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Prediabetes and the association with unrecognized myocardial infarction in the multi-ethnic study of atherosclerosis
Prediabetes and the Association with Unrecognized Myocardial Infarction in the Multi-Ethnic Study of Atherosclerosis Richard Brandon Stacey MD, MS, Paul E. Leaverton PhD, Douglas D. Schocken MD, Jennifer A. Peregoy MPH, Alain G. Bertoni MD, MPH PII: DOI: Reference:
S0002-8703(15)00513-X doi: 10.1016/j.ahj.2015.08.003 YMHJ 4978
To appear in:
American Heart Journal
Received date: Accepted date:
15 June 2015 5 August 2015
Please cite this article as: Stacey Richard Brandon, Leaverton Paul E., Schocken Douglas D., Peregoy Jennifer A., Bertoni Alain G., Prediabetes and the Association with Unrecognized Myocardial Infarction in the Multi-Ethnic Study of Atherosclerosis, American Heart Journal (2015), doi: 10.1016/j.ahj.2015.08.003
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Prediabetes and the Association with Unrecognized Myocardial Infarction in the Multi-Ethnic Study of Atherosclerosis
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R. Brandon Stacey, MD, MS1; Paul E. Leaverton, PhD3; Douglas D. Schocken, MD4; Jennifer A. Peregoy, MPH3; Alain G. Bertoni, MD, MPH2
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Running Title: Prediabetes and UMI
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From the Departments of Internal Medicine Section on Cardiology,1 Public Health Sciences2 at the Wake Forest University School of Medicine, Winston-Salem, North Carolina, 27157, USA; Department of Epidemiology and Biostatistics3, College of Public Health, University of South Florida, Tampa, Florida, USA; Division of Cardiology4, Department of Medicine, Duke University Medical Center, Durham, North Carolina
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Author Contributions: R.S. researched data/wrote manuscript; P.L researched data and contributed to discussion; D.D. contributed to discussion; J.P. wrote and edited manuscript; A.B. reviewed/edited manuscript.
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Research supported in part by NIH R01HL076438.
Address for Correspondence:
R. Brandon Stacey, MD, MS Cardiology Section Watlington Hall Wake Forest University School of Medicine Medical Center Boulevard Winston-Salem, North Carolina 27157-1045 Phone: (336) 716-2524 Fax: (336) 713-9188 E-mail: [email protected]
Financial Disclosures: None Conflicts of Interest: None Total Word Count: 4,056 Abstract Word Count: 254
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ACCEPTED MANUSCRIPT Abstract Background: With one-quarter of initial myocardial infarctions (MI) being unrecognized MI (UMI), recognition is critical to minimize further cardiovascular risk. Diabetes mellitus (DM) is an established
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risk factor for UMI. If impaired fasting glucose (IFG) also increased the risk for UMI, it would represent
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a significant public health challenge due to the rapid worldwide increase in IFG prevalence. We compared participants with IFG to those with normal fasting glucose (NFG) to determine if IFG was
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associated with UMIs.
Methods: We performed cross-sectional analyses from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort study. There were 6,814 participants recruited during July 2000 to
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September 2002 from the general community at 6 field sites. After excluding those with diabetes mellitus or missing variables, 5,885 participants were included. At baseline, there were 4,955 participants with
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NFG and 930 participants with IFG. The main outcome was an UMI defined by the presence of pathological Q waves or minor Q waves with ST-T abnormalities on initial 12-lead electrocardiogram (ECG). Logistic regression was used to generate crude odds ratios and adjust for covariates.
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Results: There was a higher prevalence of UMI in those with IFG compared with those with NFG [3.5% (n=72) vs 1.4% (n=30)]. After adjustment for multiple risk factors, there was a higher odds of an UMI
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among those with IFG compared with those with NFG [OR: 1.60 (95% CI: 1.0-2.5); p = 0.048]. Conclusions: Impaired fasting glucose is associated with unrecognized myocardial infarctions in a multi-
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ethnic population free of baseline cardiovascular disease.
