Abstract
Objectives To examine 25 year trends in first time hospitalisation for acute myocardial infarction in Denmark, subsequent short and long term mortality, and the prognostic impact of sex and comorbidity.
Design Nationwide population based cohort study using medical registries.
Setting All hospitals in Denmark.
Subjects 234 331 patients with a first time hospitalisation for myocardial infarction from 1984 through 2008.
Main outcome measures Standardised incidence rate of myocardial infarction and 30 day and 31–365 day mortality by sex. Comorbidity categories were defined as normal, moderate, severe, and very severe according to the Charlson comorbidity index, and were compared by means of mortality rate ratios based on Cox regression.
Results The standardised incidence rate per 100 000 people decreased in the 25 year period by 37% for women (from 209 to 131) and by 48% for men (from 410 to 213). The 30 day, 31–365 day, and one year mortality declined from 31.4%, 15.6%, and 42.1% in 1984–8 to 14.8%, 11.1%, and 24.2% in 2004–8, respectively. After adjustment for age at time of myocardial infarction, men and women had the same one year risk of dying. The mortality reduction was independent of comorbidity category. Comparing patients with very severe versus normal comorbidity during 2004–8, the mortality rate ratio, adjusted for age and sex, was 1.96 (95% CI 1.83 to 2.11) within 30 days and 3.89 (3.58 to 4.24) within 31–365 days.
Conclusions The rate of first time hospitalisation for myocardial infarction and subsequent short term mortality both declined by nearly half between 1984 and 2008. The reduction in mortality occurred for all patients, independent of sex and comorbidity. However, comorbidity burden was a strong prognostic factor for short and long term mortality, while sex was not.
Introduction
Despite considerable improvements in prophylaxis and treatment,1 2 3 myocardial infarction remains a common life threatening disease and an enormous burden on Western healthcare systems.1 The incidence of and mortality from myocardial infarction are not continuously monitored by surveillance registries, despite the critical need for ongoing evaluation of its primary and tertiary prevention.
As people age, they are more likely to develop chronic medical conditions. About 45% of the adult population has at least one chronic disease.4 This proportion increases to 90% in persons older than 65 years,4 who represent more than half of patients with myocardial infarction.5 Myocardial infarction shares risk factors with many chronic diseases (such as obesity, diabetes, chronic obstructive pulmonary disease, and cancer6), increasing the prevalence of comorbidity among patients with myocardial infarction.7 8 Comorbidity potentially modifies effectiveness of therapies and the clinical course of a myocardial infarction.8 9 However, clinical guidelines for treatment of myocardial infarction are based on the results of trials that often exclude patients of advanced age or with a large number of comorbid conditions.10
With the availability of new therapies that also benefit older patients,11 it has become increasingly important to understand the impact of comorbidity on the prognosis of myocardial infarction and to determine whether trends in survival apply to all patients with myocardial infarction.12 Previous studies on this topic have been limited by size (<4100 participants),9 13 inclusion period (<6 years),9 13 or selective inclusion of patients from specific hospitals9 13 or age groups.9 Also, the prognostic impact of sex remains unclear because of conflicting study findings.14 15 16 17 We therefore conducted a nationwide, population based, cohort study to examine trends in first time hospitalisation for myocardial infarction over the 25 year period from 1984 to 2008, subsequent short term and long term mortality, and the prognostic impact of sex and comorbidity.
Methods
Setting
We conducted this cohort study in Denmark, which has 5.4 million inhabitants. The Danish National Health Service provides universal, tax supported, healthcare, guaranteeing unfettered access to general practitioners and hospitals and partial reimbursement for prescribed drugs. Accurate and unambiguous linkage of all registries at the individual level is possible in Denmark by means of the unique central personal registry number assigned to each Danish citizen at birth and to residents on immigration.18
Acute myocardial infarction
We used the Danish National Registry of Patients19 to identify all first time hospitalisations for myocardial infarction from 1 January 1984 to 31 December 2008 among Danish born inhabitants aged 15 years or older. This registry contains data on dates of admission and discharge from all Danish non-psychiatric hospitals since 1977 and from emergency room and outpatient clinic visits since 1995.19 Each hospital discharge or outpatient visit is recorded in the registry with one primary diagnosis and one or more secondary diagnoses classified according to ICD-8 (international classification of diseases, 8th revision) until the end of 1993 and ICD-10 (10th revision) thereafter.19 Patients with myocardial infarction are included in the Danish National Registry of Patients if they died in the ambulance on the way to the hospital or during the hospital admission, but not if they died at home. We used ICD-8 codes 410.09 and 410.99 and ICD-10 code I21 to identify myocardial infarction.
Mortality
We obtained information on all cause mortality until the end of 2009 from the Danish Civil Registration System.18 20 This registry has recorded all changes in vital status and migration for the entire Danish population since 1968, with daily electronic updates.18
Comorbidity
We obtained information on comorbid conditions from inpatient and outpatient hospital diagnoses (all available primary or secondary diagnoses) recorded in the Danish National Registry of Patients in the five years before the myocardial infarction. To avoid inclusion of complications caused by the myocardial infarction, secondary diagnoses coded during the admission for myocardial infarction were excluded. We categorised the severity of comorbidity using the Charlson comorbidity index,21 a scoring system that has been adapted for use with hospital discharge data9 and validated for patients with acute and chronic ischaemic heart disease.8 9 22 23 The index assigns between one and six points to a range of diseases, depending on the strength of their relation to mortality in the subsequent year (during the era when the Charlson comorbidity index was developed): one point for myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, connective tissue disease, ulcer disease, mild liver disease, and diabetes without end organ damage; two points for diabetes with end organ damage, hemiplegia, moderate to severe renal disease, non-metastatic solid tumour, leukaemia, and lymphoma; three points for moderate to severe liver disease; six points for metastatic cancer and AIDS. We computed the total Charlson score for each patient and defined four categories of comorbidity as used in the Predicting Risk of Death in Cardiac Disease Tool (PREDICT) study—that is, total scores of 0 (normal), 1 (moderate), 2 (severe), and ≥3 (very severe).22 Myocardial infarction was not included in the scoring. The Charlson comorbidity index and associated ICD codes are provided in web extra table A on bmj.com.
