Skip to main content
NCBI home page
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease logoLink to Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
. 2012 Aug 24;1(4):e001206. doi: 10.1161/JAHA.112.001206

Trends in Clinical, Demographic, and Biochemical Characteristics of Patients With Acute Myocardial Infarction From 2003 to 2008: A Report From the American Heart Association Get With The Guidelines Coronary Artery Disease Program

Nathan M Boyer 1, Warren K Laskey 1,✉, Margueritte Cox 2, Adrian F Hernandez 2, Eric D Peterson 2, Deepak L Bhatt 3, Christopher P Cannon 4, Gregg C Fonarow 5
PMCID: PMC3487339  PMID: 23130159

Abstract

Background

An analysis of the changes in the clinical and demographic characteristics of patients with acute myocardial infarction could identify successes and failures of risk factor identification and treatment of patients at increased risk for cardiovascular events.

Methods and Results

We reviewed data collected from 138 122 patients with acute myocardial infarction admitted from 2003 to 2008 to hospitals participating in the American Heart Association Get With The Guidelines Coronary Artery Disease program. Clinical, demographic, and laboratory characteristics were analyzed for each year stratified on the electrocardiogram at presentation. Patients with non–ST-segment–elevation myocardial infarction were older, more likely to be women, and more likely to have hypertension, diabetes mellitus, and a history of past cardiovascular disease than were patients with ST-elevation myocardial infarction. In the overall patient sample, significant trends were observed of an increase over time in the proportions of non–ST-segment–elevation myocardial infarction, patient age of 45 to 65 years, obesity, and female sex. The prevalence of diabetes mellitus decreased over time, whereas the prevalences of hypertension and smoking were substantial and unchanging. The prevalence of “low” high-density lipoprotein increased over time, whereas that of “high” low-density lipoprotein decreased. Stratum-specific univariate analysis revealed quantitative and qualitative differences between strata in time trends for numerous demographic, clinical, and biochemical measures. On multivariable analysis, there was concordance between strata with regard to the increase in prevalence of patients 45 to 65 years of age, obesity, and “low” high-density lipoprotein and the decrease in prevalence of “high” low-density lipoprotein. However, changes in trends in age distribution, sex ratio, and prevalence of smokers and the magnitude of change in diabetes mellitus prevalence differed between strata.

Conclusions

There were notable differences in risk factors and patient characteristics among patients with ST-elevation myocardial infarction and those with non–ST-segment–elevation myocardial infarction. The increasing prevalence of dysmetabolic markers in a growing proportion of patients with acute myocardial infarction suggests further opportunities for risk factor modification. (J Am Heart Assoc. 2012;1:e001206 doi: 10.1161/JAHA.112.001206.)

Keywords: coronary disease, epidemiology, myocardial infarction, population, risk factors

Introduction

Description of the behavioral, environmental, and genetic factors in patients with acute myocardial infarction (AMI) underscores our current understanding of the causal relationship between patient- and population-specific exposures, or risk factors, and clinical outcomes.1–4 Patients with AMI represent a distinct, highly select subgroup of the general population. Changes in the extent and distribution of specific clinical, demographic, and biochemical factors over time in patients with AMI provide insight into the overall burden of disease in individuals at the highest risk for AMI. The latter is of relevance from demographic and public health perspectives, given the increasing number of individuals in the general population at risk for AMI5 and the increasing number of survivors of AMI.6 Finally, such studies, by revealing an increased or unchanging presence of specific risk factors, could suggest additional or missed opportunities for preventive strategies.7–8

In the present analysis from the American Heart Association (AHA) Get With The Guidelines Coronary Artery Disease (GWTG-CAD) program, we report the prevalences of clinical, demographic, and biochemical factors in patients presenting with AMI and the changes in those prevalences from 2003 to 2008.

Methods

The AHA GWTG-CAD Program

The mission, scope, and purpose of the AHA GWTG-CAD program have been described previously.9–10 Because GWTG-CAD is a quality-improvement program, hospitals are encouraged to consecutively enroll all eligible patients. The GWTG-CAD population includes all patients admitted to the hospital who were subsequently discharged with a diagnosis of AMI, unstable angina, chronic stable angina, or ischemic heart disease (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes 410–414). Each participating site is responsible for its own data collection and uploading. Data quality is monitored in a Web-based system, and reports are provided to the site to ensure completeness and accuracy of the submitted data. Data collected include patient demographics, medical history, symptoms on arrival, results of laboratory testing, in-hospital treatment and events, discharge treatment and counseling, and patient disposition. The de-identification of patients occurs at this level.

All participating institutions were required to comply with local regulatory and privacy guidelines and to submit the GWTG-CAD protocol for review and approval by their institutional review boards. Because data were used primarily at the local site for quality improvement, sites were granted a waiver of informed consent under the common rule. The Duke Clinical Research Institute (Durham, NC) serves as the data analysis center and has institutional review board approval to analyze the aggregate de-identified data for research purposes.

Patient Population

The GWTG-CAD program began in 2000, and the length of participation of each hospital depended on the time it entered the program. Baseline data included the first 30 admissions for each participating site and served as the entry point into the study. Subsequently, participation time was calculated in calendar quarters. Quarters with <1000 admissions were excluded to obtain reliable estimates of trends over time; this necessitated exclusion of data obtained in all 4 quarters of 2000 and 2001. Therefore, all GWTG-CAD–participating hospitals enrolled from January 1, 2002, to April 2010 were eligible for analysis.

The patient sample for this study was derived from the population of patients with a first-listed diagnosis and supporting ICD-9-CM code for coronary heart disease who were admitted to hospitals participating in the AHA GWTG-CAD program. Data from January 2002 through April 2010 were reviewed. Over this interval, 282 585 patients had an ICD-9-CM–consistent diagnosis of AMI (ICD-9-410). Excluded were records created before 2003 (n=23 024), records created after 2008 because of administrative changes in the GWTG program (n=16 396), patients with heart failure with CAD (n=36 574), patients without an AMI (n=66 940), and patients with an unspecified AMI (n=1529). The final study sample consisted of 138 122 patients (from 398 sites) admitted from January 1, 2003, to December 31, 2008. Patients subsequently were categorized by the electrocardiogram pattern on admission: specifically, those with ST-segment–elevation myocardial infarction (STEMI; n=44 172) or a new or presumably new left bundle-branch block pattern and those without ST-segment elevation (NSTEMI; n=92 950).

Data and Statistical Analysis

Data are presented as means ± standard deviations or medians and interquartile ranges (IQRs) for continuous variables and as percentages for categorical variables for the overall data set and separately for the STEMI and NSTEMI strata. Univariate associations between categorical variables and year of observation (ordered variable) were tested with χ2 statistics (for >3 levels per categorical variable) and Wilcoxon rank-based statistics (for 2 levels per category). The overall effect of linear yearly trend for each variable of interest was tested with the Cochran-Mantel-Haenszel method. P values for continuous data are based on χ2 1-degree-of-freedom rank correlation statistics. Stratum-specific multivariable logistic regression was performed to assess the association of time and the following dichotomous risk factors for AMI: age, sex, history of hypertension, history of prior myocardial infarction, history of treated diabetes mellitus, history of current or recent smoking, obesity (body mass index [BMI] >30 kg/m2), dyslipidemia (low-density lipoprotein [LDL] >100 mg/dL; high-density lipoprotein [HDL] <40 mg/dL for men, <50 mg/dL for women; triglycerides >150 mg/dL). Because patients admitted to the same hospital can have similar characteristics, the generalized estimating equations method with an exchangeable working correlation structure was used to adjust for within-hospital clustering.11 The generalized estimating equations method is only one analytical strategy to handle correlations within the same hospital. The generalized estimating equations method does not control for potential confounding effects due to the different types of hospitals to which patients are admitted. Therefore, hospital-level variables are included in the regression. Potential confounding variables were included in each fitted model for each designated risk characteristic outcome. These variables included the following baseline characteristics: age, sex, race (white, black/African American, Hispanic origin, other), BMI, insurance status, atrial fibrillation, chronic obstructive pulmonary disease, diabetes mellitus, hyperlipidemia, hypertension, peripheral vascular disease, prior myocardial infarction, heart failure, dialysis, renal insufficiency, current/recent smoking, United States Census–defined geographic region, number of beds, teaching status, and cardiac surgery on site. Age, BMI, and number of beds were entered as continuous variables, and missing values were imputed from the median. Age had no missing data. Patients whose sex was missing from the data were excluded from modeling because of concerns about data quality for other variables. Insurance status was categorized as Medicare, Medicaid, other insurance, and no insurance. Less than 9% of insurance data were missing. Patients ≥65 years of age were imputed to Medicare. All other patients were imputed to other insurance, because this category is more likely (no insurance or Medicaid is more likely to be recorded by a data entry specialist). Medical history panel variables were missing in 5.9% of patients; missing values were imputed to “no” because of hypothesized omissions. Race was missing in 2.3% of patients; missing values were imputed to “white.” BMI was imputed to the sex-specific median for 10.9% of patients (10.5% after exclusion of patients with sex missing).

A variable was not included in the model as an independent variable when that variable was the dependent variable. From these models, unadjusted and adjusted odds ratios (ORs) for the change in prevalence of each analyzed risk factor per quarter–calendar-year increment were estimated, and results were reported as the cumulative OR for the 6 years of the study by exponentiating the OR per 1-year change to the power of 6. Because there was evidence for statistical interaction—that is, P<0.05—in several of the models (male sex, diabetes mellitus, hypertension) when the interaction term (time×STEMI/NSTEMI) was added to the above list of confounders, results are reported separately for each stratum.

