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. Author manuscript; available in PMC: 2021 Jul 16.
Published in final edited form as: Circulation. 2020 Jan 6;141(6):454–463. doi: 10.1161/CIRCULATIONAHA.119.043100

Incidence, Trends and Outcomes of Type 2 Myocardial Infarction in a Community Cohort

Claire E Raphael 1, Véronique L Roger 1, Yader Sandoval 1, Mandeep Singh 1, Malcolm Bell 1, Amir Lerman 1, Charanjit S Rihal 1, Bernard J Gersh 1, Bradley Lewis 1, Ryan J Lennon 1, Allan S Jaffe 1, Rajiv Gulati 1
PMCID: PMC8283933  NIHMSID: NIHMS1549566  PMID: 31902228

Abstract

Background:

Type 2 myocardial infarction (T2MI) occurs due to an acute imbalance in myocardial oxygen supply and demand in the absence of athero-thrombosis. Despite being frequently encountered in clinical practice, the population-based incidence and trends remain unknown and the long-term outcomes incompletely characterized.

Methods:

We prospectively recruited residents of Olmsted County, Minnesota who experienced an event associated with a cardiac troponin T (cTnT) >99th percentile of a normal reference population (≥0.01 ng/mL) between 1/1/2003 and 12/31/2012. Events were retrospectively classified into type 1 MI (T1MI, atherothombotic event), T2MI or myocardial injury (troponin rise not meeting criteria for MI) using the universal definition. Outcomes were long term all-cause and cardiovascular mortality and recurrent MI. T2MI was further subclassified by inciting event for supply/demand mismatch.

Results:

A total of 5460 patients had at least one cTnT ≥0.01 ng/mL, of whom 1365 were classified as index T1MI (age 68.5±14.8 years, 63% male) and 1054 T2MI (age 73.7±15.8 years, 46% male). The annual incidence of T1MI decreased markedly from 202 to 84 per 100,000 persons between 2003 and 2012 (p<0.001), while the incidence of T2MI declined from 130 to 78 per 100,000 persons (p=0.02). Compared to T1MI, patients with T2MI had higher long-term all-cause mortality after adjustment for age and sex, driven by early and non-cardiovascular death. Rates of cardiovascular death were similar after either type of MI (HR 0.8, 95% CI 0.7–1.0, p=0.11). Sub-classification of T2MI by etiology demonstrated a more favorable prognosis when the principal provoking mechanism was arrhythmia, compared with post-operative status, hypotension, anemia and hypoxia. After index T2MI, the most common MI during follow-up was a recurrent T2MI while the occurrence of a new T1MI was relatively rare (estimated rates 9.7% and 1.7% at 5 years).

Conclusions:

There has been an evolution in type of MI occurring in the community over a decade, with the incidence of T2MI now being similar to T1MI. Mortality after T2MI is higher and driven by early and non-cardiovascular death. The provoking mechanism of supply/demand mismatch affects long-term survival. These findings underscore the healthcare burden of T2MI and provide benchmarks for clinical trial design.

Keywords: Type 2 MI, supply/demand mismatch, prognosis, incidence, mortality, epidemiology, trends

Introduction

Myocardial infarction (MI) has been sub-classified by etiology since 20071. Type 1 MI (T1MI) is a spontaneous episode occurring due to atherothrombosis, whereas type 2 MI (T2MI) results from an imbalance of myocardial blood supply and oxygen demand in the absence atherosclerotic plaque disruption1{Sandoval, 2014 #2, 2. While the epidemiology of T1MI has been well studied, to our knowledge there have been no community-based studies of T2MI. Prior studies of T2MI have been performed in selected settings (such as emergency departments or tertiary hospitals) or in selected patient cohorts 3–5. Estimates of incidence vary considerably 4, 6, 7 and studies of long-term outcomes have shown conflicting results 8, 9. While many studies have reported a decline in the community based incidence of MI 10–15, the proportion of MIs that are T2MI in these studies is unknown; the separation of T2MI from T1MI might offset or unmask a greater temporal decline in T1MI.

A major challenge in the study of T2MI is that ascertainment of diagnosis cannot be readily operationalized. Accurate classification requires careful scrutiny of individual events by trained experts particularly given the heterogeneity of underlying disease contributors and varying degrees of supply/demand mismatch necessary for myocardial ischemia. In this regard, frequently encountered precipitating mechanisms of T2MI include transient arrhythmias, tachycardia, hyper and hypotension, and anemia. Whether the specific provoking mechanisms correlate with subsequent prognosis is not known. Identification of an association between cause and prognosis might provide a useful tool for risk stratification.

Accordingly, we prospectively collected all events associated with a cardiac troponin T (cTnT) >99th percentile upper-reference limit (URL) in a defined geographic region over a 10-year period. We determined the incidence, temporal trends and prognosis of T1MI and T2MI. Additionally, we investigated whether the underlying precipitant of T2MI is associated with outcomes.