Statistical analysis
We computed and illustrated graphically the incidence rate of myocardial infarction (standardised to the age distribution of the Danish population in the year 2000) and subsequent 30 day and 31–365 day mortality (standardised to the age distribution of the population diagnosed with myocardial infarction in the year 2000) for men and women from 1984 through 2008.23 We calculated confidence intervals using the approximate bootstrap method.24 25 We repeated the analyses for subgroups of patients aged 35–49, 50–59, 60–69, 70–79, and ≥80 years.
We then characterised patients with myocardial infarction according to sex, age, and comorbidity category, overall and for five calendar periods of diagnosis (1984–8, 1989–93, 1994–8, 1999–2003, and 2004–8). We calculated the prevalence of individual Charlson comorbidities registered in the five years preceding the admission for myocardial infarction. We illustrated graphically the change in median age from 1984 through 2008 for both men and women.
We followed all patients until the date of death, emigration, or one year of follow-up, whichever came first. Using the Kaplan-Meier estimator,25 we computed the 30 day and 31–365 day mortality risk associated with each calendar period of diagnosis and comorbidity category. We used Cox proportional hazards regression to estimate the mortality rate ratio (specifically, the hazard ratio) associated with calendar period of diagnosis and comorbidity category within 30 days and 31–365 days after myocardial infarction.
First, we compared mortality rates across calendar periods, using the earliest period as the reference and adjusting for sex, age groups, and comorbidity categories. To evaluate the potential for residual confounding by age and comorbidity, we repeated the analysis modelling age and comorbidity by three knot cubic splines.25 The results were consistent with the categorical modelling strategy and are therefore not reported further. Second, we compared mortality rates across comorbidity categories, using normal comorbidity category as the reference and adjusting for sex and age groups. Within the 2004–8 calendar period of diagnosis, we also examined the 30 day and 31–365 day mortality rate ratios associated with the individual Charlson comorbidities, adjusting for the other comorbidities, age, and sex. The proportional hazards assumption was assessed graphically by plotting log(−log(survival function)) against time for all exposure variables and found to be valid.25
Results
Incidence
We identified 234 331 first time hospitalisations for myocardial infarction in Denmark from 1984 through 2008. The Danish population in this 25 year period consisted of 5 610 039 Danish born inhabitants aged 15 years or older. The annual standardised incidence rate of myocardial infarction (per 100 000 people) decreased during this period, by 37% for women (from 209 to 131) and by 48% for men (from 410 to 213) (fig 1). A transient increase in incidence occurred between 2000 and 2004 (fig 1). It was driven by the incidence among people aged ≥70 years, particularly those aged ≥80 years (fig 2). For patients younger than 70 years, the incidence steadily decreased throughout the 25 year period (fig 2).
Fig 1 Standardised incidence rates for first time hospitalisation for myocardial infarction in Denmark between 1984 and 2008 among men and women
Fig 2 Standardised incidence rates for first time hospitalisation for myocardial infarction between 1984 and 2008, for men and women within age groups
Patient characteristics
Although the female proportion of patients with myocardial infarction increased slightly between the first five year calendar period (35.8%) and the last (38.8%), men still accounted for the majority (62.1%) of all hospitalisations for myocardial infarction (table 1). The median age at time of diagnosis was 75 years for women and 68 for men. While the median age held fairly steady at about 68 years for men, it increased for women from 74 years in 1984 to 77 years in 2008 (web extra fig A on bmj.com). The prevalence of patients with normal comorbidity burden fell from 75.5% to 63.8% between the earliest and latest calendar period (table 1). The percentage of patients with moderate comorbidity increased from 13.2% to 16.2%, the percentage with severe comorbidity increased from 7.4% to 10.5%, and the percentage with very severe comorbidity increased from 3.9% to 9.6% (the prevalence for Charlson scores 1 to 10 is provided in web extra table B). The most prevalent Charlson comorbidities were diabetes (7.0%), stroke (7.0%), congestive heart failure (5.8%), chronic pulmonary disease (5.8%), peripheral vascular disease (5.3%), cancer (5.4%), ulcer disease (2.5%), connective tissue disease (2.1%), and severe renal disease (1.6%).
Table 1.