Sensitivity Analysis

Because sites both “dropped in” and “dropped out” over the time interval of the study, a sensitivity analysis was performed on only those sites that contributed at least 1 patient in 2003 or 2004 and at least 1 patient in each of the following years: 2005, 2006, 2007, and 2008. For this “core” data set analysis, there were 73 715 patients from 78 unique sites.

All analyses were performed in SAS version 9.2 (SAS Institute, Cary, NC). All significance tests were 2 sided, and P values <0.05 were considered statistically significant. Given the number of comparisons performed in this study, the lack of adjustment for such multiple comparisons, and the large overall sample size, a more conservative definition of statistical significance is suggested when P<0.001.

Results

Demographic Characteristics of Overall AMI Patient Population Over Time: Univariate Analysis

As seen in Table 1, the change in age distribution over time for the total sample was of borderline statistical significance (2003 median/IQR, 67/22 years; 2008 median/IQR, 66/22 years; P=0.0535). However, there was a significant increase over time in the relative proportion of patients between the ages of 45 and 65 years (P<0.0001), and the relative proportion of patients ≥65 years of age decreased (P<0.0001). There was a significant change in the sex ratio (males per 100 females) from 2003 to 2008, with an increasing proportion of females in later years (Figure 1A and 1B).

Table 1.

Trends in Demographic, Medical Historical, and Laboratory Characteristics in the Overall AMI Patient Sample

Variables Level Overall (n=138 122) 2003 (n=19 504) 2004 (n=22 177) 2005 (n=27 689) 2006 (n=22 921) 2007 (n=23 086) 2008 (n=22 745) P
Diagnosis NSTEMI 92 950 67.30 12 798 65.62 14 691 66.24 19 051 68.80 15 281 66.67 15 438 66.87 15 691 68.99 <0.0001
Demographics
Age Median 138 122 67.00 19 504 67.00 22 177 67.00 27 689 67.00 22 921 66.00 23 086 66.00 22 745 66.00 0.0535
25th 55.00 56.00 56.00 56.00 55.00 55.00 56.00
75th 78.00 78.00 78.00 78.00 78.00 78.00 78.00
Mean 66.43 66.66 66.45 66.52 66.08 66.29 66.60
SD 14.43 14.10 14.38 14.51 14.42 14.53 14.53
Minimum 18.00 19.00 18.00 18.00 19.00 18.00 19.00
Maximum 107.00 104.00 106.00 104.00 105.00 106.00 107.00
Age ≤45 y Yes 10 645 7.71 1446 7.41 1717 7.74 2196 7.93 1812 7.91 1808 7.83 1666 7.32 0.7521
Age ≥65 y Yes 75 473 54.64 10 980 56.30 12 254 55.26 15 260 55.11 12 238 53.39 12 362 53.55 12 379 54.43 <0.0001
Age >45, <65 y Yes 52 004 83.01 7078 83.04 8206 82.70 10 233 82.33 8871 83.04 8916 83.14 8700 83.93 0.0241
Sex Female 51 496 37.28 7251 37.18 8365 37.72 10 389 37.52 8389 36.60 8586 37.19 8516 37.44 0.0024
Race Other 5424 3.93 619 3.17 681 3.07 1133 4.09 959 4.18 995 4.31 1037 4.56 <0.0001
Hispanic 10 051 7.28 1549 7.94 2023 9.12 2169 7.83 1579 6.89 1321 5.72 1410 6.20
Black or African American 10 181 7.37 1390 7.13 1563 7.05 1892 6.83 1778 7.76 1692 7.33 1866 8.20
White 10 3250 74.75 14 667 75.20 16 092 72.56 20 579 74.32 16 885 73.67 17 920 77.62 17 107 75.21
Missing 9216 6.67 1279 6.56 1818 8.20 1916 6.92 1720 7.50 1158 5.02 1325 5.83
Non-Hispanic white Yes 10 3250 74.75 14 667 75.20 16 092 72.56 20 579 74.32 16 885 73.67 17 920 77.62 17 107 75.21 <0.0001
Hispanic Yes 10 051 7.28 1549 7.94 2023 9.12 2169 7.83 1579 6.89 1321 5.72 1410 6.20 <0.0001
Insurance No insurance/not documented/UTD 12 268 8.88 1395 7.15 2361 10.65 2958 10.68 2193 9.57 1686 7.30 1675 7.36 <0.0001
Medicare 42 009 30.41 6492 33.29 7157 32.27 8886 32.09 6510 28.40 6377 27.62 6587 28.96
Medicaid 9268 6.71 1096 5.62 1615 7.28 1939 7.00 1648 7.19 1531 6.63 1439 6.33
Other 63 227 45.78 7719 39.58 10 517 47.42 13 629 49.22 10 873 47.44 10 715 46.41 9774 42.97
Missing 11 350 8.22 2802 14.37 527 2.38 277 1.00 1697 7.40 2777 12.03 3270 14.38
Medical history
None Yes 12 309 9.47 1387 7.73 1730 8.22 2337 8.83 2236 10.22 2481 11.38 2138 10.28 <0.0001
Chronic or recurrent atrial fibrillation Yes 10 018 7.71 1406 7.83 1743 8.28 2281 8.62 1589 7.26 1404 6.44 1595 7.67 <0.0001
Atrial flutter Yes 417 0.32 0 0.00 0 0.00 3 0.01 108 0.49 153 0.70 153 0.74 <0.0001
COPD or asthma Yes 18 429 14.18 2717 15.14 2997 14.23 3558 13.45 2923 13.36 3059 14.03 3175 15.26 0.7310
Diabetes mellitus Yes 41 623 32.03 5966 33.24 7043 33.44 8603 32.51 6747 30.85 6680 30.63 6584 31.65 <0.0001
Hyperlipidemia Yes 60 750 46.75 5868 32.69 9680 45.97 13 187 49.84 10 922 49.93 10 614 48.67 10 479 50.37 <0.0001
Hypertension Yes 87 194 67.10 12 139 67.63 14 213 67.49 17 897 67.64 14 378 65.73 14 317 65.65 14 250 68.50 0.1931
Peripheral vascular disease Yes 11 276 8.68 1734 9.66 1876 8.91 2253 8.51 1854 8.48 1758 8.06 1801 8.66 <0.0001
Prior MI/CAD Yes 38 429 29.57 4192 23.35 4481 21.28 5262 19.89 7174 32.80 8681 39.81 8639 41.53 <0.0001
CVA/TIA Yes 11 141 8.57 1583 8.82 1707 8.11 1955 7.39 1748 7.99 2105 9.65 2043 9.82 <0.0001
Heart failure Yes 19 580 15.07 2725 15.18 3576 16.98 4251 16.07 3153 14.42 2906 13.33 2969 14.27 <0.0001
Anemia Yes 2897 2.23 0 0.00 0 0.00 1 0.00 668 3.05 1063 4.87 1165 5.60 <0.0001
Renal insufficiency Yes 12 445 9.58 2056 11.45 2358 11.20 2653 10.03 1925 8.80 1769 8.11 1684 8.09 <0.0001
Depression Yes 3436 2.64 1 0.01 0 0.00 6 0.02 678 3.10 1336 6.13 1415 6.80 <0.0001
Prior PCI Yes 2695 2.07 0 0.00 0 0.00 0 0.00 1 0.00 50 0.23 2644 12.71 <0.0001
Prior CABG Yes 1980 1.52 0 0.00 0 0.00 0 0.00 0 0.00 43 0.20 1937 9.31 <0.0001
Medical history panel missing Yes 8168 5.91 1554 7.97 1118 5.04 1228 4.43 1048 4.57 1278 5.54 1942 8.54 <0.0001
Smoking Yes 43 010 31.14 5834 29.91 6924 31.22 8508 30.73 7315 31.91 7261 31.45 7168 31.51 0.7434
Laboratories
BMI Median 123 127 27.59 18 023 27.40 20 688 27.41 25 670 27.49 19 943 27.62 19 725 27.83 19 078 27.89 <0.0001
25th 24.22 24.21 24.12 24.16 24.22 24.34 24.38
75th 31.74 31.37 31.37 31.59 31.95 32.17 32.09
Mean 28.54 28.29 28.27 28.43 28.62 28.83 28.79
SD 6.62 6.43 6.44 6.56 6.68 6.88 6.71
Minimum 13.02 13.05 13.03 13.02 13.07 13.04 13.04
Maximum 99.27 99.27 96.95 98.41 88.71 97.00 96.88
BMI ≥30 kg/m2 Yes 41 860 30.31 5776 29.61 6636 29.92 8530 30.81 6943 30.29 7095 30.73 6880 30.25 <0.0001
Total cholesterol, mg/dL Median 94 094 167.00 12 791 173.00 14 868 169.00 18 749 167.00 15 754 165.00 16 169 164.00 15 763 163.00 <0.0001
25th 138.00 145.00 141.00 139.00 136.00 135.00 134.00
75th 199.00 205.00 201.00 199.00 198.00 195.00 196.00
Mean 171.06 177.67 173.84 171.29 169.61 167.93 167.45
SD 47.88 47.53 47.36 47.20 48.30 48.35 47.86
Minimum 10.00 15.00 16.00 10.00 11.00 21.00 18.00
Maximum 827.00 776.00 720.00 592.00 667.00 827.00 642.00
Total cholesterol >200 mg/dL Yes 22 551 16.33 3604 18.48 3769 17.00 4504 16.27 3661 15.97 3548 15.37 3465 15.23 <0.0001
HDL, mg/dL Median 92 601 37.00 12 430 39.00 14 574 38.00 18 490 36.00 15 538 36.00 15 990 36.00 15 579 36.00 <0.0001
25th 30.00 32.00 31.00 29.00 30.00 30.00 30.00
75th 45.00 47.00 46.00 45.00 45.00 45.00 45.00
Mean 38.77 40.57 39.50 37.93 38.29 38.49 38.40
SD 12.89 12.73 13.19 13.57 12.87 12.24 12.42
Minimum 0.00 0.00 0.00 0.00 0.00 0.00 2.00
Maximum 100.00 100.00 100.00 100.00 100.00 100.00 100.00
HDL <40 mg/dL Yes 54 836 39.70 6562 33.64 8200 36.98 11 265 40.68 9510 41.49 9714 42.08 9585 42.14 <0.0001
HDL <40 mg/dL (men), HDL <50 mg/dL (women) Yes 62 951 45.58 7820 40.09 9645 43.49 12 887 46.54 10 707 46.71 11 087 48.02 10 805 47.50 <0.0001
LDL, mg/dL Median 91 626 100.00 12 057 103.00 14 142 101.00 17 950 100.00 15 332 100.00 16 142 98.00 16 003 98.00 <0.0001
25th 76.00 81.00 78.00 77.00 76.00 74.00 73.00
75th 128.00 131.00 128.00 128.00 128.00 125.00 125.00
Mean 104.37 108.07 105.64 104.87 104.37 102.42 101.87
SD 39.89 39.25 39.48 39.48 39.71 40.70 40.23
Minimum 30.00 30.00 30.00 30.00 30.00 30.00 30.00
Maximum 500.00 483.00 486.00 451.00 444.00 500.00 500.00
LDL >100 mg/dL Yes 45 290 32.79 6432 32.98 7215 32.53 8929 32.25 7563 33.00 7622 33.02 7529 33.10 <0.0001
Triglycerides, mg/dL Median 92 852 122.00 12 499 128.00 14 635 126.00 18 535 124.00 15 569 120.00 15 983 119.00 15 631 119.00 <0.0001
25th 84.00 88.00 87.00 85.00 83.00 81.00 83.00
75th 181.00 189.00 186.00 185.00 176.00 176.00 177.00
Mean 152.79 157.78 156.25 155.57 149.45 148.45 150.01
SD 120.74 121.23 120.24 122.71 119.41 119.30 120.92
Minimum 5.00 5.00 5.70 6.60 7.00 5.00 5.00
Maximum 1998.0 1977.0 1881.0 1813.0 1938.0 1998.0 1935.0
Triglycerides >150 mg/dL Yes 33 229 24.06 4762 24.42 5540 24.98 6830 24.67 5319 23.21 5429 23.52 5349 23.52 <0.0001
Open in a new tab

