; $85 000 ($81 000-$89 000) for new-onset AF; and $97 000 ($94 000-$100 000) for prior AF. Inpatient costs composed the largest share of total median costs (no AF, 82%; new-onset AF, 84%; prior AF, 83%).

CONCLUSIONS

Atrial fibrillation frequently coexists with MI and imposes incremental costs, mainly attributable to inpatient care. Timing of AF matters, as prior AF was found to be associated with higher costs than new-onset AF.

A Robust e-Epidemiology Tool in Phenotyping Heart Failure with Differentiation for Preserved and Reduced Ejection Fraction: the Electronic Medical Records and Genomics (eMERGE) Network

Identifying populations of heart failure (HF) patients is paramount to research efforts aimed at developing strategies to effectively reduce the burden of this disease. The use of electronic medical record (EMR) data for this purpose is challenging given the syndromic nature of HF and the need to distinguish HF with preserved or reduced ejection fraction. Using a gold standard cohort of manually abstracted cases, an EMR-driven phenotype algorithm based on structured and unstructured data was developed to identify all the cases. The resulting algorithm was executed in two cohorts from the Electronic Medical Records and Genomics (eMERGE) Network with a positive predictive value of >95 %. The algorithm was expanded to include three hierarchical definitions of HF (i.e., definite, probable, possible) based on the degree of confidence of the classification to capture HF cases in a whole population whereby increasing the algorithm utility for use in e-Epidemiologic research.

A contemporary appraisal of the heart failure epidemic in Olmsted County, Minnesota, 2000 to 2010

IMPORTANCE

Heart failure (HF) is commonly referred to as an epidemic, posing major clinical and public health challenges. Yet, contemporary data on its magnitude and implications are scarce.

OBJECTIVE

To evaluate recent trends in HF incidence and outcomes overall and by preserved ejection fraction (HFpEF) or reduced ejection fraction (HFrEF).

DESIGN, SETTING, AND PARTICIPANTS

Incidence rates of HF in Olmsted County, Minnesota (population, approximately 144,248), between January 1, 2000, and December 31, 2010, were assessed.

MAIN OUTCOMES AND MEASURES

Patients identified with incident HF (n = 2762) (mean age, 76.4 years; 43.1% male) were followed up for all-cause and cause-specific hospitalizations (through December 2012) and death (through March 2014).

RESULTS

The age- and sex-adjusted incidence of HF declined substantially from 315.8 per 100,000 in 2000 to 219.3 per 100,000 in 2010 (annual percentage change, -4.6), equating to a rate reduction of 37.5% (95% CI, -29.6% to -44.4%) over the last decade. The incidence declined for both HF types but was greater (interaction P = .08) for HFrEF (-45.1%; 95% CI, -33.0% to -55.0%) than for HFpEF (-27.9%; 95% CI, -12.9% to -40.3%). Mortality was high (24.4% for age 60 years and 54.4% for age 80 years at 5 years of follow-up), frequently ascribed to noncardiovascular causes (54.3%), and did not decline over time. The risk of cardiovascular death was lower for HFpEF than for HFrEF (multivariable-adjusted hazard ratio, 0.79; 95% CI, 0.67-0.93), whereas the risk of noncardiovascular death was similar (1.07; 95% CI, 0.89-1.29). Hospitalizations were common (mean, 1.34; 95% CI, 1.25-1.44 per person-year), particularly among men, and did not differ between HFpEF and HFrEF. Most hospitalizations (63.0%) were due to noncardiovascular causes. Hospitalization rates for cardiovascular causes did not change over time, whereas those for noncardiovascular causes increased.

CONCLUSIONS AND RELEVANCE

Over the last decade, the incidence of HF declined substantially, particularly for HFrEF, contrasting with no apparent change in mortality. Noncardiovascular conditions have an increasing role in hospitalizations and remain the most frequent cause of death. These results underscore the need to augment disease-centric management approaches with holistic strategies to reduce the population burden of HF.