Numbers (percentages) of people with a first time hospitalisation for myocardial infarction in Denmark in five year periods from 1984 through 2008 by sex, age, and comorbidity category
| Calendar periods of diagnosis | Total (n=234 331) | |||||
|---|---|---|---|---|---|---|
| 1984–8 (n=56 454) | 1989–93 (n=50 249) | 1994–8 (n=42 261) | 1999–2003 (n=44 365) | 2004–8 (n=41 002) | ||
| Sex: | ||||||
| Female | 20 201 (35.8) | 18 691 (37.2) | 16 238 (38.4) | 17 652 (39.8) | 15 926 (38.8) | 88 708 (37.9) |
| Male | 36 253 (64.2) | 31 558 (62.8) | 26 023 (61.6) | 26 713 (60.2) | 25 076 (61.2) | 145 623 (62.1) |
| Age (years): | ||||||
| 15–34 | 206 (0.4) | 196 (0.4) | 223 (0.5) | 228 (0.5) | 224 (0.5) | 1 077 (0.5) |
| 35–49 | 3 845 (6.8) | 3 521 (7.0) | 2 974 (7.0) | 3 172 (7.1) | 3 185 (7.8) | 16 697 (7.1) |
| 50–59 | 8 334 (14.8) | 7 241 (14.4) | 6 176 (14.6) | 6 859 (15.5) | 6 296 (15.4) | 34 906 (14.9) |
| 60–69 | 15 610 (27.7) | 12 978 (25.8) | 10 020 (23.7) | 9 604 (21.6) | 9 227 (22.5) | 57 439 (24.5) |
| 70–79 | 18 465 (32.7) | 16 080 (32.0) | 13 309 (31.5) | 12 617 (28.4) | 10 526 (25.7) | 70 997 (30.3) |
| ≥80 | 9 994 (17.7) | 10 233 (20.4) | 9 559 (22.6) | 11 885 (26.8) | 11 544 (28.2) | 53 215 (22.7) |
| Comorbidity category*: | ||||||
| Normal | 42 645 (75.5) | 37 771 (75.2) | 30 041 (71.1) | 28 323 (63.8) | 26 157 (63.8) | 164 937 (70.4) |
| Moderate | 7 455 (13.2) | 6 845 (13.6) | 6 409 (15.2) | 7 599 (17.1) | 6 633 (16.2) | 34 941 (14.9) |
| Severe | 4 168 (7.4) | 3 701 (7.4) | 3 571 (8.4) | 4 592 (10.4) | 4 295 (10.5) | 20 327 (8.7) |
| Very severe | 2 186 (3.9) | 1 932 (3.8) | 2 240 (5.3) | 3 851 (8.7) | 3 917 (9.6) | 14 126 (6.0) |
*Categories of comorbidity were based on Charlson comorbidity index scores of 0 (normal), 1 (moderate), 2 (severe), and ≥3 (very severe).
Mortality
The standardised 30 day and 31–365 day mortality risks after first time myocardial infarction were similar for men and women, decreasing comparably between 1984 and 2008 (fig 3). The 30 day mortality declined from 31.4% (95% confidence interval: 31.0% to 31.8%) during 1984–8 to 14.8% (14.5% to 15.2%) during 2004–8 (table 2). The one year mortality declined overall from 42.1% (41.7% to 42.5%) during 1984–8 to 24.2% (23.8% to 24.7%) during 2004–8; and among 30 day survivors it fell from 15.6% (15.2% to 16.0%) during 1984–8 to 11.1% (10.7% to 11.4%) during 2004–8. When the latest five year period was compared with the earliest, the mortality rate ratio adjusted for age and comorbidity category was 0.37 (95% confidence interval 0.35 to 0.38) within 30 days and 0.48 (0.47 to 0.51) within 31–365 days. Age stratified analyses revealed no difference in mortality among men and women within age categories (web extra fig B on bmj.com).
Fig 3 Standardised 30 day and 31–365 day mortality after first time hospitalisation for myocardial infarction among men and women between 1984 and 2008.
Table 2.
30 day and 31–365 day mortality risk and mortality rate ratio after first time hospitalisation for myocardial infarction in Denmark in five year periods of diagnosis from 1984 through 2008
| Period of diagnosis | No of patients | Median age (years) | 30 day mortality | 31–365 day mortality | |||||
|---|---|---|---|---|---|---|---|---|---|
| Mortality risk % (95% CI) | Mortality rate ratio (95% CI) | Mortality risk % (95% CI) | Mortality rate ratio (95% CI) | ||||||
| Unadjusted | Adjusted* | Unadjusted | Adjusted* | ||||||
| 1984–8 | 56 454 | 70 | 31.4 (31.0 to 31.8) | 1 (reference) | 1 (reference) | 15.6 (15.2 to 16.0) | 1 (reference) | 1 (reference) | |
| 1989–93 | 50 249 | 70 | 27.4 (27.1 to 27.8) | 0.86 (0.84 to 0.88) | 0.84 (0.82 to 0.86) | 13.2 (12.9 to 13.6) | 0.83 (0.80 to 0.87) | 0.79 (0.76 to 0.82) | |
| 1994–8 | 42 261 | 71 | 23.8 (23.4 to 24.2) | 0.73 (0.71 to 0.75) | 0.68 (0.67 to 0.70) | 11.7 (11.3 to 12.0) | 0.73 (0.70 to 0.76) | 0.63 (0.60 to 0.66) | |
| 1999–2003 | 44 365 | 72 | 18.1 (17.8 to 18.5) | 0.54 (0.52 to 0.55) | 0.46 (0.45 to 0.47) | 12.2 (11.8 to 12.5) | 0.76 (0.73 to 0.79) | 0.56 (0.54 to 0.58) | |
| 2004–8 | 41 002 | 71 | 14.8 (14.5 to 15.2) | 0.43 (0.42 to 0.44) | 0.37 (0.35 to 0.38) | 11.1 (10.7 to 11.4) | 0.69 (0.66 to 0.72) | 0.48 (0.47 to 0.51) | |
*Adjusted for age, sex, and comorbidity category.
Prognostic impact of comorbidity
The improvement in mortality after myocardial infarction between 1984 and 2008 was observed for all patients in all age groups, independent of their comorbidity category (fig 4). The 30 day and 31–365 day mortality risks were strongly associated with the patient’s category of comorbidity for all five year calendar periods (web extra table C on bmj.com). With normal comorbidity category as the reference, the mortality rate ratios adjusted for age and sex among patients with moderate comorbidity in 2004–8 were 1.35 (95% confidence interval 1.26 to 1.45) within 30 days and 1.83 (1.68 to 2.00) within 31–365 days (table 3). Comparing patients with very severe and normal comorbidity in 2004–8, the adjusted mortality rate ratios were 1.96 (1.83 to 2.11) within 30 days and 3.89 (3.58 to 4.24) within 31–365 days (table 3). The magnitude of the increased mortality rate ratios associated with increasing comorbidity categories was similar across calendar periods (web extra table C). Consistent with the principle that effect estimates are higher among those at lower baseline risk, we found that age modified the mortality rate ratio associated with each comorbidity category, with higher estimates in younger age groups (web extra table D).