Categorical data in columns are displayed as count|percent of overall. SD indicates standard deviation; UTD, unable to determine; COPD, chronic obstructive pulmonary disease; CVA, cerebrovascular accident; MI, myocardial infarction; TIA, transient ischemic attack; PCI, percutaneous coronary intervention; CABG, coronary artery bypass graft; LDL, low-density lipoprotein; HDL, high-density lipoprotein; BMI, body mass index; and AMI, acute myocardial infarction.

Figure 1.

Figure 1.

Open in a new tab

A, Distribution of women with AMI in 2003 (blue) and 2008 (red) in the AHA GWTG-CAD sample. Women >70 years of age comprised the highest proportion of female patients with AMI. There was an increase in the percentage of patients (x-axis) in the 45- to 65-year age group between 2003 and 2008. These age cohorts correspond to a significant portion of the “Baby Boom” generation born between 1946 and 1964. There is also an increase in the proportion of older women with AMI (>85 years) from 2003 to 2008. B, Distribution of men with AMI in 2003 (blue) and 2008 (red) in the AHA GWTG-CAD sample. Men between 55 and 65 years of age comprised the highest proportion of male patients with AMI. There was an increase in the percentage of patients (x-axis) in the 45- to 65-year age group between 2003 and 2008. These age cohorts correspond to a significant portion of the “Baby Boom” generation born between 1946 and 1964. There is also an increase in the proportion of older men with AMI (>85 years) from 2003 to 2008.

The distribution of racial/ethnic groups within the overall sample exhibited a significant change over time (Table 1), with a decreasing proportion of Hispanics within the sample, an increasing proportion of African Americans, and a relatively constant proportion of white patients. There was also a significant change in the distribution of insurance status over time (Table 1), with an initial increase in the proportion of Medicaid and uninsured patients and a decrease in the proportion of Medicare patients.

Clinical Characteristics and Risk Factors of Overall AMI Patient Population Over Time: Univariate Analysis

Ninety-three percent of the sample reported at least 1 risk factor among 5 modifiable “classic” risk factors (hypertension, hyperlipidemia, current smoking, diabetes mellitus, and obesity), and 69% reported ≥2 such risk factors. The overall prevalence of a history of hypertension remained high at 67.1% and varied little over time (2003, 67.6%; 2008, 68.5%; P for trend=0.19). The prevalence of current or recent smoking did not change significantly (2003, 29.9%; 2008, 31.5%; P for trend=0.74). The prevalence of a history of hyperlipidemia increased (2003, 32.7%; 2008, 50.4%; P for trend <0.0001). The prevalence of a BMI ≥30 kg/m2 increased slightly, from 29.6% in 2003 to 30.3% in 2008 (P for trend <0.0001). The overall prevalence of diabetes mellitus was 32.0% and decreased over time from 33.2% to 31.7% (P for trend <0.0001). The prevalence of total cholesterol >200 mg/dL decreased from 18.5% in 2003 to 15.2% in 2008 (P for trend <0.0001), and the prevalence of LDL >100 mg/dL initially trended down from 2003 to 2006 and then seemed to stabilize from 2006 to 2008 (P for trend <0.0001). However, the prevalence of “low” HDL (men, <40 mg/dL; women, <50 mg/dL) increased from 40.1% in 2003 to 47.5% in 2008 (P for trend <0.0001). There was a significant increase in the proportion of patients with NSTEMI over time (Table 1). Overall trends in the prevalence of key risk factors are depicted in Figure 2.

Figure 2.

Figure 2.

Open in a new tab

Trends in prevalence of cardiovascular risk factors (age, sex, hypertension, diabetes mellitus, hyperlipidemia, obesity, smoking) from 2003 to 2008 in the overall GWTG-CAD AMI sample. *P<0.05 for trend. HTN indicates hypertension.

There were notable differences between patients with NSTEMI and patients with STEMI (Table 2). In general, patients with NSTEMI were significantly more likely to be older and female and to have a greater burden of clinical risk factors—for example, hypertension, diabetes mellitus, and prior myocardial infarction. Conversely, patients with STEMI were more likely to be younger, male, and active smokers and to have a higher prevalence of biochemical risk factors—for example, “low” HDL, “high” LDL, and triglycerides >150 mg/dL.

Table 2.

STEMI and NSTEMI Patient Profile, 2003–2008

STEMI (n=45 172) NSTEMI (n=92 950) STEMI vs NSTEMI (P)
Age, y
Median 62 69 <0.0001
IQR 22 23
Mean 62.86 68.16
SD 14.15 14.2
Age ≤45 y, % 10.71 6.25 <0.0001
Age ≥65 y, % 43.33 60.14 <0.0001
Male, % 66.53 58.33 <0.0001
Race, %
Hispanic 7.15 7.34 <0.0001
Black or African American 6.51 7.79
White 75.55 74.36
Asian 2.87 3.32
Insurance status, %
None/UTD 12.86 6.95 <0.0001
Medicare 24.47 33.30
Medicaid 5.66 7.22
Other 48.41 44.49
Missing 8.60 8.03
Diabetes mellitus, % 25.56 35.12 <0.0001
Hypertension, % 60.60 70.21 <0.0001
Hyperlipidemia, % 44.44 47.85 <0.0001
Prior MI/CAD, % 23.24 32.60 <0.0001
Current/recent smoking, % 39.82 26.92 <0.0001
BMI ≥30 kg/m2, % 30.17 30.37 0.0874
HDL <40 mg/dL (men), <50 mg/dL (women), % 49.35 43.74 0.0283
LDL >100 mg/dL, % 37.92 30.30 <0.0001
Triglycerides >150 mg/dL, % 26.31 22.96 <0.0001
Open in a new tab

SD indicates standard deviation; STEMI, ST-segment elevation myocardial infarction; NSTEMI, non-ST-segment elevation myocardial infarction; UTD, unable to determine; MI, myocardial infarction; IRQ, interquartile range; CAD, coronary artery disease; BMI, body mass index; HDL, high-density lipoprotein; and LDL, low-density lipoprotein.