Methods

The data that support the findings of this study are available from the corresponding author upon reasonable request. The study was approved by an institutional review committee and all subjects gave informed consent.

Olmsted County is situated in Minnesota, United States and is well suited to epidemiological research since it is relatively isolated from other urban centers and medical care is delivered by a small number of providers, chiefly the Mayo Clinic and Olmsted Medical Center. The USA census (2010) recorded a total population of 144,248 (49% male) with a median age of 36 years. Twenty four percent were aged less than 18 years-old and 13% over 65 years-old16. Approximately 86% were Caucasian. The population characteristics are similar to the national demographics for Caucasians in the USA, with exceptions of a higher median household income ($66 252 vs $53 054), higher proportion employed in healthcare and lower percentage beneath the poverty line (8 vs 15%)16. Estimated health insurance uninsured rate was 5%16. The Rochester Epidemiology project (REP) is a medical records linkage system that links and archives the medical records of nearly all persons living in the county since 1966 17. This infrastructure allows comprehensive examination of disease incidence and outcomes in a defined population. For the present study, our design enabled prospective collection of all events with cardiac cTnT elevation above the 99th percentile URL (cTnT ≥ 0.01 ng/mL) within Olmsted County over a 10-year period.

Collection of cases

Data were collected between 1st January 2003 and 31st December 2012. Cases were defined as any clinical episode associated with a serum cTnT concentration above the 99th percentile URL (≥0.01ng/mL) in any community, clinic, or hospital location within Olmsted County. cTnT was measured using a sandwich electrochemiluminescence immunoassay (Elecsys 2010, Roche Diagnostic Corp, Indianapolis, Ind). Delta cTnT was defined as the difference (rise or fall) in cTnT concentrations between two measurements less than 1 week apart.

Definition of comorbidities

Clinical characteristics and patient demographics were collected by from medical records. ICD-9 codes at baseline were used to define co-morbidities. Cases with prior MI were excluded from analysis.

Classification of cause of cTnT elevation

Cause (s) were retrospectively classified by two cardiologists (CER and RG) following detailed review of each clinical record and impressions of the responsible cardiologists and internists, 12-lead electrocardiogram (ECG), and where applicable, echocardiography, coronary angiography, computerized tomography (CT) and/or magnetic resonance imaging. Any difference was resolved through consensus. Following recommendations from the Task Force for the 4th Universal Definition of MI (UDMI)1, MI was manually ascertained if there was a rise and/or fall in cTnT with at least one concentration >99th percentile URL associated with at least one of the following (a) ischemic symptoms (b) new/presumed new ECG changes or (c) new imaging evidence of ischemia e.g. regional wall motion abnormalities or (d) identification of intracoronary thrombus on angiogram or autopsy1.

T1MI was defined as MI presumed to result from a spontaneous primary atherosclerotic coronary event, T2MI as MI secondary to a decrease in myocardial oxygen supply or increase in myocardial oxygen demand not due to acute athero-thrombosis. Use of the terms demand ischemia or supply/demand mismatch by physicians in their clinical impressions were classified as a T2MI, unless subsequent imaging or clinical course suggested an alternate diagnosis. Descriptions in keeping with demand ischemia, for example “troponin rise due to acute GI bleed with drop in hemoglobin” were similarly classified as T2MI. Strict cut-points for supply/demand variables, such as hypotension or hemoglobin, were not used as the level at which these lead to demand ischemia will be patient specific 18. Type 4–5 MI (procedure-related MI) were classified according to the 4th UDMI 1. Cases in which cTnT increases occurred in the absence of clinical evidence of acute myocardial ischemia, in whom the definition of MI was not met were classified as myocardial injury1. These included many heart failure exacerbations, post defibrillator therapy, myo- and peri-carditis, and primary non-cardiac pathologies such as sepsis, critical illness, and renal failure.

This was a per-patient analysis. For subjects with multiple qualifying MIs, only the first event was used for analysis. Subsequent events were defined as recurrent MI. For the purposes of this study, recurrent MI was defined as any MI that occurred subsequent to the incident MI. This represents a combination of the World Health Organization definitions of re-infarction (≤28 days) and recurrent MI (>28 days) 19.

Sub-classification of T2MI by etiology

The inciting stimuli for supply-demand mismatch were categorized as follows and recorded as primary or contributory: arrhythmia (tachy - or brady-), hypotension, anemia, post-surgical status (in the absence of other causes e.g. T1MI, arrhythmia), hypoxia, and other (including spontaneous coronary artery dissection, coronary embolism, coronary spasm, structural heart disease e.g. severe aortic stenosis and malignant hypertension).

Collection of outcome data

All death certificates, autopsy reports, obituary reports and electronic death certificate files from the State of Minnesota Department of Vital and Health Statistics were prospectively collected. Cause of death was determined following review of full medical records by the coroner and autopsy data where available. It was divided into cardiovascular and non-cardiovascular causes using the American Heart Association categories for cardiovascular deaths20 (ICD codes I00-I99).