Fig 4 30 day and 31–365 day mortality after first time hospitalisation for myocardial infarction between 1984 and 2008, according to comorbidity category.
Table 3.
30 day and 31–365 day mortality risk and mortality rate ratio after first time hospitalisation for myocardial infarction in Denmark between 2004 and 2008 associated with comorbidity category
| Comorbidity category* | No of patients | 30 day mortality | 31–365 day mortality | |||||
|---|---|---|---|---|---|---|---|---|
| Mortality risk % (95% CI) | Mortality rate ratio (95% CI) | Mortality risk % (95% CI) | Mortality rate ratio (95% CI) | |||||
| Unadjusted | Adjusted† | Unadjusted | Adjusted† | |||||
| Normal | 26 157 | 10.8 (10.4 to 11.2) | 1 (reference) | 1 (reference) | 6.2 (5.9 to 6.5) | 1 (reference) | 1 (reference) | |
| Moderate | 6633 | 19.2 (18.3 to 20.2) | 1.85 (1.73 to 1.98) | 1.35 (1.26 to 1.45) | 15.5 (14.6 to 16.5) | 2.64 (2.42 to 2.87) | 1.83 (1.68 to 2.00) | |
| Severe | 4295 | 21.4 (20.2 to 22.7) | 2.09 (1.94 to 2.25) | 1.52 (1.41 to 1.64) | 20.6 (19.3 to 22.1) | 3.61 (3.30 to 3.96) | 2.50 (2.29 to 2.74) | |
| Very severe | 3917 | 27.1 (25.7 to 28.5) | 2.72 (2.53 to 2.91) | 1.96 (1.83 to 2.11) | 31.2 (29.5 to 32.9) | 5.80 (5.34 to 6.31) | 3.89 (3.58 to 4.24) | |
* Categories of comorbidity were based on Charlson comorbidity index scores of 0 (normal), 1 (moderate), 2 (severe), and ≥3 (very severe).
†Adjusted for sex and age.
Among the individual non-malignant comorbidities, liver disease and dementia were each associated with a roughly doubled mortality rate within 30 days after myocardial infarction compared with patients without comorbidity (table 4). Within 31–365 days, twofold increased mortality rate ratios were also observed for patients with moderate to severe liver or renal diseases. Congestive heart failure, peripheral or cerebrovascular vascular disease, chronic pulmonary disease, and ulcer disease were associated with a 1.2 to 1.3-fold increased mortality rate ratio within 30 days, increasing to 1.5-fold within 31–365 days. Diabetes with end organ damage was associated with 1.3-fold increased short term and long term mortality rate ratios, whereas connective tissue disease was not.
Table 4.
30 day and 31–365 day mortality rate ratios associated with individual comorbidities after first time hospitalisation for myocardial infarction in Denmark between 2004 and 2008
| Adjusted mortality rate ratio (95% CI)* | ||
|---|---|---|
| 30 day | 31-365 days | |
| No comorbid diseases | 1 (reference) | 1 (reference) |
| Congestive heart failure | 1.30 (1.20 to 1.41) | 1.62 (1.48 to 1.78) |
| Peripheral vascular disease | 1.23 (1.13 to 1.34) | 1.47 (1.33 to 1.62) |
| Cerebrovascular disease | 1.21 (1.12 to 1.30) | 1.52 (1.39 to 1.65) |
| Dementia | 1.81 (1.60 to 2.05) | 1.52 (1.28 to 1.81) |
| Chronic pulmonary disease | 1.21 (1.12 to 1.31) | 1.54 (1.41 to 1.68) |
| Connective tissue disease | 0.95 (0.82 to 1.09) | 1.05 (0.89 to 1.23) |
| Ulcer disease | 1.24 (1.10 to 1.39) | 1.50 (1.31 to 1.72) |
| Mild liver disease | 2.00 (1.48 to 2.71) | 1.80 (1.22 to 2.67) |
| Diabetes without end organ damage | 0.99 (0.89 to 1.09) | 1.19 (1.05 to 1.34) |
| Diabetes with end organ damage | 1.30 (1.16 to 1.46) | 1.25 (1.09 to 1.44) |
| Hemiplegia | 1.32 (0.79 to 2.19) | 1.68 (0.97 to 2.89) |
| Moderate to severe renal disease | 1.26 (1.11 to 1.42) | 2.08 (1.83 to 2.36) |
| Non-metastatic solid tumour | 1.22 (1.12 to 1.34) | 1.69 (1.53 to 1.87) |
| Leukaemia | 1.85 (1.32 to 2.59) | 1.89 (1.21 to 2.95) |
| Lymphoma | 1.40 (1.07 to 1.83) | 1.60 (1.15 to 2.22) |
| Moderate to severe liver disease | 2.21 (1.34 to 3.64) | 1.97 (0.94 to 4.10) |
| Metastatic cancer | 1.58 (1.25 to 2.01) | 2.91 (2.33 to 3.63) |
AIDS was omitted from the table because of its low prevalence (<0.1%).
*Adjusted for the other comorbidities, age, and sex.
Discussion
In this nationwide cohort study, we found an almost 50% reduction both in the first time hospitalisation for myocardial infarction between 1984 and 2008 and in subsequent short term mortality. During the same period, one year mortality among 30 day survivors declined by a third. The improved survival since 1984 applied to all myocardial infarction patients independently of sex and comorbidity. However, the comorbidity burden measured five years before admission was a strong predictor of mortality within 30 days after myocardial infarction and during the remainder of the first year, whereas sex was not.