Demographic, Clinical, and Biochemical Characteristics of Patients With STEMI Over Time: Univariate Analysis

As seen in Table 3, in patients with STEMI, the median/IQR ages in 2003 and 2008 were, respectively, 63/22 years and 61/20 years (P for trend <0.0001), and the proportion of patients ≥65 years of age decreased (P<0.0001). The proportion of patients between 45 and 65 years of age remained stable over time. The sex ratio (number of males/100 females) increased over time (P=0.0002). There was a slight but significant decrease in the proportion of non-Hispanic whites (P<0.0001) and a decrease in the proportion of Hispanic patients over time (2003, 7.1%; 2008, 6.25%; P<0.0001). There was a significant decrease in the prevalence of a history of diabetes mellitus (2003, 28.5%; 2008, 22.93%; P<0.0001) and history of hypertension (2003, 63.06%; 2008, 60.46%; P<0.0001), although the prevalence of a history of hyperlipidemia increased (2003, 32.36%; 2008, 46.27%; P<0.0001). The prevalence of smoking increased (2003, 37.22%; 2008, 41.76%; P=0.0002). The prevalence of obesity increased (2003, 29.7%; 2008, 30.82%; P<0.0001). The prevalence of “low” HDL (<40 mg/dL in men, <50 mg/dL in women) increased significantly (2003, 42.86%; 2008, 52.32%; P<0.0001), and the prevalence of “high” LDL (LDL >100 mg/dL) increased (2003, 37.2%; 2008, 39.95%; P<0.0001), as did the prevalence of triglycerides >150 mg/dL (2003, 26.27%; 2008, 27.02%; P=0.0004).

Table 3.

Trends in Demographic, Medical Historical, and Laboratory Characteristics in Patients With STEMI

Variables Level Overall (n=45 172) 2003 (n=6706) 2004 (n=7486) 2005 (n=8638) 2006 (n=7640) 2007 (n=7648) 2008 (n=7054) P
Demographics
Age Median 45 172 62.00 6706 63.00 7486 62.00 8638 62.00 7640 62.00 7648 60.00 7054 61.00 <0.0001
25th 52.00 53.00 53.00 53.00 52.00 52.00 52.00
75th 74.00 75.00 75.00 75.00 74.00 73.00 72.00
Mean 62.86 63.72 63.37 63.15 62.77 62.13 62.06
SD 14.15 14.02 14.23 14.32 14.17 14.12 13.94
Minimum 18.00 19.00 18.00 18.00 19.00 18.00 20.00
Maximum 107.00 102.00 103.00 102.00 104.00 106.00 107.00
Age ≤45 y Yes 4837 10.71 666 9.93 775 10.35 930 10.77 826 10.81 866 11.32 774 10.97 0.0079
Age ≥65 y Yes 19 574 43.33 3132 46.70 3384 45.20 3824 44.27 3281 42.95 3103 40.57 2850 40.40 <0.0001
Age >45, <65 y Yes 20 761 81.10 2908 81.37 3327 81.11 3884 80.68 3533 81.05 3679 80.95 3430 81.59 0.7926
Sex Female 14 312 31.68 2220 33.10 2488 33.24 2785 32.24 2390 31.28 2335 30.53 2094 29.69 0.0002
Race Other 1567 3.47 201 3.00 218 2.91 301 3.48 310 4.06 290 3.79 247 3.50 <0.0001
Hispanic 3232 7.15 477 7.11 698 9.32 671 7.77 474 6.20 471 6.16 441 6.25
Black or African American 2941 6.51 439 6.55 431 5.76 535 6.19 535 7.00 485 6.34 516 7.31
White 34 128 75.55 5124 76.41 5499 73.46 6531 75.61 5689 74.46 5931 77.55 5354 75.90
Missing 3304 7.31 465 6.93 640 8.55 600 6.95 632 8.27 471 6.16 496 7.03
Non-Hispanic white Yes 34 128 75.55 5124 76.41 5499 73.46 6531 75.61 5689 74.46 5931 77.55 5354 75.90 <0.0001
Hispanic Yes 3232 7.15 477 7.11 698 9.32 671 7.77 474 6.20 471 6.16 441 6.25 <0.0001
Insurance No insurance/not documented/UTD 5808 12.86 691 10.30 1155 15.43 1309 15.15 1011 13.23 812 10.62 830 11.77 <0.0001
Medicare 11 053 24.47 1847 27.54 2051 27.40 2201 25.48 1756 22.98 1682 21.99 1516 21.49
Medicaid 2555 5.66 300 4.47 443 5.92 559 6.47 438 5.73 433 5.66 382 5.42
Other 21 869 48.41 2872 42.83 3702 49.45 4510 52.21 3770 49.35 3733 48.81 3282 46.53
Missing 3887 8.60 996 14.85 135 1.80 59 0.68 665 8.70 988 12.92 1044 14.80
Medical history
Laboratories
BMI, kg/m2 Median 40 478 27.68 6221 27.46 6963 27.42 8068 27.63 6643 27.64 6571 27.97 6012 28.05 <0.0001
25th 24.48 24.46 24.32 24.41 24.45 24.58 24.82
75th 31.56 31.24 31.11 31.47 31.67 31.88 32.03
Mean 28.52 28.31 28.19 28.48 28.50 28.83 28.87
SD 6.21 6.11 6.08 6.25 6.09 6.44 6.24
Minimum 13.02 13.06 13.17 13.02 13.07 13.19 13.04
Maximum 95.20 74.73 76.13 85.41 69.27 95.20 72.66
BMI ≥30 kg/m2 Yes 13 628 30.17 1992 29.70 2182 29.15 2652 30.70 2274 29.76 2354 30.78 2174 30.82 <0.0001
Total cholesterol, mg/dL Median 33 076 170.00 4737 175.00 5323 172.00 6334 169.00 5581 169.00 5775 167.00 5326 167.00 <0.0001
25th 142.00 148.00 144.00 141.00 141.00 139.00 139.00
75th 201.00 206.00 203.00 200.00 200.00 197.00 199.00
Mean 173.71 179.60 176.02 172.51 172.89 170.93 171.45
SD 46.70 47.35 46.72 45.21 47.09 46.59 47.02
Minimum 10.00 19.00 22.00 10.00 12.00 26.00 50.00
Maximum 776.00 776.00 720.00 574.00 667.00 709.00 608.00
Total cholesterol >200 mg/dL Yes 8305 18.39 1364 20.34 1424 19.02 1547 17.91 1377 18.02 1322 17.29 1271 18.02 <0.0001
HDL, mg/dL Median 32 593 36.00 4614 39.00 5218 37.00 6248 35.85 5516 36.00 5719 36.00 5278 36.00 <0.0001
25th 30.00 32.00 31.00 29.00 29.00 30.00 30.00
75th 44.00 47.00 45.00 44.00 44.00 44.00 43.00
Mean 38.24 40.61 39.09 37.34 37.69 37.74 37.49
SD 12.22 12.48 12.63 12.83 12.16 11.28 11.57
Minimum 0.00 0.00 0.00 0.00 5.00 5.00 3.00
Maximum 100.00 100.00 98.00 100.00 99.00 99.00 100.00
HDL <40 mg/dL (men), HDL <50 mg/dL (women) Yes 22 292 49.35 2874 42.86 3471 46.37 4414 51.10 3829 50.12 4013 52.47 3691 52.32 <0.0001
LDL, mg/dL Median 32 264 103.00 4471 106.00 5074 104.00 6087 103.00 5450 104.00 5754 102.00 5428 102.00 <0.0001
25th 80.00 82.00 80.00 80.00 80.00 78.00 78.00
75th 130.00 132.00 130.00 130.00 131.00 128.00 129.00
Mean 107.23 109.61 107.76 107.04 107.44 105.82 106.27
SD 39.45 38.65 39.50 38.68 38.76 39.83 41.08
Minimum 30.00 30.00 30.00 30.00 30.00 30.00 30.00
Maximum 500.00 400.00 486.00 451.00 399.00 500.00 500.00
LDL >100 mg/dL Yes 17 130 37.92 2497 37.24 2725 36.40 3207 37.13 2905 38.02 2978 38.94 2818 39.95 <0.0001
Triglycerides, mg/dL Median 32 641 124.00 4636 127.00 5221 127.00 6269 124.00 5526 123.00 5701 122.00 5288 124.00 <0.0001
25th 86.00 90.00 88.00 85.00 84.00 83.00 85.00
75th 182.00 189.00 187.00 181.00 179.00 178.00 181.00
Mean 153.62 159.80 157.39 152.10 151.82 148.98 153.17
SD 119.97 128.63 122.33 115.21 118.84 117.06 119.28
Minimum 5.00 5.00 5.70 8.00 13.00 12.00 5.00
Maximum 1998.0 1977.0 1539.0 1813.0 1659.0 1998.0 1863.0
Triglycerides >150 mg/dL Yes 11 886 26.31 1762 26.27 1985 26.52 2275 26.34 1971 25.80 1987 25.98 1906 27.02 0.0004
Open in a new tab

Categorical data in columns are displayed as count|percent of overall. SD indicates standard deviation; UTD, unable to determine; STEMI, ST-segment elevation myocardial infarction; BMI, body mass index; HDL, high-density lipoprotein; and LDL, low-density lipoprotein.

Demographic, Clinical, and Biochemical Characteristics of Patients With NSTEMI Over Time: Univariate Analysis

As seen in Table 4, in patients with NSTEMI, the median/IQR ages in 2003 and 2008 were, respectively, 70/21 years and 69/22 years (P for trend=0.004). The proportion of patients between 45 and 65 years of age increased slightly. In contrast to the patients with STEMI, sex ratio decreased over time (P<0.0001). There was a trend toward an increase in the proportion of non-Hispanic whites, and the proportion of Hispanic patients decreased over time (2003, 8.38%; 2008, 6.18%; P<0.0001). Consistent with the older age of patients with NSTEMI, there was a higher proportion of Medicare-insured patients. The prevalence of a history of diabetes mellitus marginally decreased over time (2003, 35.62%; 2008, 35.55%; P=0.0327). The prevalence of a history of hypertension increased further over time (2003, 69.92%; 2008, 72.10%; P=0.0162), and the prevalence of a history of hyperlipidemia increased from 32.8% in 2003 to 52.21% in 2008 (P<0.0001). There was a marginal increase in the prevalence of smoking (2003, 26.08%; 2008, 26.91%; P=0.0224). The prevalence of obesity increased marginally, from 29.57% in 2003 to 29.99% in 2008 (P<0.0001). The prevalence of “low” HDL increased from 38.65% in 2003 to 45.34% in 2008 (P<0.0001), whereas the prevalence of “high” LDL decreased marginally (2003, 30.75%; 2008, 30.02%; P<0.0001).