Statistical analysis

Continuous variables were presented as mean (standard deviation) and median (interquartile range), and categorical variables as frequency (percentage). Comparisons between groups were tested using one-way ANOVA analysis for continuous and Pearson’s χ2 test for categorical data. Agreement between operators was assessed using Cohen’s Kappa coefficient. Age adjusted incidence rates were calculated using Poisson regression separately for T1 MI and T2MI. Mann-Kendall tests for monotonic trend were used to test temporal trends. Confidence intervals of incidence were calculated with the Wilson score interval. Cumulative incidence curves were created for all-cause mortality, cardiovascular mortality, and first recurrent MI. For first recurrent MI, T1MI and T2MI were analyzed separately. Adjustments for age and gender were made to the curves using inverse probability weighting (IPW) where logistic regression was used to estimate the odds of being in the T1MI or T2MI group given age and gender. The inverse probabilities were calculated for each patient being in their respective group from the logistic model and used as weights to calculate the expected survival for each subpopulation. When analyzing cardiovascular death, non-cardiovascular death was treated as a competing risk. Similarly, for recurrent MI, all-cause mortality and the alternate MI type were considered as competing risks. Generation of cumulative incidence curves in the presence of these competing risks was performed using the Fine and Gray model. Kaplan Meier curves were created comparing all-cause mortality between T2MI subtypes and multiple vs single inciting events. The log-rank test was used to make comparisons between curves. Because of known challenges in discriminating T2MI and myocardial injury we performed multiple sensitivity analyses by incorporating subgroups of myocardial injury into the T2MI cohort.

A multivariable Cox proportional hazards models with adjustments for age, gender, and comorbidities was utilized to assess the effect of MI type on long-term all-cause and cardiovascular mortality. A Cox proportional hazard model was also used to assess how the hazard of all-cause mortality, cardiovascular mortality, and non-cardiovascular mortality vary across troponin levels. Troponin was fit using a penalized cubic spline with 10 knots spaced evenly across the range of troponin. All Cox model’s proportional hazards assumption were assessed using plots of the scaled Schoenfeld residuals against time. Statistical significance was defined as a 2-tailed P value of less than 0.05. Statistical analyses were performed using R (version 3.4.2).

Results

An overview of the study population and classification of cTnT-positive events is illustrated in Figure 1. Of patients meeting the definition of MI, 1365 (56%) were adjudicated as T1MI and 1054 (43%) as T2MI. These patient groups were used for further analysis. The inter-operator agreement for adjudication of type of MI was excellent (Cohen’s kappa = 0.89 (95% CI: 0.86–0.92)).

Figure 1.

Figure 1.

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Study outline and event classification. URL – upper reference limit. UDMI – Universal Definition of MI.

Patients with T2MI were older and were more likely to be female, with a higher prevalence of COPD and CKD (Table 1). Patients with T1MI were more likely to have traditional cardiovascular risk factors, including diabetes, smoking and previous revascularization. Peak and delta cTnT were lower in T2MI. Patients with a T1MI were more likely to be prescribed aspirin, ACE inhibitors, beta blockers and lipid lowering therapies on discharge than patients with T2MI (Supplementary Table 1).

Table 1:

Baseline demographics.

  T1MI (N=1365) T2MI (N=1054) p value
Age (years) 68.5 ±14.8 73.7±15.8 <0.001
Sex (%male) 861(63) 486 (46) <0.001
Max cTnT, median (Q1, Q3), ng/ml 0.33 (0.09, 1.50) 0.11 (0.05, 0.27) <0.001
Delta cTnT, median (Q1, Q3), ng/ml 0.20 (0.04, 1.05) 0.06 (0.03, 0.17) <0.001
Hemoglobin, g/dl 13.4±1.9 11.9±2.4 <0.001
Creatinine clearance, ml/min 61.7±24.0 51.3±28.5 <0.001
Previous CABG/PCI (n, %) 125 (10) 18 (5) <0.001
Hypertension (n, %) 966 (71) 716 (68) 0.12
Diabetes Mellitus (n, %) 313 (23) 150 (14) <0.001
Hypercholesterolemia (n, %) 790 (58) 359 (34) <0.001
Smoking history (n, %) 907 (50) 462 (43) <0.001 
Stroke (n, %) 47 (3) 21 (2) 0.032
Liver disease (n, %) 29 (2) 39 (4) 0.02
Heart Failure (n, %) 26 (2) 86 (8) <0.001
COPD (n, %) 159 (12) 163 (16) 0.006
History of cancer (n, %) 225 (17) 229 (22) 0.001
Sepsis within 1 week of event (n, %) 29 (2) 138 (13) <0.001
Peptic ulcer disease (n, %) 42 (3) 52 (5) 0.019
Presenting ECG      
STEMI (n, %) 198 (15) 23 (2) <0.001
NSTEMI (n, %) 1165 (85) 1031 (98) <0.001
Angiographic study performed☨  1200 (88) 402 (38) <0.001
 ≥ 70%stenosis 1022 (85) 138 (34) <0.001
 ≥ 50%stenosis 1058 (88) 162 (40) <0.001
 Intra coronary thrombus 191 (16) 1 (0.2)* <0.001
 PCI/CABG during admission 791 (58) 77 (7) <0.001
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☨

angiographic findings are presented as a percentage of the patients undergoing angiography.