Strengths and limitations of study
Several issues should be considered in interpreting our results. The population based design in a country with universal healthcare reduced selection biases stemming from selective inclusion of specific hospitals, health insurance systems, or age groups. All patients were followed until death, emigration, or end of follow-up, and hence no one had incomplete registration.
The positive predictive values of diagnoses in the Danish National Registry of Patients have previously been validated and found to exceed 90% for both myocardial infarction (>90%)26 and the Charlson comorbidities (98% overall).27 A potential limitation was that patients with sudden cardiac death outside hospital or ambulance or who did not receive a resuscitation attempt at the emergency room were not registered in the Danish National Registry of Patients. To address this limitation, we compared over time the proportion of patients who had myocardial infarctions recorded as cause of death in the Danish Register of Causes of Death without having it or a previous myocardial infarction recorded in the Danish National Registry of Patients. This supplementary analysis revealed that such patients could not account for the observed incidence and mortality trends.
Other diseases such as diabetes and chronic pulmonary disease are likely to be under-represented in the Danish National Registry of Patients, because some patients are treated in primary care only. Although the 7% prevalence of diabetes among patients with myocardial infarction is substantially lower than in other Western countries,2 it is only slightly lower than reported in the second Danish trial on Acute Myocardial Infarction (DANAMI-2) (11%).28 Also, because the comparisons were made within a population of patients with myocardial infarction, underascertainment of comorbidities is unlikely to influence substantially the relative mortality estimates associated with comorbidity categories. The mortality data from the Danish Civil Registration System are virtually complete.18
As suggested for stable angina pectoris patients,23 the Charlson comorbidity index could potentially be made even more appropriate for patients with myocardial infarction by assigning greater weight to some diseases (such as liver and renal disease) and omitting others lacking prognostic significance among patients with myocardial infarction (such as connective tissue disease) or with low prevalence (such as hemiplegia, leukaemia, and AIDS).23 29 Also, peripheral and cerebrovascular disease may to some extent represent “disease staging” of underlying atherosclerosis that has progressed to multiple vascular systems, rather than representing separate disease entities.29 However, despite these limitations regarding individual comorbidities, the Charlson comorbidity index in its original form has proved an adequate tool for measuring the prognostic impact of total comorbidity burden in patients with myocardial infarction.9 30
Comparison with other studies
Our study is the first to examine nationwide 25 year trends in myocardial infarction epidemiology. Its results are in line with previous US,31 32 33 34 35 36 37 38 39 40 41 UK,42 43 Australian,44 and multinational3 45 studies examining trends in the incidence and outcomes of myocardial infarction. Compared with our study, these studies were conducted over shorter time periods,34 35 36 37 38 39 40 41 42 43 44 45 with data collection before the definition of myocardial infarction was amended in 2000,32 33 34 38 42 45 or in modest sized cohorts such as the Atherosclerosis Risk in Communities Study,35 Framingham Heart Study,32 33 Minnesota Heart Survey,34 Perth MONICA (Monitoring Trends and Determinants in Cardiovascular Disease) cohort,44 or Worcester Heart Attack Study.31 39
It is estimated that half of the decline in mortality since 1980 is attributable to primary prevention of myocardial infarction—that is, reduction in the prevalence of major cardiovascular risk factors such as smoking, sedentary lifestyle, and uncontrolled high blood pressure.1 2 The other half is attributable to the introduction of thrombolysis, coronary artery bypass grafting, percutaneous coronary intervention, and improved tertiary medical prevention with antiplatelet regimens, β blockers, angiotensin converting enzyme inhibitors, and statins.1 3 It is noteworthy that the incidence of myocardial infarction has continued to decline despite increased prevalence of obesity and diabetes.1 2 The transient increase in incidence between 2000 and 2004 with local maximum in 2002 was presumably attributable to new diagnostic criteria that included troponin as the main diagnostic biomarker of myocardial infarction.46 Although we did not discriminate between ST segment and non-ST segment elevation myocardial infarction, the changing biomarker use is likely to have increased the detection rate of smaller infarcts and thus predominantly the rates of non-ST segment elevation myocardial infarction.35 36
We observed a larger decrease in myocardial infarction incidence among men than women until 1997, after which the decreasing trend seemed independent of sex. One explanation for this difference is that cardiovascular disease previously was considered primarily a man’s disease, and thus cardiovascular disease prevention primarily focused on risk modification among men. Also, within the last two to three decades, the lifestyles and risk behaviours of women and men became more similar with regard to smoking, sedentary work, and working outside the home. We observed that sex did not influence the prognosis of myocardial infarction as previously suggested.14 15 Thus, age is the single most important prognostic factor to control for when comparing mortality from myocardial infarction between men and women.16 17 47
Our study is also the first to examine the short and long term mortality risks and rates associated with comorbidity burden in a nationwide population. We observed increased levels of comorbidity over time. This trend may, however, be explained partly by the increase in age at time of diagnosis, a more complete disease registration (owing to the addition of outpatient clinic diagnoses in the Danish National Registry of Patients) from 1995 onwards, and the introduction of the diagnosis related group system as a prospective payment system around 2000. Because short term mortality is likely to be closely related to the severity and progression of myocardial infarction, it is notable that comorbidity had a substantial influence on 30 day mortality. Also important, we found that improvements in survival among patients with myocardial infarction occurred independently of their comorbidity burden. In contrast, survival improvements for other major diseases, such as breast cancer, depend on patients’ comorbidity categories, with poorer survival improvement among those with severe comorbidity.12
Our large study, including nearly 250 000 patients, extends the results of two smaller studies that also examined the prognostic impact of comorbidity burden as classified by the Charlson comorbidity index.9 13 O’Connell et al based their analysis on the MONICA study of 4081 people aged 25–69 years who were admitted for myocardial infarction between 1988 and 1994 and who survived for at least 28 days.9 Their reported association between comorbidity and mortality (adjusted hazard ratio 1.36 (95% confidence interval 1.07 to 1.72) for moderate to severe comorbidity and 2.74 (1.73 to 4.34) for very severe comorbidity) was consistent with our results. Núñez et al examined the association between comorbidity and mortality among 1035 patients admitted to hospital with myocardial infarction between 2000 and 2003.13 The 30 day and one year mortality rate ratios that they reported were consistent with our results for the calendar period 1999–2003.