Table 4.

Trends in Demographic, Medical Historical, and Laboratory Characteristics in Patients With NSTEMI

Variables Level Overall (n=92 950) 2003 (n=12 798) 2004 (n=14 691) 2005 (n=19 051) 2006 (n=15 281) 2007 (n=15 438) 2008 (n=15 691) P
Demographics
Age Median 92 950 69.00 12 798 70.00 14 691 69.00 19 051 69.00 15 281 69.00 15 438 69.00 15 691 69.00 0.0038
25th 57.00 58.00 57.00 57.00 57.00 58.00 58.00
75th 80.00 79.00 79.00 80.00 79.00 80.00 80.00
Mean 68.16 68.20 68.02 68.05 67.74 68.35 68.64
SD 14.24 13.90 14.20 14.34 14.26 14.29 14.33
Minimum 18.00 19.00 19.00 19.00 20.00 18.00 19.00
Maximum 106.00 104.00 106.00 104.00 105.00 106.00 105.00
Age ≤45 y Yes 5808 6.25 780 6.09 942 6.41 1266 6.65 986 6.45 942 6.10 892 5.68 0.0291
Age ≥65 y Yes 55 889 60.14 7848 61.32 8870 60.38 11 436 60.03 8957 58.62 9259 59.98 9529 60.73 0.1567
Age >45, <65 y Yes 31 243 84.32 4170 84.24 4879 83.82 6349 83.37 5338 84.41 5237 84.75 5270 85.52 0.0050
Sex Female 37 184 40.00 5031 39.31 5877 40.00 7604 39.91 5999 39.26 6251 40.49 6422 40.93 <0.0001
Race Other 3857 4.15 418 3.27 463 3.15 832 4.37 649 4.25 705 4.57 790 5.03 <0.0001
Hispanic 6819 7.34 1072 8.38 1325 9.02 1498 7.86 1105 7.23 850 5.51 969 6.18
Black or African American 7240 7.79 951 7.43 1132 7.71 1357 7.12 1243 8.13 1207 7.82 1350 8.60
White 69122 74.36 9543 74.57 10593 72.11 14048 73.74 11196 73.27 11989 77.66 11753 74.90
Missing 5912 6.36 814 6.36 1178 8.02 1316 6.91 1088 7.12 687 4.45 829 5.28
Non-Hispanic White Yes 69 122 74.36 9543 74.57 10 593 72.11 14 048 73.74 11 196 73.27 11 989 77.66 11 753 74.90 <0.0001
Hispanic Yes 6819 7.34 1072 8.38 1325 9.02 1498 7.86 1105 7.23 850 5.51 969 6.18 <0.0001
Insurance No insurance/not documented/UTD 6460 6.95 704 5.50 1206 8.21 1649 8.66 1182 7.74 874 5.66 845 5.39 <0.0001
Medicare 30 956 33.30 4645 36.29 5106 34.76 6685 35.09 4754 31.11 4695 30.41 5071 32.32
Medicaid 6713 7.22 796 6.22 1172 7.98 1380 7.24 1210 7.92 1098 7.11 1057 6.74
Other 41 358 44.49 4847 37.87 6815 46.39 9119 47.87 7103 46.48 6982 45.23 6492 41.37
Missing 7463 8.03 1806 14.11 392 2.67 218 1.14 1032 6.75 1789 11.59 2226 14.19
Medical history
Diabetes mellitus Yes 30 873 35.12 4255 35.62 5087 36.14 6444 35.23 4968 33.96 5010 34.35 5109 35.55 0.0327
Hyperlipidemia Yes 42 062 47.85 3925 32.86 6449 45.82 9213 50.36 7538 51.52 7434 50.97 7503 52.21 <0.0001
Hypertension Yes 61 713 70.21 8353 69.92 9886 70.23 12 824 70.10 10 150 69.37 10 139 69.51 10 361 72.10 0.0162
Prior MI/CAD Yes 28 658 32.60 2990 25.03 3266 23.20 3954 21.61 5252 35.90 6547 44.89 6649 46.27 <0.0001
CVA/TIA Yes 8693 9.89 1160 9.71 1311 9.31 1536 8.40 1349 9.22 1669 11.44 1668 11.61 <0.0001
Medical history panel missing Yes 5047 5.43 852 6.66 615 4.19 758 3.98 650 4.25 852 5.52 1320 8.41 <0.0001
Smoking Yes 25 022 26.92 3338 26.08 4022 27.38 5108 26.81 4195 27.45 4137 26.80 4222 26.91 0.0224
Laboratories
BMI, kg/m2 Median 82 649 27.53 11 802 27.36 13 725 27.40 17 602 27.45 13 300 27.61 13 154 27.80 13 066 27.81 <0.0001
25th 24.09 24.09 23.96 24.02 24.12 24.20 24.17
75th 31.86 31.45 31.51 31.64 32.10 32.28 32.14
Mean 28.54 28.28 28.31 28.41 28.69 28.83 28.76
SD 6.81 6.59 6.61 6.70 6.95 7.09 6.92
Minimum 13.03 13.05 13.03 13.04 13.08 13.04 13.15
Maximum 99.27 99.27 96.95 98.41 88.71 97.00 96.88
BMI ≥30 kg/m2 Yes 28 232 30.37 3784 29.57 4454 30.32 5878 30.85 4669 30.55 4741 30.71 4706 29.99 <0.0001
Total cholesterol, mg/dL Median 61 018 165.00 8054 172.00 9545 168.00 12 415 166.00 10 173 163.00 10 394 161.00 10 437 160.00 <0.0001
25th 136.00 143.00 140.00 138.00 134.00 132.00 131.00
75th 198.00 205.00 200.00 199.00 196.00 194.00 194.00
Mean 169.62 176.54 172.62 170.66 167.81 166.27 165.41
SD 48.45 47.60 47.68 48.17 48.86 49.23 48.15
Minimum 11.00 15.00 16.00 16.00 11.00 21.00 18.00
Maximum 827.00 574.00 624.00 592.00 660.00 827.00 642.00
Total cholesterol >200 mg/dL Yes 14 246 15.33 2240 17.50 2345 15.96 2957 15.52 2284 14.95 2226 14.42 2194 13.98 <0.0001
HDL, mg/dL Median 60 008 37.00 7816 39.00 9356 38.00 12 242 36.00 10 022 36.00 10 271 37.00 10 301 37.00 <0.0001
25th 30.00 32.00 31.00 29.00 30.00 30.00 30.00
75th 46.00 47.00 47.00 45.00 45.00 45.00 45.00
Mean 39.05 40.55 39.73 38.23 38.62 38.90 38.86
SD 13.24 12.88 13.49 13.92 13.23 12.72 12.81
Minimum 0.00 0.00 0.00 0.00 0.00 0.00 2.00
Maximum 100.00 100.00 100.00 100.00 100.00 100.00 100.00
HDL <40 mg/dL Yes 35 016 37.67 4112 32.13 5221 35.54 7339 38.52 6044 39.55 6098 39.50 6202 39.53 <0.0001
HDL <40 mg/dL (men), HDL <50 mg/dL (women) Yes 40 659 43.74 4946 38.65 6174 42.03 8473 44.48 6878 45.01 7074 45.82 7114 45.34 <0.0001
LDL, mg/dL Median 59 362 98.00 7586 102.00 9068 100.00 11 863 99.00 9882 97.00 10 388 95.00 10 575 95.00 <0.0001
25th 74.00 80.00 77.00 75.00 74.00 71.00 70.00
75th 126.00 130.00 127.00 127.00 126.00 123.00 123.00
Mean 102.82 107.16 104.45 103.76 102.68 100.54 99.60
SD 40.04 39.58 39.42 39.84 40.13 41.06 39.60
Minimum 30.00 30.00 30.00 30.00 30.00 30.00 30.00
Maximum 500.00 483.00 439.00 401.00 444.00 500.00 476.00
LDL >100 mg/dL Yes 28 160 30.30 3935 30.75 4490 30.56 5722 30.04 4658 30.48 4644 30.08 4711 30.02 <0.0001
Triglycerides, mg/dL Median 60 211 121.00 7863 128.00 9414 126.00 12 266 125.00 10 043 119.00 10 282 117.00 10 343 117.00 <0.0001
25th 84.00 88.00 87.00 85.00 82.00 81.00 81.00
75th 181.00 189.00 185.00 186.00 174.00 176.00 174.00
Mean 152.33 156.59 155.62 157.34 148.14 148.15 148.39
SD 121.15 116.64 119.07 126.35 119.72 120.52 121.72
Minimum 5.00 14.00 8.40 6.60 7.00 5.00 14.00
Maximum 1940.0 1940.0 1881.0 1750.0 1938.0 1939.0 1935.0
Triglycerides >150 mg/dL Yes 21 343 22.96 3000 23.44 3555 24.20 4555 23.91 3348 21.91 3442 22.30 3443 21.94 <0.0001
Open in a new tab

Categorical data in columns are displayed as count|percent of overall. SD indicates standard deviation; UTD, unable to determine; MI, myocardial infarction; CVA, cerebrovascular accident; TIA, transient ischemic attack; NSTEMI, non-ST-segment elevation myocardial infarction; CAD, coronary artery disease; BMI, body mass index; HDL, high-density lipoprotein; and LDL, low-density lipoprotein.