*

coronary embolism

Figure 2 illustrates a marked reduction in the incidence of T1MI over the 10-year period (p<0.001 for trend) with a modest reduction in incidence of T2MI (p=0.012 for trend). The differential rates of decline have resulted in a similar contemporary community-based incidence of T2MI to T1MI, with an age adjusted annual incidence of ~60/100,000.

Figure 2. Temporal trends in T1MI and T2MI.

Figure 2.

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The annual incidence of T1MI decreased markedly between 2003 and 2012, with a more modest decline in T2MI such that the incidence of T2MI is similar to that of T1MI in contemporary years.

Long-term all-cause and cause-specific mortality

During a median follow up of 5.5 (IQR 3.1, 7.9) years there were 638 (47%) deaths in the T1MI and 766 (73%) in the T2MI group. Age and sex adjusted rates of all-cause mortality were significantly higher after T2MI vs. T1MI (52% vs 31% at 5 years, Figure 3A; unadjusted rates Supplementary Figure 1), whereas rates of cardiovascular mortality were similar after either MI type (~20% at 5 years, Figure 3B). Mortality after T2MI was highest in the first 3 months after the index episode and thereafter continued to accrue at a greater rate than T1MI.

Figure 3. A and B. Mortality after T2MI and T1MI.

Figure 3.

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Adjusted rates of long-term all-cause adjusted mortality were markedly higher following T2MI compared to T1MI whereas rates of cardiovascular mortality were similar after either MI type. Mortality risk was highest early after the index event. C and D. Recurrent MI after T2MI and T1MI. Following index T2MI, the most common recurrent MI was another T2MI event, with notably low rates of T1MI occurring during long-term follow-up. The reverse pattern was seen following index T1MI

Given challenges in discriminating T2MI from myocardial injury in certain cases, multiple sensitivity analyses were performed, incorporating different subgroups of myocardial injury into the T2MI group (Supplementary Figure 2).

Predictors of mortality

On univariable analysis, patients with T2MI had a significantly higher risk of all-cause mortality (HR 2.3 (95% CI 2.0–2.5) p<0.001) compared to T1MI. Cardiovascular mortality was similar between the two groups (HR 1.1 (95% CI 0.9–1.3), p=0.20). After adjustment for age, sex and baseline co-morbidities, T2MI remained an independent predictor of all-cause (HR 1.4, 95% CI 1.2–1.6, p<0.001) but not cardiovascular mortality. On multivariable analysis (Supplementary Table 2), all-cause mortality was lower in hypertensive patients but higher in patients with diabetes, renal failure and heart failure. Cardiovascular mortality in T2MI was higher in older patients, those with prior stroke and chronic kidney disease. Peak cTnT level during index T2MI was associated with risk of mortality at 1 year (Figure 4).

Figure 4. Troponin and mortality risk.

Figure 4.

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Peak cTNT was a strong predictor of one year all-cause (A), cardiovascular (B) and non cardiovascular (C) death in the T2MI population. CI – confidence interval

Recurrent MI

Following index T2MI, a recurrent MI was more likely to be another T2MI event than a new T1MI (~10% recurrent T2MI, 1.7% T1MI at 5 years, Figure 3C and D). Conversely, index T1MI was more likely to be followed by a recurrent T1MI than a new T2MI.

Prognosis of T2MI stratified by inciting event.

Figure 5A demonstrates that T2MI with principal classified precipitants of arrhythmia or post-surgical status exhibited a relatively more favorable prognosis compared to T2MI precipitated by hypoxia, hypotension or anemia. These differences persisted following adjustment for age and sex. Patients with multiple provoking factors experienced significantly worse survival after T2MI compared to those in whom a single contributor was present (HR 1.39, 95% CI 1.19–1.61, p<0.001, Figure 5B).

Figure 5: A: Subclassification of T2MI and all-cause mortality.

Figure 5:

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Risk of long-term mortality was associated with the principal inciting cause of T2MI. Arrhythmic and post-operative precipitants conferred more favorable prognoses than anemia, hypotension and hypoxic insults. Rarer inciting causes of T2MI (n=49) were not included in panel A due to low number of patients in each category: structural heart disease (14), malignant hypertension (4), coronary embolism (8), spontaneous coronary artery dissection (19), coronary vasospasm (4).B: Patients with a single inciting cause of T2MI had a more favorable prognosis than those with multiple causes

Discussion

The major findings of this, the first community-based study of T2MI, include 1. The incidence of T2MI is similar to that of T1MI in contemporary years due to a greater temporal decline in T1MI than T2MI occurring over a decade. 2. Long-term mortality after T2MI is higher than after T1MI, driven by early and non-cardiovascular death. Risk of cardiovascular death is similar after either type of MI. 3. Recurrent MI after T2MI is principally due to another T2MI event. 4. Long-term mortality after T2MI is strongly associated with the provoking factor for supply/demand mismatch.