Comorbidity may influence the prognosis of myocardial infarction in several ways. Comorbid conditions may directly alter the effectiveness of treatments and affect the course of myocardial infarction. Although comorbidities are likely to increase non-cardiac mortality in particular,48 the increased short term mortality also suggests an impact on cardiac mortality. Underuse of coronary reperfusion therapy among patients with comorbid diseases may account for some of the increased mortality associated with comorbidity within the first 30 days after hospitalisation for myocardial infarction.7
Generalisability, implications, and conclusions
The observed trend for incidence and mortality of myocardial infarction are likely generalisable to most industrial Western societies where changes in lifestyle, risk factor modification, and increasing use of aggressive medical and interventional treatment have followed international recommendations.2 Furthermore, the ratio of mortality rates associated with comorbidity categories should be unbiased because the comparisons over time were made between patients all with myocardial infarction.25
Our findings have implications for research and clinical care. Clinical trials should include patients with prevalent comorbid illness so that results may be extrapolated to the entire spectrum of patients with myocardial infarction.5 Cardiovascular disease registries should measure comorbidities to permit fair inferences regarding mortality, process of care, and risk stratification after myocardial infarction.8 22 Finally, comorbidity should be considered in individual patient counselling, with treatment optimised to improve the outcome both of the comorbid condition and the myocardial infarction. Our findings are particularly important for elderly people, given their high prevalence of comorbidity4 and the increasing numbers of people of advanced age facing treatment decisions for coronary artery disease.4 5
In conclusion, we found that the rate of first time hospitalisation for myocardial infarction and subsequent short term mortality both declined by nearly half between 1984 and 2008. The reduction in mortality occurred for all patients, independent of sex and the severity of comorbidity. However, comorbidity burden was a strong prognostic factor for short and long term mortality, while sex was not.
What is already known on this topic
A marked decrease in incidence of acute myocardial infarction and associated mortality has occurred since 1980
As the population ages, an increasing proportion of patients with myocardial infarction will have comorbidities
What this study adds
This study of all 234 331 patients hospitalised in Denmark with first time myocardial infarction between 1984 and 2008 showed a near halving of incidence and short term mortality of myocardial infarction
The reduction in mortality occurred for all patients with myocardial infarction independent of sex and comorbidity
Comorbidity burden was a strong independent predictor of short term and long term mortality, while sex was not
Contributorship: MS, JBJ, and HTS conceived the study idea and designed the study. JBJ and HTS collected the data. MS, HEB, and HTS reviewed the literature. MS, JBJ, TLL, and HTS directed the analyses, which were carried out by JBJ. All authors participated in the discussion and interpretation of the results. MS organised the writing and wrote the initial drafts. All authors critically revised the manuscript for intellectual content and approved the final version. HTS is the guarantor.
Funding: The study was supported by the Danish Medical Research Council (grant 271-05-0511), the Clinical Epidemiological Research Foundation, Denmark, and Aarhus University. None of the funding sources had a role in the design, conduct, analysis, or reporting of the study.
Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare that (1) no authors have support from any company for the submitted work. Department of Clinical Epidemiology is, however, involved in studies with funding from various companies as research grants to (and administered by) Aarhus University. None of these studies have relation to the present study; (2) no authors have relationships with companies that might have an interest in the submitted work in the previous 3 years; (3) their spouses, partners, or children have no financial relationships that may be relevant to the submitted work; and (4) no authors have non-financial interests that may be relevant to the submitted work.
Ethical approval: Not needed.
Data sharing: No additional data available.