Cardiovascular diseases in populations: secular trends and contemporary challenges-Geoffrey Rose lecture, European Society of Cardiology meeting 2014

Geoffrey Rose pioneered the concept that, to reduce the burden of disease, improving the population distribution of a risk factor was preferable to interventions that target high-risk individuals. Reflecting on this concept prompted us to ask if temporal trends in the burden of cardiovascular disease support this hypothesis. This perspective article summarizes the Geoffrey Rose lecture given at the European Society of Cardiology meeting in 2014 and examines how cardiovascular diseases have evolved over the past three decades focusing on temporal trends in myocardial infarction and heart failure.

Acute coronary syndromes in the community

OBJECTIVES

To measure the incidence of acute coronary syndrome (ACS), defined as first-ever myocardial infarction (MI) or unstable angina (UA); evaluate recent temporal trends; and determine whether survival after ACS has changed over time and differs by type.

PATIENTS AND METHODS

This was a population surveillance study conducted in Olmsted County, Minnesota (population: 144,248). All persons hospitalized with incident ACS between January 1, 2005, and December 31, 2010, were identified using International Classification of Diseases, Ninth Revision codes, natural language processing of the medical records, and biomarkers. Myocardial infarction was validated by epidemiologic criteria and UA by the Braunwald classification. Patients were followed through June 30, 2013, for death.

RESULTS

Of 1244 incident ACS cases, 35% (n=438) were UA and 65% (n=806) were MI. The standardized rates (per 100,000) of ACS were 284 (95% CI, 248-319) in 2005 and 184 (95% CI, 157-210) in 2010 (2010 vs 2005: rate ratio, 0.62; 95% CI, 0.53-0.73), indicating a 38% decline (similar for MI and UA). The 30-day case fatality rates did not differ by year of diagnosis but were worse for MI (8.9%; 95% CI, 6.9%-10.9%) compared with UA (1.9%; 95% CI, 0.6%-3.1%). Among 30-day survivors, the risk of death did not differ by ACS type or diagnosis year.

CONCLUSION

In the community, UA constitutes 35% of ACS. The incidence of ACS has declined in recent years, and trends were similar for UA and MI, reaffirming a substantial decline in all acute manifestations of coronary disease. Survival after ACS did not change over time, but 30-day survival was worse for MI compared with UA.

Contributions of increasing obesity and diabetes to slowing decline in subclinical coronary artery disease

Background

Our previous study of nonelderly adult decedents with nonnatural (accident, suicide, or homicide) cause of death (96% autopsy rate) between 1981 and 2004 revealed that the decline in subclinical coronary artery disease (CAD) ended in the mid‐1990s. The present study investigated the contributions of trends in obesity and diabetes mellitus to patterns of subclinical CAD and explored whether the end of the decline in CAD persisted.

Methods and Results

We reviewed provider‐linked medical records for all residents of Olmsted County, Minnesota, who died from nonnatural causes within the age range of 16 to 64 years between 1981 and 2009 and who had CAD graded at autopsy. We estimated trends in CAD risk factors including age, sex, systolic blood pressure, diabetes (qualifying fasting glucose or medication), body mass index, smoking, and diagnosed hyperlipidemia. Using multiple regression, we tested for significant associations between trends in CAD risk factors and CAD grade and assessed the contribution of trends in diabetes and obesity to CAD trends. The 545 autopsied decedents with recorded CAD grade exhibited significant declines between 1981 and 2009 in systolic blood pressure and smoking and significant increases in blood pressure medication, diabetes, and body mass index ≥30 kg/m². An overall decline in CAD grade between 1981 and 2009 was nonlinear and ended in 1994. Trends in obesity and diabetes contributed to the end of CAD decline.

Conclusions

Despite continued reductions in smoking and blood pressure values, the previously observed end to the decline in subclinical CAD among nonelderly adult decedents was apparent through 2009, corresponding with increasing obesity and diabetes in that population.