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Keywords: Impaired fasting glucose, myocardial infarction, ECG
Word count: 250
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ACCEPTED MANUSCRIPT Background Unrecognized myocardial infarctions (UMIs) are subclinical myocardial infarctions that by definition go unrecognized by both patient and physician, and may be either symptomatic or
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asymptomatic (i.e., “silent”). UMI is a prevalent condition with an estimated 25 percent of first
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myocardial infarctions being unrecognized.1 UMIs are predictive of later symptomatic infarctions and for other subsequent major cardiovascular events, including coronary death.2-4 A precise prevalence for UMIs in the United States is difficult to obtain; however, a recent study found the prevalence of silent
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MIs to be as high as 17%, which is higher than reported by previous studies.3
Unfortunately, there is a dearth of information about risk factors that may predispose one to an
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UMI as opposed to a clinically recognized myocardial infarction (MI).5 One of the most cited of the known MI risk factors is the presence of diabetes mellitus (DM).6, 7 In particular, it has been shown that
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the greater the duration of DM, the greater the risk of MI.8 Because of this observation, some have investigated whether or not persons in a prediabetic condition may also be at greater risk for cardiovascular disease (CVD), including MIs, as compared to those with normal glucose values.9-12 The
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results have been inconclusive and this possibility remains under-investigated. The prevalence of prediabetes in the United States has increased substantially in recent decades to over a third of the adult population, with the proportion of U.S. women and adolescent girls with
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prediabetes growing at a significantly higher rate than males.13, 14 Many will eventually progress to overt DM, and for those, the risks for UMI are well described. However, for those with impaired fasting
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glucose (IFG), an indicator of prediabetes, the risk for UMI is less certain. If IFG were associated with even a modest increase in risk of UMI, the public health ramifications would be substantial. To better
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assess whether such an association exists, we turned to the Multi-Ethnic Study of Atherosclerosis to examine this question quantitatively.
Methods The Multi-Ethnic Study of Atherosclerosis (MESA) Population - Study Participants The recruitment criteria for participants in MESA have been published previously.15 The MESA study is a population–based cohort of 6,814 men and women aged 45 to 84 years with four distinct ethnic groups (white, black, Hispanic, and Chinese) who were free of clinical cardiovascular disease and were recruited during 2000-2002. Of these participants, 24 were excluded who did not have electrocardiogram (ECG) data. Further, 905 participants with pre-existing diabetes mellitus or without known glucose status were excluded. Also, of note, no individuals with pacemakers were enrolled in the MESA study. The detailed protocols for exam-related blood pressure measurements16 and fasting laboratory blood analyses16 have been previously published.
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Fasting Blood Glucose Individuals in the study were initially classified into one of two groups using criteria based on the
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fasting glucose level established by the American Diabetes Association.17 These groups included normal
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fasting glucose (NFG; fasting glucose level < 100 mg/dL) and impaired fasting glucose (IFG; fasting glucose level 100-125 mg/dL).
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Electrocardiography
Standard 12 lead ECGs were digitally acquired using a Marquette MAC–PC electrocardiograph
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(Marquette electronics, Milwaukee, Wisconsin) at 10 mm/mV calibration and speed of 25 mm/secs. All ECGs were read centrally and visually inspected for technical errors or inadequate quality. Participants baseline exam (2000-2002).18
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Unrecognized Myocardial Infarction
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with pacemakers were excluded from the study. Standard 12 lead ECGs were obtained during the
The definition employed for UMI was that used by previous publications.19 In summary, an unrecognized myocardial infarction was defined as the presence of major Q waves that met the specific
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standards for the Minnesota code (codes 1 – 1 through 1 – 2, except 1 – 2 – 8) or the presence of smaller Q waves (code 1 – 2 – 8 or 1 – 3) when combined with significant ST–T–wave abnormalities (codes 4-1
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Covariates
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through 4-3 or codes 4-2 through 5–3).
As part of the baseline exam, participants submitted fasting blood samples. Total cholesterol and HDL-C were measured in EDTA plasma on the Roche/Hitachi 911 Automatic Analyzer (Roche Diagnostics Corporation, Indianapolis, IN) using a cholesterol esterase, cholesterol oxidase reaction (Chol R1, Roche Diagnostics Corporation). Before measurement of HDL-C, the non-HDL-C fractions were precipitated with magnetic 50,000 MW dextran sulfate and magnesium chloride. Triglycerides were measured using a glycerol blanked enzymatic method (Trig/GB, Roche Diagnostics Corporation). During baseline exam, histories and physical exams were performed to obtain covariate clinical information. Resting, seated systolic and diastolic blood pressure was measured 3 times using a Dinamap automated oscillometric sphygmomanometer (Model pro100l Critkon, Tampa Fl); the last 2 measures were averaged for analyses. Hypertension was defined on the basis of use of an antihypertensive medications or BP>= 140/90. Use of lipid-lowering medication was used as an indicator of being
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ACCEPTED MANUSCRIPT diagnosed wtih high cholesterol. Cigarette use was divided into 3 groups: never, former, and current, which was defined as having smoked within the past 30 days.