Cite this as: BMJ 2012;344:e356
Web Extra. Extra material supplied by the author
Supplementary figures A and B
Supplementary tables A–D
References
- 1.Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, et al. Explaining the decrease in US deaths from coronary disease, 1980-2000. N Eng J Med 2007;356:2388-98. [DOI] [PubMed] [Google Scholar]
- 2.Steinberg BA, Bhatt DL, Mehta S, Poole-Wilson PA, O’Hagan P, Montalescot G, et al. Nine-year trends in achievement of risk factor goals in the US and European outpatients with cardiovascular disease. Am Heart J 2008;156:719-27. [DOI] [PubMed] [Google Scholar]
- 3.Fox KA, Steg PG, Eagle KA, Goodman SG, Anderson FA, Granger CB, et al. Decline in rates of death and heart failure in acute coronary syndromes, 1999-2006. JAMA 2007;297:1892-900. [DOI] [PubMed] [Google Scholar]
- 4.Wolff JL, Starfield B, Anderson G. Prevalence, expenditures, and complications of multiple chronic conditions in the elderly. Arch Intern Med 2002;162:2269-76. [DOI] [PubMed] [Google Scholar]
- 5.Beller GA. Are you ever too old to be risk stratified? J Am Coll Cardiol 1992;19:1399-401. [DOI] [PubMed] [Google Scholar]
- 6.Eyre H, Kahn R, Robertson RM, Clark NG, Doyle C, Hong Y, et al. Preventing cancer, cardiovascular disease, and diabetes: a common agenda for the American Cancer Society, the American Diabetes Association, and the American Heart Association. Circulation 2004;109:3244-55. [DOI] [PubMed] [Google Scholar]
- 7.Balzi D, Barchielli A, Buiatti E, Franceschini C, Lavecchia R, Monami M, et al. Effect of comorbidity on coronary reperfusion strategy and long-term mortality after acute myocardial infarction. Am Heart J 2006;151:1094-100. [DOI] [PubMed] [Google Scholar]
- 8.Singh M. Scores for post-myocardial infarction risk stratification in the community. Circulation 2002;106:2309-14. [DOI] [PubMed] [Google Scholar]
- 9.O’Connell RL, Lim LL. Utility of the Charlson comorbidity index computed from routinely collected hospital discharge diagnosis codes. Methods Inf Med 2000;39:7-11. [PubMed] [Google Scholar]
- 10.Krumholz HM, Gross CP, Peterson ED, Barron HV, Radford MJ, Parsons LS, et al. Is there evidence of implicit exclusion criteria for elderly subjects in randomized trials? Evidence from the GUSTO-1 study. Am Heart J 2003;146:839-47. [DOI] [PubMed] [Google Scholar]
- 11.Newell MC, Henry JT, Henry TD, Duval S, Browning JA, Christiansen EC, et al. Impact of age on treatment and outcomes in ST-elevation myocardial infarction. Am Heart J 2011;161:664-72. [DOI] [PubMed] [Google Scholar]
- 12.Cronin-Fenton D, Nørgaard M, Jacobsen JF, Garne J, Ewertz M, Lash TL, et al. Comorbidity and survival of Danish breast cancer patients from 1995 to 2005. Br J Cancer 2007;96:1462-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Núñez JE, Núñez E, Fácila L, Bertomeu V, Llàcer A, Bodí V, et al. [Prognostic value of Charlson comorbidity index at 30 days and 1 year after acute myocardial infarction.] Rev Esp Cardiol 2004;57:842-9. [PubMed] [Google Scholar]
- 14.Hochman JS, Tamis JE, Thompson TD, Weaver WD, White HD, Van De Werf F, et al. Global Use of Strategies to Open Occluded Coronary Arteries in Acute Coronary Syndromes IIb Investigators. Sex, clinical presentation, and outcome in patients with acute coronary syndromes. N Eng J Med 1999;341:226-32. [DOI] [PubMed] [Google Scholar]
- 15.Bairey Merz CN, Shaw LJ, Reis SE, Bittner V, Kelsey SF, Olson M, et al. Insights from the NHLBI-Sponsored Women’s Ischemia Syndrome Evaluation (WISE) Study: Part II: gender differences in presentation, diagnosis, and outcome with regard to gender-based pathophysiology of atherosclerosis and macrovascular and microvascular coronary disease. J Am Coll Cardiol 2006;47:S21-9. [DOI] [PubMed] [Google Scholar]
- 16.MacIntyre K, Stewart S, Capewell S, Chalmers JW, Pell JP, Boyd J, et al. Gender and survival: a population-based study of 201,114 men and women following a first acute myocardial infarction. J Am Coll Cardiol 2001;38:729-35. [DOI] [PubMed] [Google Scholar]
- 17.Nicolau JC, Auxiliadora Ferraz M, Nogueira PR, Coimbra Garzon SA, Serrano CV, Ramires JA. The role of gender in the long-term prognosis of patients with myocardial infarction submitted to fibrinolytic treatment. Ann Epidemiol 2004;14:17-23. [DOI] [PubMed] [Google Scholar]
- 18.Pedersen CB. The Danish civil registration system. Scand J Public Health 2011;39:22-5. [DOI] [PubMed] [Google Scholar]
- 19.Andersen TF, Madsen M, Jorgensen J, Mellemkjaer L, Olsen JH. The Danish National Hospital Register. A valuable source of data for modern health sciences. Dan Med Bull 1999;46:263-8. [PubMed] [Google Scholar]
- 20.Pedersen CB, Gøtzsche H, Møller JO, Mortensen PB. The Danish Civil Registration System. A cohort of eight million persons. Dan Med Bull 2006;53:441-9. [PubMed] [Google Scholar]
- 21.Charlson ME, Pompei P, Ales Kl, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373-83. [DOI] [PubMed] [Google Scholar]
- 22.Jacobs DR, Kroenke C, Crow R, Deshpande M, Gu DF, Gatewood L, et al. PREDICT: a simple risk score for clinical severity and long-term prognosis after hospitalization for acute myocardial infarction or unstable angina: the Minnesota heart survey. Circulation 1999;100:599-607. [DOI] [PubMed] [Google Scholar]
- 23.Sachdev M, Sun JL, Tsiatis AA, Nelson CL, Mark DB, Jollis JG. The prognostic importance of comorbidity for mortality in patients with stable coronary artery disease. J Am Coll Cardiol 2004;43:576-82. [DOI] [PubMed] [Google Scholar]
- 24.Swift M. A simulation study comparing methods for calculating confidence intervals for directly standardized rates. Comput Stat Data An 2010;54:1103-8. [Google Scholar]
- 25.Rothman KJ, Greenland S, Lash TL. Modern epidemiology. 3rd ed. Lippincott Williams & Wilkins, 2008.