Incidence and temporal trends of T2MI and T1MI

The study design enabled accurate categorization of type of MI according to etiology through use of a sensitive marker of myocyte injury as an entry criterion and expert scrutiny of each clinical event. Prior epidemiologic studies that employed standard operational definitions for STEMI and NSTEMI as entry criteria were unlikely to have captured T2MI and would have included MI due to non atherosclerotic processes10–14, 21. We therefore relied on clinical criteria for MI sub-classification. Classification of events according to etiology of ischemia in the present study demonstrates that the temporal decline in MI incidence primarily reflects a reduction in T1MI –. that is episodes of acute coronary athero-thrombosis. The incidence of T2MI has also declined over the period of study, perhaps unexpectedly. Changes in selection of patients for cTnT testing over the period of study are unlikely to explain the temporal decline, since symptoms or clinical evidence of ischemia were required to satisfy UDMI criteria and such patients would typically have had a cTnT measurement. Whether improved lifestyle measures and increased use of primary preventative medications, factors which have contributed to the decline in T1MI 22, also underlie the modest temporal decline in T2MI through mechanisms such as reduced atherosclerotic burden 23 or improved myocardial tolerance of supply-demand mismatch remains uncertain.

The effect of transitioning from contemporary to high sensitivity cardiac troponin (hs-cTN) assays on the unselected community based incidence of T2MI will be an important area for future study. To date, studies in selected cohorts have yielded conflicting results. The High-STEACS study, a large stepped-wedge, cluster randomized trial in Scotland that evaluated the implementation of a hs-cTnI assay demonstrated a greater relative incidence of T2MI compared with T1MI, and showed that most reclassified patients were women with either T2MI or myocardial injury 24. However, other studies indicate an increase in MI driven by more T1MIs 25. The finding that T2MI is now encountered as frequently as T1MI in contemporary clinical practice highlights the current burden of T2MI related healthcare utilization as well as need for re-evaluation following wider implementation of hs-cTN assays.

Mortality and recurrent MI after T2MI

The early and non-cardiovascular nature of death after index T2MI is consistent with studies in non-community cohorts 26–28 and supports a relation to the primary illness. The finding that adjusted rates of cardiovascular mortality after T2MI were as high as that of T1MI, while utilization of standard prognostic therapies after T2MI were lower might suggest an important therapeutic opportunity for post T2MI care. The high risk of recurrent episodes of T2MI in survivors of the index event may reflect abnormalities in coronary flow reserve or microvascular function underpinning an intolerance of increase in myocardial demand. These recurrent episodes may in turn lead to heart failure death 29, 30. The higher prevalence of women in our and other T2MI cohorts 6, 23 and high prevalence of risk factors for microvascular disease 31 support this hypothesis, however it remains speculative. A more detailed understanding of mechanisms of MI and subtypes of cardiovascular death is important to guide efforts toward mortality risk reduction.

Implications for management and future trial design

Management strategies that are effective in T1MI may not be of benefit in T2MI and evidence base for these therapies following T2MI is largely lacking. Secondary prevention therapies such as blood pressure lowing and smoking cessation are likely to be beneficial in microvascular dysfunction, however antiplatelet therapies may be less effective. While the use of medications for the specific treatment of T2MI remains to be studied, the ODYSSEY OUTCOMES trial did demonstrate benefit of lipid lowering on the occurrence of future T2MI after an index acute coronary syndrome (ACS). The majority of the enrolled ACS population was T1MI. In a pre-specified analysis of the randomized trial, Alirocumab treatment after ACS reduced the overall incidence of subsequent MI compared with placebo, driven by reductions in both T1MI and T2MI 32. In the current study, utilization of antiplatelet medications, HMG Co-A reductase inhibitors and ACE inhibitors was markedly lower after T2MI than T1MI, consistent with findings reported in other T2MI cohorts26, 27. Notably, a diagnosis of hypertension was found to be associated with lower all-cause mortality after T2MI. Whether this reflects co-utilization of prognostic medications, a direct mechanistic relationship or type 1 error is uncertain. The observation does however highlight unanswered questions regarding the impact of cardiovascular medications on survival after T2MI.

Trials in progress, including ACT-2 (appropriateness of coronary investigation in myocardial injury and T2MI) will assess whether early coronary angiography will lead to reduced cardiovascular mortality following T2MI 33. Detection and treatment of significant epicardial CAD may raise the threshold at which ischemia occurs and could reduce the rate of recurrent T2MI as well as the rates of cardiovascular death. Pending an evidence base from future trials, we would recommend that patients with T2MI are assessed by a cardiologist to assess for modifiable cardiovascular risk factors.