Sensitivity Analysis

Sensitivity analysis on the core data set (cf. Methods) indicated excellent quantitative and qualitative agreement with the overall data set findings. Specifically, the frequency of missing medical history data was 6.35% in the core data set and 5.91% in the overall data set. Median age (67 years) and mean age (66.3 years) in the core data set were identical to the overall data set, and the trends over time were directionally similar. Sex ratios were numerically similar in the core and overall data sets, although the sex ratio trend in the core data set failed to reach statistical significance. Numerically and directionally similar trends in the prevalences of diabetes mellitus, hypertension, and hyperlipidemia were also in close agreement, as were the trends in obesity prevalence and “low” HDL.

Trends in Clinical Characteristics and Risk Factors of STEMI Patient Population: Multivariable Analysis

After adjustment for multiple potential confounding variables, including other risk factors (Table 5), the increase over time in the proportion of patients between 45 and 65 years of age was significant, along with increases in the prevalences of obesity and “low” HDL. However, there were significant decreases over time in the prevalences of hypertension, diabetes mellitus, prior AMI, and current/recent smoking, as well as decreases in the prevalences of “high” LDL and triglycerides >150 mg/dL.

Table 5.

ORs for Outcomes for Calendar Quarter (Per 6-Year Increase) With Adjustment for Potential Confounders*: STEMI Group

Outcome Total N (45 172) Unadjusted OR Lower (95% CI for Unadjusted OR) Upper (95% CI for Unadjusted OR) Unadjusted P Adjusted OR Lower (95% CI for Adjusted OR) Upper (95% CI for Adjusred OR) Adjusted P
Demographics
Age ≤45 y 45 172 1.100 0.970 1.248 0.136 0.873 0.759 1.005 0.059
Age ≥65 y 45 172 0.756 0.685 0.835 <0.001 1.053 0.879 1.261 0.579
Age >45, <65 y 25 598 1.041 0.921 1.176 0.521 1.148 1.009 1.306 0.036
Sex, male 44 364 1.166 1.063 1.278 0.001 1.071 0.976 1.175 0.149
White race 44 077 1.021 0.796 1.310 0.869 1.010 0.780 1.307 0.942
Hispanic ethnicity 44 077 1.174 0.933 1.476 0.171 1.113 0.888 1.395 0.354
Medical history
Diabetes mellitus 42 051 0.671 0.595 0.757 <0.001 0.718 0.643 0.802 <0.001
Hypertension 42 051 0.800 0.700 0.915 0.001 0.813 0.704 0.939 0.005
Prior MI 42 051 0.681 0.589 0.787 <0.001 0.735 0.631 0.856 <0.001
Current or recent smoking 44 112 0.984 0.898 1.078 0.727 0.890 0.802 0.987 0.028
Laboratories
BMI ≥30 kg/m2 40 478 1.264 1.146 1.394 <0.001 1.232 1.119 1.357 <0.001
LDL >100 mg/dL 32 264 0.789 0.708 0.879 <0.001 0.688 0.605 0.781 <0.001
HDL <40 mg/dL (men), <50 mg/dL (women) 32 593 1.588 1.357 1.859 <0.001 1.667 1.396 1.992 <0.001
TG >150 mg/dL 32 641 0.866 0.767 0.978 0.020 0.821 0.731 0.922 <0.001
Open in a new tab

COPD indicates chronic obstructive pulmonary disease; CI, confidence interval; MI, myocardial infarction; TIA, transient ischemic attack; TG, triglycerides; STEMI, ST-segment elevation myocardial infarction; BMI, body mass index; LDL, low-density lipoprotein; and HDL, high-density lipoprotein.

*

Variables in the model: age, sex, race (white, black, Hispanic, other), BMI, insurance, atrial fibrillation, COPD/asthma, cerebrovascular accident/TIA, diabetes mellitus, hyperlipidemia, hypertension, peripheral vascular disease, prior MI, heart failure, dialysis, renal insufficiency, smoking, geographic region, number of beds, teaching status, and cardiac surgery on site.

Trends in Clinical Characteristics and Risk Factors of NSTEMI Patient Population: Multivariable Analysis

After adjustment for multiple confounding variables, including other risk factors (Table 6), there were significant increases over time in the proportion of patients between 45 and 65 years of age, whereas the proportion of “younger” patients (≤45 years) decreased. The proportion of women increased over time, as did the proportion of Hispanic patients. The prevalence of diabetes mellitus decreased over time, whereas the prevalence of obesity increased. The prevalence of “low” HDL increased significantly, whereas the prevalence of “high” LDL decreased over time.

Table 6.

ORs for Outcomes for Calendar Quarter (Per 6-Year Increase) With Adjustment for Potential Confounders*: NSTEMI Group

Outcome Total N (92 950) Unadjusted OR Lower (95% CI for Unadjusted OR) Upper (95% CI for Unadjusted OR) Unadjusted P Adjusted OR Lower (95% CI for Adjusted OR) Upper (95% CI for Adjusted OR) Adjusted P
Demographics
Age ≤45 y 92 950 0.884 0.776 1.008 0.065 0.804 0.689 0.939 0.006
Age ≥65 y 92 950 1.014 0.943 1.090 0.715 1.168 0.975 1.400 0.093
Age >45, <65 y 37 051 1.157 1.024 1.308 0.019 1.213 1.054 1.396 0.007
Sex, male 91 401 0.896 0.833 0.964 0.003 0.921 0.850 0.997 0.043
White race 90 866 1.264 0.850 1.879 0.247 1.059 0.730 1.535 0.762
Hispanic ethnicity 90 866 1.211 1.065 1.377 0.003 1.232 1.101 1.379 <0.001
Medical history
Diabetes mellitus 87 903 0.920 0.852 0.994 0.034 0.888 0.814 0.968 0.007
Hypertension 87 903 1.003 0.884 1.138 0.965 0.886 0.779 1.007 0.065
Prior MI 87 903 0.703 0.589 0.840 <0.001 0.706 0.591 0.844 <0.001
Current or recent smoking 90 591 0.867 0.798 0.943 <0.001 0.944 0.858 1.038 0.232
Laboratories
BMI ≥30 kg/m2 82 649 1.192 1.112 1.278 <0.001 1.233 1.147 1.325 <0.001
LDL >100 mg/dL 59 362 0.726 0.669 0.787 <0.001 0.665 0.604 0.732 <0.001
HDL <40 mg/dL (men), <50 mg/dL (women) 60 008 1.437 1.232 1.677 <0.001 1.657 1.388 1.978 <0.001
TG >150 mg/dL 60 211 0.736 0.675 0.801 <0.001 0.733 0.665 0.807 <0.001
Open in a new tab

COPD indicates chronic obstructive pulmonary disease; CI, confidence interval; MI, myocardial infarction; TIA, transient ischemic attack; TG, triglycerides; NSTEMI, non-ST-segment elevation myocardial infarction; BMI, body mass index; LDL, low-density lipoprotein; and HDL, high-density lipoprotein.

*

Variables in the model: age, sex, race (white, black, Hispanic, other), BMI, insurance, atrial fibrillation, COPD/asthma, cerebrovascular accident / TIA, diabetes mellitus, hyperlipidemia, hypertension, peripheral vascular disease, prior MI, heart failure, dialysis, renal insufficiency, smoking, geographic region, number of beds, teaching status, and cardiac surgery on site.

Sensitivity Analysis

In general, there was quantitative and qualitative agreement between the core data sets and the overall stratum-specific analyses. In the STEMI group, the analyses differed only in the magnitude of the coefficient for the decrease in hypertension prevalence, whereas in the NSTEMI group, the analyses differed only in the magnitude of the coefficients for the changes in sex ratio and hypertension prevalence.

Discussion

The present analysis of the clinical, demographic, and biochemical characteristics of patients with AMI admitted to hospitals participating in the AHA GWTG-CAD quality-improvement initiative from 2003 to 2008 suggests that the cumulative risk factor burden in patients with AMI remained substantial. Favorable decreases in the prevalences of several “classic” risk factors over this interval were offset by increases in the prevalences of obesity and “low” HDL and suggest that metabolic derangements are likely to remain important contributors to overall risk factor burden.

The present observations are in agreement with previous reports from dedicated registries of patients with AMI12–13 and population-based studies,14–15 which described an increase in the NSTEMI/STEMI ratio over time. Although some of this increase has been attributed to a change in the diagnostic criteria for AMI around 2000,16 not all of the increase in the proportion of NSTEMI can be attributed to this transition.15,17–18 All patients in the present analysis were enrolled from 2003 forward and thus were ascertained with standardized post-transition criteria.

Our data are also in agreement with prior studies reporting the risk factor burden in patients with AMI.1–3 Despite high prevalence of a history of hyperlipidemia and hypertension, the recorded numerical values for admission blood pressure (data not shown), LDL, and total cholesterol in the GWTG-CAD registry are consistent with the increasing extent of antihypertensive and lipid-lowering treatment in the general US population.19–20

The present data mirror previously reported magnitudes and trends in the prevalence of obesity in AMI registries12–13 and population-based studies.14,19,21 However, the increase in the prevalence of obesity in the general population might not be continuing at the same rate in more recent years.22–23 The small numerical, albeit statistically significant, increase in the prevalence of BMI ≥30 kg/m2 in the present sample of patients with AMI is in agreement with these latter reports. The clinical relevance of an overall prevalence of obesity of 30% in this sample of patients with AMI should not be overlooked, given the strong associations among obesity, diabetes mellitus, hypertension, and dyslipidemia. The observed downward trend in the unadjusted and adjusted prevalences of diabetes mellitus in our study remains unexplained and is at odds with prior observations in patients with AMI,12–13 although it is numerically consistent with a more recent nested cohort population-based study.15 The present data should be viewed in the broader clinical context of, on average, a prevalence of diabetes mellitus of 30% in patients with AMI,6,14,21 depending on the diagnostic criteria used. The overall prevalence of diabetes mellitus was higher in patients with NSTEMI, whereas the magnitude of change in the prevalence of diabetes mellitus in patients with NSTEMI was less than that observed in patients with STEMI, which underscores the importance of stratum-specific analysis.