- 26.Madsen M, Davidsen M, Rasmussen S, Abildstrom SZ, Osler M. The validity of the diagnosis of acute myocardial infarction in routine statistics: a comparison of mortality and hospital discharge data with the Danish MONICA registry. J Clin Epidemiol 2003;56:124-30. [DOI] [PubMed] [Google Scholar]
- 27.Thygesen SK, Christiansen CF, Christensen S, Lash TL, Sørensen HT. The predictive value of ICD-10 diagnostic coding used to assess Charlson comorbidity index conditions in the population-based Danish National Registry of Patients. BMC Med Res Methodol 2011;11:83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Madsen MM, Busk M, Søndergaard HM, Bøttcher M, Mortensen LS, Andersen HR, et al. Does diabetes mellitus abolish the beneficial effect of primary coronary angioplasty on long-term risk of reinfarction after acute ST-segment elevation myocardial infarction compared with fibrinolysis? (A DANAMI-2 substudy). Am J Cardiol 2005;96:1469-75. [DOI] [PubMed] [Google Scholar]
- 29.Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011;173:676-82. [DOI] [PubMed] [Google Scholar]
- 30.Chirinos JA, Veerani A, Zambrano JP, Schob A, Perez G, Mendez AJ, et al. Evaluation of comorbidity scores to predict all-cause mortality in patients with established coronary artery disease. Int J Cardiol 2007;117:97-102. [DOI] [PubMed] [Google Scholar]
- 31.Floyd KC, Yarzebski J, Spencer FA, Lessard D, Dalen JE, Alpert JS, et al. A 30-year perspective (1975-2005) into the changing landscape of patients hospitalized with initial acute myocardial infarction: Worcester Heart Attack Study. Circ Cardiovasc Qual Outcomes 2009;2:88-95. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Sytkowski PA, D’Agostino RB, Belanger A, Kannel WB. Sex and time trends in cardiovascular disease incidence and mortality: the Framingham Heart Study, 1950-1989. Am J Epidemiol 1996;143:338-50. [DOI] [PubMed] [Google Scholar]
- 33.Fox CS, Evans JC, Larson MG, Kannel WB, Levy D. Temporal trends in coronary heart disease mortality and sudden cardiac death from 1950 to 1999: the Framingham Heart Study. Circulation 2004;110:522-7. [DOI] [PubMed] [Google Scholar]
- 34.McGovern PG, Jacobs DR, Shahar E, Arnett DK, Folsom AR, Blackburn H, et al. Trends in acute coronary heart disease mortality, morbidity, and medical care from 1985 through 1997: the Minnesota heart survey. Circulation 2001;104:19-24. [DOI] [PubMed] [Google Scholar]
- 35.Myerson M, Coady S, Taylor H, Rosamond WD, Goff DC; ARIC Investigators. Declining severity of myocardial infarction from 1987 to 2002: the Atherosclerosis Risk in Communities (ARIC) Study. Circulation 2009;119:503-14. [DOI] [PubMed] [Google Scholar]
- 36.Yeh RW, Sidney S, Chandra M, Sorel M, Selby JV, Go AS. Population trends in the incidence and outcomes of acute myocardial infarction. N Eng J Med 2010;362:2155-65. [DOI] [PubMed] [Google Scholar]
- 37.Masoudi FA, Foody JM, Havranek EP, Wang Y, Radford MJ, Allman RM, et al. Trends in acute myocardial infarction in 4 US states between 1992 and 2001: clinical characteristics, quality of care, and outcomes. Circulation 2006;114:2806-14. [DOI] [PubMed] [Google Scholar]
- 38.Arciero TJ, Jacobsen SJ, Reeder GS, Frye RL, Weston SA, Killian JM, et al. Temporal trends in the incidence of coronary disease. Am J Med 2004;117:228-33. [DOI] [PubMed] [Google Scholar]
- 39.McManus D, Gore J, Yarzebski J, Spencer F, Lessard D, Goldberg R. Recent trends in the incidence, treatment, and outcomes of patients with STEMI and NSTEMI. Am J Med 2010;124:40-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Movahed MR, John J, Hashemzadeh M, Jamal MM. Trends in the age adjusted mortality from acute ST segment elevation myocardial infarction in the United States (1988-2004) based on race, gender, infarct location and comorbidities. Am J Cardiol 2009;104:1030-4. [DOI] [PubMed] [Google Scholar]
- 41.Roger VL, Weston SA, Gerber Y, Killian JM, Dunlay SM, Jaffe AS, et al. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation 2010;121:863-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Capewell S, Livingston BM, MacIntyre K, Chalmers JW, Boyd J, Finlayson A, et al. Trends in case-fatality in 117,718 patients admitted with acute myocardial infarction in Scotland. Eur Heart J 2000;21:1833-40. [DOI] [PubMed] [Google Scholar]
- 43.Davies AR, Grundy E, Nitsch D, Smeeth L. Constituent country inequalities in myocardial infarction incidence and case fatality in men and women in the United Kingdom, 1996-2005. J Public Health (Oxf) 2011;33:131-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Briffa T, Hickling S, Knuiman M, Hobbs M, Hung J, Sanfilippo F, et al. Long term survival after evidence based treatment of acute myocardial infarction and revascularisation: follow-up of population based Perth MONICA cohort, 1984-2005. BMJ 2009;338:b36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Tunstall-Pedoe H, Kuulasmaa K, Mähönen M, Tolonen H, Ruokokoski E, Amouyel P. Contribution of trends in survival and coronary-event rates to changes in coronary heart disease mortality: 10-year results from 37 WHO MONICA project populations. Monitoring trends and determinants in cardiovascular disease. Lancet 1999;353:1547-57. [DOI] [PubMed] [Google Scholar]
- 46.Alpert JS, Thygesen K, Antman E, Bassand 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;36:959-69. [DOI] [PubMed] [Google Scholar]
- 47.D’Ascenzo F, Gonella A, Quadri G, Longo G, Biondi-Zoccai G, Moretti C, et al. Comparison of mortality rates in women versus men presenting with ST-segment elevation myocardial infarction. Am J Cardiol 2011;107:651-4. [DOI] [PubMed] [Google Scholar]
- 48.Kostis W, Deng Y, Pantazopoulos J, Moreyra A, Kostis J. Trends in mortality of acute myocardial infarction after discharge from the hospital. Circ Cardiovasc Qual Outcomes 2010;3:581-9. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplementary figures A and B
Supplementary tables A–D