Underlying cause of supply/demand mismatch affects prognosis

Another novel aspect of this study is the demonstration that T2MI outcomes can be stratified according to inciting mechanism of supply/demand mismatch. Provoking factors that may be transient and reversible, such as peri-operative insult or arrhythmia were associated with more favorable outcomes, while factors such as hypoxia likely characterize a sicker population at baseline, with a greater risk of adverse outcome. Although previous smaller series have attempted to sub-classify T2MI by underlying cause, these were underpowered to detect differences in mortality between groups 26. These findings underscore that T2MI is not a single entity, rather a group of phenotypic clusters 3, 5, 34based on underlying mechanisms of mismatch. The current study is therefore an important step forward in T2MI, providing event rates for trial design and indicating that treatment strategies should take into account outcomes according to sub-classification.

Strengths and Limitations

The findings may not be generalizable to populations of a different racial and ethnic background; however previous studies suggest that cardiovascular trends in the region parallel those nationally35. We relied on clinical criteria to classify MIs. Thus, our incidence rates are not directly comparable to the incidence rates previously reported using standardized epidemiological criteria in the same community. Not all patients had angiography, and it is possible some of T2MIs were unrecognized T1MIs. Patients with critical illness state or sepsis may have had an undetected acute T1MI or T2MI. While it is possible that the awareness of T2MI as an entity increased over the study period, if this was significant, an increasing incidence would be expected and the converse was seen.

The study period was before the transition to use of 5th generation (high sensitivity) troponin assays. The impact of newer assays on incidence of T1MI and T2MI requires further study. Peak-recorded cTnT may not have been taken at the same time point following onset of symptoms in all patients and patients who were sicker may have been more closely surveilled. The delta cTnT was derived from the peak recorded cTnT and the prior/subsequent cTnT, with the same potential biases. Co-morbidities were recorded and adjusted for as dichotomous variables and may have been more severe in the T2MI compared to the T1MI population.

Despite these limitations, this remains the only community-based study with rigorous ascertainment of diagnosis, requiring evidence of ischemia in T2MI, comprehensive follow-up, manual classification of the inciting event, and adjudication of the events by 2 independent operators.

Conclusions

This study demonstrates temporal changes in type of MI occurring in the community over a decade. The incidence of T2MI is now similar to that of T1MI. Mortality after T2MI is higher and is driven by early and non-cardiovascular death. The provoking mechanism of supply/demand mismatch in T2MI affects long-term survival.

Supplementary Material

Supplemental Publication Material

What is new?

  • Using 14th generation cardiac troponin T elevation as an entry criterion, this study showed an evolution in type of MI occurring in the community over a decade, with the incidence of T2MI now being similar to T1MI

  • Adjusted long-term mortality following T2 MI is markedly higher than after T1MI, driven by early and non-cardiovascular death.

  • Mortality after T2MI is associated with the provoking factor for supply/demand mismatch.

What are the clinical implications?

  • The clinical burden of T2MI and associated rates of mortality as well as recurrent T2MI underscore the need for evidence based management strategies

  • The precipitating mechanism of supply demand mismatch is a novel factor for mortality risk stratification in T2MI

Acknowledgments

Funding Sources

Part funded using the resources of the Rochester Epidemiology Project, which is supported by the National Institute on Aging of the NIH under Award Number R01AG034676. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH

Conflict of Interest Disclosures

Dr. Jaffe has or presently consults for most of the major diagnostic companies and for companies who need help in interpreting biomarker data. Dr. Sandoval has served on an advisory board/speaker for Abbott Diagnostics, and an advisory board for Roche Diagnostics; all without personal financial compensation.