The additional information presented herein about a significant trend for the increase in prevalence of “low” HDL is in agreement with previous reports of an increase in prevalence of metabolic derangements in patients with AMI24 as well as in the adult US population.25

Implications of Changes in Demographic Composition of the Current AMI Sample

The changes in the age and sex distributions of the GWTG-CAD AMI population from 2003 to 2008, as shown in Figure 1A and 1B, parallel the changes seen in the US population in the first decade of this century,5 with the fastest rate of growth noted in the 45- to 64-year age group.5 This group comprises the initial cohorts of the “Baby Boom” generation as they enter the age range in which the risk of AMI begins to increase steeply.6 The increased prevalence of poor cardiovascular health behaviors and health factors in middle (40 to 64 years) and older (≥65 years) age groups in the US population over the identical time period as the present study provides additional insight into the correspondence between specific characteristics in patients with AMI and adults of similar age in the general population.26 In a separate report from the National Health and Nutrition Examination Survey encompassing the years 1988–2010, the prevalence of smoking decreased, and the prevalences of desirable levels of untreated blood pressure and total cholesterol were unchanged, whereas the prevalences of desirable levels of BMI and fasting glucose decreased,27 indicative of a persistently elevated risk factor burden in the general US population.

The public health implications and relevance of these observations and correlations are clear.28–30 The prevalence of risk factors, and their trends over time, in patients with AMI point to additional need for risk factor intervention at the population level.31–32 The present data from 2003 to 2008, however, only begin to suggest a population momentum effect resulting from the age cohorts comprising the “Baby Boom” generation. Even static levels of age-specific prevalences, when multiplied by the increasing number of subjects at risk due to population momentum, will result in an increase in the overall risk factor burden.

Limitations

The limitations of the present analysis relate chiefly to the use of registry data. It is recognized that there are many potential sources of selection bias in any registry and that the patients in the AHA GWTG-CAD registry might not be representative of all patients with AMI. Similarities to, as well as differences from, the published literature have been noted. Participation in the GWTG-CAD quality-improvement program is voluntary, and as such, the program is likely to include higher-performing hospitals. However, such potential selection bias is unlikely to affect the type, or number, of patient(s) presenting with an AMI, nor are the prevalences of underlying risk factors likely to be affected. Data could be influenced by both drop-in and drop-out of participating hospitals. Sensitivity analysis limited to those hospitals participating in each year revealed substantially similar trends and associations among key risk factors, with few exceptions. Participation in the GWTG-CAD program calls for consecutive enrollment of patients, as is appropriate for performance (per Centers for Medicare and Medicaid Services) and quality-improvement (per Joint Commission) initiatives. Compliance, or the number of patients enrolled per site per year, did not change over time among core sites (P for trend=0.17). The analysis of data collected over 6 years from >100 000 patients is likely to be more representative of “real-world” patients with AMI than an analysis from any one region or in any one year would be. The GWTG-CAD program includes sites from all regions of the United States and includes academically affiliated as well as community-based hospitals. Patients in the GWTG-Stroke performance-improvement program, a group not substantially dissimilar from patients with AMI with regard to cardiovascular risk factors, have been shown to be similar to patients in non–GWTG-participating centers.33 However, at the present time, there are no comparable studies in patients with CAD/AMI. Changes in professional and societal awareness of the presence and importance of sex-specific differences in cardiovascular disease at the time of this study34 could have had an important, albeit unquantifiable, effect on our findings. However, a recent study failed to identify differences in the time to hospital presentation among women with AMI after a national awareness campaign.35

Data were collected by chart review and are dependent on the accuracy and completion of documentation and abstraction. All data are entered at the site by highly trained individuals with experience in data entry. The GWTG database features carefully defined data entries, standardized diagnostic criteria throughout, and regular quality assessment. Importantly, the GWTG database includes only patients with confirmed AMI diagnosis at discharge and avoids many of the sources of information bias when the diagnosis is based on admission characteristics. These data and inferences from the data could, however, be limited by potential bias resulting from the inability of disadvantaged and minority groups to access medical care. Such patients are not, by definition, included in the GWTG-CAD data set and cannot be evaluated. The inferences with regard to changes in the prevalence of risk factors suggested by these data apply to the overall patient population.

The magnitudes of the reported main outcome measures of association—the OR for a change in prevalence of a given risk factor per 1 year—were small and initially suggested little clinically significant change from year to year, despite their statistical significance. We chose to report the cumulative OR for the change in prevalence of characteristics over the 6-year observation period in an effort to underscore their clinical significance. Statistical methodology dictates that the (adjusted) ORs must be interpreted in the context of all other covariates being fixed. From clinical and epidemiological perspectives, multiple covariates are not infrequently identified in the same individual—for example, diabetes mellitus, hypertension, and obesity. Statistical attempts to “isolate” changes in one of several highly associated variables might result in unstable or misleading estimates of a true association.

It is acknowledged that the use of an OR as an approximation of relative risk, or risk ratio, is problematic when prevalence is high. The majority of the characteristics and risk factors reported here have a high prevalence, and calculation of prevalence ratios and their changes would be more appropriate.36 However, qualitative inferences from this study remain valid.

In conclusion, the present analysis, based on >100 000 patients with AMI from 2003 to 2008, indicates that there were clinically and statistically significant changes over time in the risk factors and characteristics assessed. Increases in the prevalence of women, NSTEMI, and patients 45 to 65 years of age, when viewed from an epidemiological perspective, have important implications for the identification of further opportunities for risk factor modification. Continued increases in the prevalence of obesity and low HDL over the next decade, along with persistently high prevalences of hypertension and diabetes mellitus, particularly in the growing segment of patients with NSTEMI, could offset the beneficial clinical effects of decreasing trends in other risk factors and could result in higher disease burden and post-AMI morbidity in AMI survivors.37

Sources of Funding

The GWTG-CAD program was supported, in part, through the AHA Pharmaceutical Roundtable and an unrestricted educational grant from Merck. Drs Boyer and Laskey were supported, in part, by the Robert S. Flinn Endowment for Cardiovascular Medicine (University of New Mexico School of Medicine).

Disclosures

Dr Bhatt has served on the Advisory Board of Medscape Cardiology and on the Board of Directors of the Boston VA Research Institute and the Society of Chest Pain Centers; has served as the Chair of the AHA Get With The Guidelines Science Subcommittee; has received honoraria (significant) from the American College of Cardiology (Editor, Clinical Trials, Cardiosource), Duke Clinical Research Institute (clinical trial steering committees), Slack Publications (Chief Medical Editor, Cardiology Today Intervention), and WebMD (CME steering committees); has received research grants (significant) from Amarin, AstraZeneca, Bristol-Myers Squibb, Eisai, Ethicon, Medtronic, Sanofi Aventis, and The Medicines Company; and has performed unfunded research for FlowCo, PLx Pharma, and Takeda. Dr Hernandez has received research grants (significant) from Johnson & Johnson and Amylin and has received honoraria (significant) from Corthera. Dr Peterson has received research grants (significant) from Merck, Bristol-Meyers Squibb/Sanofi, Lilly, and Johnson & Johnson. Dr Cannon has received research grants (significant) from Accumetrics, AstraZeneca, GlaxoSmithKline, Merck, and Takeda; has received honoraria (modest) from Pfizer and AstraZeneca; and has served as a consultant to or on the advisory board (modest) of Bristol-Meyers Squibb/Sanofi, Novartis, Alnylam, and Automedics Medical Systems. Dr Fonarow has served on the Steering Committee of Get With the Guidelines and has received a research grant (significant) from the National Institutes of Health. Drs Boyer and Laskey and M. Cox have nothing to disclose.