Non-standard Abbreviations and Acronyms

cTnT

cardiac troponin T

T1MI

Type 1 myocardial infarction

T2MI

Type 2 myocardial infarction

UDMI

Universal Definition

URL

Upper reference limit

References

  • 1.Thygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DAWhite HD. Fourth Universal Definition of Myocardial Infarction (2018). Circulation. 2018;138:e618–e651. [DOI] [PubMed] [Google Scholar]
  • 2.McCarthy CP, Vaduganathan MJanuzzi JL Jr., Type 2 Myocardial Infarction-Diagnosis, Prognosis, and Treatment. Jama. 2018;320:433–434. [DOI] [PubMed] [Google Scholar]
  • 3.Gaggin HK, Liu Y, Lyass A, van Kimmenade RR, Motiwala SR, Kelly NP, Mallick A, Gandhi PU, Ibrahim NE, Simon ML, et al. Incident Type 2 Myocardial Infarction in a Cohort of Patients Undergoing Coronary or Peripheral Arterial Angiography. Circulation. 2017;135:116–127. [DOI] [PubMed] [Google Scholar]
  • 4.Morrow DA, Wiviott SD, White HD, Nicolau JC, Bramucci E, Murphy SA, Bonaca MP, Ruff CT, Scirica BM, McCabe CH, et al. Effect of the novel thienopyridine prasugrel compared with clopidogrel on spontaneous and procedural myocardial infarction in the Trial to Assess Improvement in Therapeutic Outcomes by Optimizing Platelet Inhibition with Prasugrel-Thrombolysis in Myocardial Infarction 38: an application of the classification system from the universal definition of myocardial infarction. Circulation. 2009;119:2758–64. [DOI] [PubMed] [Google Scholar]
  • 5.Sandoval Y Jaffe AS. Type 2 Myocardial Infarction: JACC Review Topic of the Week. J Am Coll Cardiol. 2019;73:1846–1860. [DOI] [PubMed] [Google Scholar]
  • 6.Saaby L, Poulsen TS, Hosbond S, Larsen TB, Pyndt Diederichsen AC, Hallas J, Thygesen KMickley H. Classification of myocardial infarction: frequency and features of type 2 myocardial infarction. Am J Med. 2013;126:789–97. [DOI] [PubMed] [Google Scholar]
  • 7.Javed U, Aftab W, Ambrose JA, Wessel RJ, Mouanoutoua M, Huang G, Barua RS, Weilert M, Sy FThatai D. Frequency of elevated troponin I and diagnosis of acute myocardial infarction. Am J Cardiol. 2009;104:9–13. [DOI] [PubMed] [Google Scholar]
  • 8.Nestelberger T, Boeddinghaus J, Badertscher P, Twerenbold R, Wildi K, Breitenbucher D, Sabti Z, Puelacher C, Rubini Gimenez M, Kozhuharov N, et al. Effect of Definition on Incidence and Prognosis of Type 2 Myocardial Infarction. J Am Coll Cardiol. 2017;70:1558–1568. [DOI] [PubMed] [Google Scholar]
  • 9.Neumann JT, Sorensen NA, Rubsamen N, Ojeda F, Renne T, Qaderi V, Teltrop E, Kramer S, Quantius L, Zeller T, et al. Discrimination of patients with type 2 myocardial infarction. Eur Heart J. 2017;38:3514–3520. [DOI] [PubMed] [Google Scholar]
  • 10.Floyd KC, Yarzebski J, Spencer FA, Lessard D, Dalen JE, Alpert JS, Gore JMGoldberg RJ. 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]
  • 11.Yeh RW, Sidney S, Chandra M, Sorel M, Selby JVGo AS. Population trends in the incidence and outcomes of acute myocardial infarction. N Engl J Med. 2010;362:2155–65. [DOI] [PubMed] [Google Scholar]
  • 12.Smolina K, Wright FL, Rayner MGoldacre MJ. Determinants of the decline in mortality from acute myocardial infarction in England between 2002 and 2010: linked national database study. Bmj. 2012;344:d8059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Ko DT, Newman AM, Alter DA, Austin PC, Chiu M, Cox JL, Goodman SGTu JV. Secular trends in acute coronary syndrome hospitalization from 1994 to 2005. Can J Cardiol. 2010;26:129–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Roger VL, Weston SA, Gerber Y, Killian JM, Dunlay SM, Jaffe AS, Bell MR, Kors J, Yawn BPJacobsen SJ. Trends in incidence, severity, and outcome of hospitalized myocardial infarction. Circulation. 2010;121:863–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Roger VL, Jacobsen SJ, Weston SA, Goraya TY, Killian J, Reeder GS, Kottke TE, Yawn BPFrye RL. Trends in the incidence and survival of patients with hospitalized myocardial infarction, Olmsted County, Minnesota, 1979 to 1994. Ann Intern Med. 2002;136:341–8. [DOI] [PubMed] [Google Scholar]
  • 16.U.S_Census_Bureau. 2010 US Census Statistics for Olmsted County. <https://factfinder.census.gov/faces/tableservices/>. updated 6.12.2019. Accessed 9/15/2019. Last.
  • 17.Melton LJ 3rd., History of the Rochester Epidemiology Project. Mayo Clin Proc. 1996;71:266–74. [DOI] [PubMed] [Google Scholar]
  • 18.Sandoval Y, Smith SW, Thordsen SEApple FS. Supply/demand type 2 myocardial infarction: should we be paying more attention? J Am Coll Cardiol. 2014;63:2079–2087. [DOI] [PubMed] [Google Scholar]
  • 19.Mendis S, Thygesen K, Kuulasmaa K, Giampaoli S, Mahonen M, Ngu Blackett KLisheng L. World Health Organization definition of myocardial infarction: 2008–09 revision. Int J Epidemiol. 2011;40:139–46. [DOI] [PubMed] [Google Scholar]
  • 20.Go AS, Mozaffarian D, Roger VL, Benjamin EJ, Berry JD, Blaha MJ, Dai S, Ford ES, Fox CS, Franco S, et al. Executive summary: heart disease and stroke statistics−−2014 update: a report from the American Heart Association. Circulation. 2014;129:399–410. [DOI] [PubMed] [Google Scholar]
  • 21.Manemann SM, Gerber Y, Chamberlain AM, Dunlay SM, Bell MR, Jaffe AS, Weston SA, Killian JM, Kors JRoger VL. Acute coronary syndromes in the community. Mayo Clin Proc. 2015;90:597–605. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Shah NS, Huffman MD, Ning HLloyd-Jones DM. Trends in myocardial infarction secondary prevention: The National Health and Nutrition Examination Surveys (NHANES), 1999–2012. J Am Heart Assoc. 2015;4:e001709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Webber BJ, Seguin PG, Burnett DG, Clark LLOtto JL. Prevalence of and risk factors for autopsy-determined atherosclerosis among US service members, 2001–2011. Jama. 2012;308:2577–83. [DOI] [PubMed] [Google Scholar]
  • 24.Shah ASV, Anand A, Strachan FE, Ferry AV, Lee KK, Chapman AR, Sandeman D, Stables CL, Adamson PD, Andrews JPM, et al. High-sensitivity troponin in the evaluation of patients with suspected acute coronary syndrome: a stepped-wedge, cluster-randomised controlled trial. Lancet. 2018;392:919–928. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Reichlin T, Twerenbold R, Reiter M, Steuer S, Bassetti S, Balmelli C, Winkler K, Kurz S, Stelzig C, Freese M, et al. Introduction of high-sensitivity troponin assays: impact on myocardial infarction incidence and prognosis. Am J Med. 2012;125:1205–1213.e1. [DOI] [PubMed] [Google Scholar]
  • 26.Saaby L, Poulsen TS, Diederichsen AC, Hosbond S, Larsen TB, Schmidt H, Gerke O, Hallas J, Thygesen KMickley H. Mortality rate in type 2 myocardial infarction: observations from an unselected hospital cohort. Am J Med. 2014;127:295–302. [DOI] [PubMed] [Google Scholar]
  • 27.Chapman AR, Shah ASV, Lee KK, Anand A, Francis O, Adamson P, McAllister DA, Strachan FE, Newby DEMills NL. Long-Term Outcomes in Patients With Type 2 Myocardial Infarction and Myocardial Injury. Circulation. 2018;137:1236–1245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Sandoval Y, Smith SW, Sexter A, Thordsen SE, Bruen CA, Carlson MD, Dodd KW, Driver BE, Hu Y, Jacoby K, et al. Type 1 and 2 Myocardial Infarction and Myocardial Injury: Clinical Transition to High-Sensitivity Cardiac Troponin I. Am J Med. 2017;130:1431–1439.e4. [DOI] [PubMed] [Google Scholar]
  • 29.Taqueti VR, Everett BM, Murthy VL, Gaber M, Foster CR, Hainer J, Blankstein R, Dorbala SDi Carli MF. Interaction of impaired coronary flow reserve and cardiomyocyte injury on adverse cardiovascular outcomes in patients without overt coronary artery disease. Circulation. 2015;131:528–35. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Taqueti VR, Solomon SD, Shah AM, Desai AS, Groarke JD, Osborne MT, Hainer J, Bibbo CF, Dorbala S, Blankstein R, et al. Coronary microvascular dysfunction and future risk of heart failure with preserved ejection fraction. Eur Heart J. 2018;39:840–849. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Herrmann J, Kaski JCLerman A. Coronary microvascular dysfunction in the clinical setting: from mystery to reality. Eur Heart J. 2012;33:2771–2782b. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.White HD, Steg PG, Szarek M, Bhatt DL, Bittner VA, Diaz R, Edelberg JM, Erglis A, Goodman SG, Hanotin C, et al. Effects of alirocumab on types of myocardial infarction: insights from the ODYSSEY OUTCOMES trial. Eur Heart J. 2019;40:2801–2809. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Lambrakis K, French JK, Scott IA, Briffa T, Brieger D, Farkouh ME, White H, Chuang AM, Tiver K, Quinn S, et al. The appropriateness of coronary investigation in myocardial injury and type 2 myocardial infarction (ACT-2): A randomized trial design. Am Heart J. 2019;208:11–20. [DOI] [PubMed] [Google Scholar]
  • 34.Januzzi JL Sandoval Y The Many Faces of Type 2 Myocardial Infarction. J Am Coll Cardiol. 2017;70:1569–1572. [DOI] [PubMed] [Google Scholar]
  • 35.Jabre P, Jouven X, Adnet F, Thabut G, Bielinski SJ, Weston SARoger VL. Atrial fibrillation and death after myocardial infarction: a community study. Circulation. 2011;123:2094–100. [DOI] [PMC free article] [PubMed] [Google Scholar]

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