References

  • 1.Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng Lon behalf of the INTERHEART Study Investigators Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART Study): case control study. Lancet. 2004;364:937-952 [DOI] [PubMed] [Google Scholar]
  • 2.Greenland P, Knoll MD, Stamler J, Neaton JD, Dyer AR, Garside DB, Wilson PW. Major risk factors as antecedents of fatal and non-fatal coronary heart disease events. JAMA. 2003;290:891-897 [DOI] [PubMed] [Google Scholar]
  • 3.Khot UN, Khot MB, Bajzer CT, Sapp SK, Ohman EM, Brener SJ, Ellis SG, Lincoff AM, Topol EJ. Prevalence of conventional risk factors in patients with coronary heart disease. JAMA. 2003;290:898-904 [DOI] [PubMed] [Google Scholar]
  • 4.Canto JG, Kiefe CI, Rogers WJ, Peterson ED, Frederick PD, French WJ, Gibson CM, Pollack CV, Ornato JP, Zalenski RJ, Tiefenbrunn AJ, Greenland Pfor the NRMI Investigators Number of coronary heart disease risk factors and mortality in patients with first myocardial infarction. JAMA. 2011;306:2120-2127 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.United States Census Bureau. US Census Age and Sex Composition 2010: 2010 Census Briefs. Issued May 2011. Available at: http://www.census.gov/prod/cen2010/briefs/c2010br-03.pdf. Accessed October 1, 2011.
  • 6.Roger VL, Go AS, Lloyd-Jones DM, Adams RJ, Berry JD, Brown TM, Carnethon MR, Dai S, de Simone G, Ford ES, Fox CS, Fullerton HJ, Gillespie C, Greenlund KJ, Hailpern SM, Heit JA, Ho PM, Howard VJ, Kissela BM, Kittner SJ, Lackland DT, Lichtman JH, Lisabeth LD, Makuc DM, Marcus GM, Marelli A, Matchar DB, McDermott MM, Meigs JB, Moy CS, Mozaffarian D, Mussolino ME, Nichol G, Paynter NP, Rosamond WD, Sorlie PD, Stafford RS, Turan TN, Turner MB, Wong NDon behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart disease and stroke statistics—2011 update: a report from the American Heart Association. Circulation. 2011;123:e18-e209 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Libby P. The forgotten majority: unfinished business in cardiovascular risk reduction. J Am Coll Cardiol. 2005;46:1225-1228 [DOI] [PubMed] [Google Scholar]
  • 8.Akosah KO, Schaper A, Cogbill C, Schoenfeld P. Preventing myocardial infarction in the young adult in the first place: how do the National Cholesterol Education Panel III Guidelines perform?. J Am Coll Cardiol. 2003;2003:1475-1479 [DOI] [PubMed] [Google Scholar]
  • 9.LaBresh KA, Fonarow GC, Smith SC, Jr, Bonow RO, Smaha LC, Tyler PA, Hong Y, Albright D, Ellrodt AG. Improved treatment of hospitalized coronary artery disease patients with the Get With The Guidelines program. Crit Pathw Cardiol. 2007;6:98-105 [DOI] [PubMed] [Google Scholar]
  • 10.Lewis WR, Peterson ED, Cannon CP, Super DM, LaBresh KA, Quealy K, Liang L, Fonarow GC. An organized approach to improvement in guideline adherence for acute myocardial infarction: results with the Get With The Guidelines Quality Improvement Program. Arch Intern Med. 2008;168:1813-1819 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimation equation approach. Biometrics. 1988;44:1049-1060 [PubMed] [Google Scholar]
  • 12.Rogers WJ, Frederick PD, Stoehr E, Canto JG, Ornato JP, Gibson CM, Pollack CV, Gore JM, Chandra-Strobos N, Peterson ED, French WJfor the National Registry of Myocardial Infarction Investigators Trends in presenting characteristics and hospital mortality among patients with ST elevation and non-ST elevation myocardial infarction in the National Registry of Myocardial Infarction from 1990 to 2006. Am Heart J. 2008;156:1026-1034 [DOI] [PubMed] [Google Scholar]
  • 13.Steg PG, Goldberg RJ, Gore JM, Fox KAA, Eagle KA, Flather MD, Sadiq I, Kasper R, Rushton-Mellor SKfor the GRACE Investigators Baseline characteristics, management and in-hospital outcomes of patients hospitalized with acute coronary syndromes in the Global Registry of Acute Coronary Events (GRACE). Am J Cardiol. 2002;90:358-363 [DOI] [PubMed] [Google Scholar]
  • 14.Yeh RW, Sidney S, Chandra M, Sorel M, Selby JV, Go AS. Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362:2155-2165 [DOI] [PubMed] [Google Scholar]
  • 15.Roger VL, Weston SA, Gerber Y, Killian JM, Dunlay SM, Jaffe AS, Bell MR, Kors J, Yawn BP, Jacobsen SJ. Trends in incidence, severity and outcome of hospitalized myocardial infarction. Circulation. 2010;121:863-869 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Alpert JS, Thygesen K, Antman E, Basand JP. Myocardial infarction redefined: a consensus document of the Joint European Society of Cardiology/American College of Cardiology Committee for the redefinition of myocardial infarction. J Am Coll Cardiol. 2000;36:959-969 [DOI] [PubMed] [Google Scholar]
  • 17.Ruff CT, Braunwald E. The evolving epidemiology of acute coronary syndromes. Nat Rev Cardiol. 2011;8:140-147 [DOI] [PubMed] [Google Scholar]
  • 18.Rosamond WD, Chambless LE, Heiss G, Moseley TH, Coresh J, Whitsel E, Wagenknecht L, Ni H, Folson AR. Twenty-two year trends in incidence of myocardial infarction, coronary heart disease mortality and case fatality in 4 US communities, 1987–2008. Circulation. 2012;125:1848-1857 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Gregg EW, Cheng YJ, Cadwell BL, Imperatore G, Williams DE, Flegal KM, Narayan KMV, Williamson DF. Secular trends in cardiovascular disease risk factors according to body mass index in US adults. JAMA. 2005;293:1868-1874 [DOI] [PubMed] [Google Scholar]
  • 20.Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment and control of hypertension in the United States, 1988–2000. JAMA. 2003;290:199-206 [DOI] [PubMed] [Google Scholar]
  • 21.Wijeysundera HC, Machado M, Farahati F, Wang X, Witteman W, ver der Velde G, Tu JV, Lee DS, Goodman SG, Petrella R, O'Flaherty M, Krahn M, Capewell S. Association of temporal trends in risk factors and treatment uptake with coronary heart disease mortality, 1994-2005. JAMA. 2010;303:1841-1847 [DOI] [PubMed] [Google Scholar]
  • 22.Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999–2008. JAMA. 2010;303:235-241 [DOI] [PubMed] [Google Scholar]
  • 23.Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA. 2012;307:491-497 [DOI] [PubMed] [Google Scholar]
  • 24.Mente A, Yusuf S, Islam S, McQueen MJ, Tanomsup S, Onen CL, Rangarajan S, Gerstein HCINTERHEART Investigators Metabolic syndrome and risk of acute myocardial infarction: a case–control study of 26,903 subjects from 52 countries. J Am Coll Cardiol. 2010;55:2390-2398 [DOI] [PubMed] [Google Scholar]
  • 25.Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults. JAMA. 2002;287:356-359 [DOI] [PubMed] [Google Scholar]
  • 26.Shay CM, Ning H, Allen NB, Carnethon MR, Chiuve SE, Greenlund KJ, Daviglus ML, Lloyd-Jones DM. Status of cardiovascular health in US adults. Circulation. 2012;125:45-56 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Yang Q, Cogswell ME, Flanders WD, Hong Y, Zhang A, Loustalot F, Gillespie C, Merritt R, Hu FB. Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults. JAMA. 2012;307:1273-1283 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.US Department of Health and Human Services. Healthy People 2020: Objectives and Topic Areas. Available at: http://healthypeople.gov/2020/topicsobjectives2020/pdfs/HP2020objectives.pdf. Accessed October 1, 2011.
  • 29.Koh H. A 2020 vision for healthy people. N Engl J Med. 2010;362:1653-1656 [DOI] [PubMed] [Google Scholar]
  • 30.Heidenreich PA, Trogdon JG, Khavjou OA, Butler J, Dracup K, Ezekowitz MD, Finkelstein EA, Hong Y, Johnston SC, Khera A, Lloyd-Jones DM, Nelson SA, Nichol G, Orenstein D, Wilson PW, Woo YJ. Forecasting the future of cardiovascular disease in the United States: a policy statement from the American Heart Association. Circulation. 2011;123:933-944 [DOI] [PubMed] [Google Scholar]
  • 31.Rose G.The Strategy of Preventive Medicine. 1992Oxford, UK: Oxford University Press [Google Scholar]
  • 32.Lloyd-Jones DM, Hong Y, Labarth D, Mozaffarian D, Appel LJ, Van Horn L, Greenlund K, Daniels S, Nichol G, Tomaselli GF, Arnett DK, Fonarow GC, Ho PM, Lauer MS, Masoudi FA, Robertson RM, Roger V, Schwamm LH, Sorlie P, Yancy CW, Rosamond WD. Defining and setting national goals for cardiovascular health promotion and disease reduction. Circulation. 2010;121:586-613 [DOI] [PubMed] [Google Scholar]
  • 33.Reeves MJ, Fonarow GC, Smith EE, Pan W, Olson D, Hernandez AF, Peterson ED, Schwamm LH. Representativeness of the Get With The Guidelines–Stroke Registry. Stroke. 2012;43:44-49 [DOI] [PubMed] [Google Scholar]
  • 34.Mosca L, Barrett-Connor E, Wenger NK. Sex/gender differences in cardiovascular disease prevention: what a difference a decade makes. Circulation. 2011;124:2145-2154 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Diercks DB, Owen KP, Kontos MC, Blomkalns A, Chen AY, Miller C, Wiviott S, Peterson ED. Gender differences in time to presentation for myocardial infarction before and after a national women's cardiovascular awareness campaign. Am Heart J. 2010;160:80.e3-87.e3 [DOI] [PubMed] [Google Scholar]
  • 36.Greenland S. Model based estimation of relative risks and other epidemiologic measures in the studies of common outcomes and in case–control studies. Ann Epidemiol. 2009;160:301-305 [DOI] [PubMed] [Google Scholar]
  • 37.Jokhadar M, Jacobsen SJ, Reeder GS, Weston SA, Roger VL. Sudden death and recurrent ischemic events after myocardial infarction in the community. Am J Epidemiol. 2004;159:1040-1046 [DOI] [PubMed] [Google Scholar]

Articles from Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease are provided here courtesy of Wiley

RESOURCES