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Statistical Analysis
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Baseline characteristics were described for NFG and IFG by presence of UMI. T-tests and chi square tests were performed to identify statistical differences in baseline characteristics between the groups, with no prior myocardial infarction serving as our reference for NFG and IFG separately. A p
software version 9.1 (SAS Institute, Inc.; Cary, NC).
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value of <0.05 was considered statistically significant. All statistical analyses were performed using SAS
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The unadjusted relationship between fasting glucose status and unrecognized myocardial infarction was quantified by overall prevalence and crude odds ratios. Next, two logistic regression
glucose status as an independent variable:
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models were used to adjust for covariates with baseline UMI as the dependent variable and fasting
Model 1: age, race, gender, and body mass index
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Model 2: Model 1 + hypertension, systolic blood pressure, anti-hypertensive medication use, total cholesterol, high-density lipoprotein cholesterol, lipid-lowering medication use, and cigarette use The Multi-Ethnic Study of Atherosclerosis is funded by the NIH R01HL076438. The authors are
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solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of
Results
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the paper and its final contents.
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After exclusions, the study population consisted of 5,885 participants. Their characteristics by fasting glucose status and UMI are shown in Table 1. Among participants with normal fasting glucose, those with an UMI tended to be older. Among participants with impaired fasting glucose, those with an UMI were more likely to be male. There was a slightly higher representation of African-Americans overall in the impaired fasting glucose group compared to the normal fasting glucose group. There was a higher prevalence of UMI in those with IFG compared with those with NFG [3.5% (n=72) vs 1.4% (n=30); p<0.001; Table 1]. For model 1, there was a higher odds for an UMI among those with IFG compared with those with NFG [OR: 1.78 (95% confidence interval: 1.12-2.77); p = 0.015; see Table 2]. For model 2, this relationship persisted after further adjustment [OR: 1.60 (95% confidence interval: 1.01-2.48); p = 0.048; see Table 2]. Results from gender-stratified analyses showed that both men and women had a tendency towards increased UMIs among those with IFG compared to those with NFG, but this result was only statistically significant among men (Table 2). For further comparison of IFG as a risk factor for UMI, the ORs and their p-values from model 2 are presented (Table 3).
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Discussion Several key findings are demonstrated in this investigation. Most importantly, this study reveals
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an association between impaired fasting glucose and unrecognized myocardial infarctions. Among the
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MESA multi-ethnic cohort, persons with IFG have an increased risk of an UMI, and this relationship persists with adjustment for potentially confounding variables. This observation suggests that the association may be mediated by pathways not shared with other covariates, such as BMI, cholesterol, and
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systolic blood pressure. This finding further substantiates the central role of IFG and its associated sequelae in the causal pathway for UMI.
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One of the most common complications of long-standing diabetes mellitus is the development of peripheral neuropathy,20 which can also affect cardiac autonomic nerves.21 Vinik and Ziegler stated that,
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“one of the most overlooked of all serious complications of diabetes is cardiovascular autonomic neuropathy (CAN), which encompasses damage to the autonomic nerve fibers that innervate the heart and blood vessels.” 22 This is part of the mechanism that may increase the risk of diabetics having clinically
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unrecognized myocardial infarctions. Many studies have suggested that even during initial stages of abnormal glucose metabolism, nerve function may already be impaired.23-27 Papanas and Ziegler found that almost 25% of prediabetics experienced peripheral neuropathy.28 Boulton and Malik suggested that
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impaired glucose tolerance (IGT) can cause neuropathy in both small and large nerve fibers.26 In a 2011 cohort study, Laitinen, et al. found that CAN was common in persons with IGT.29 Because CAN implies
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the potential for some degree of cardiac pain suppression,22, 29-31 it is reasonable to expect that such a condition could suppress the pain usually felt during a myocardial infarction.32 Indeed, one small study of
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diabetic patients demonstrated that the incidence of silent MI was significantly higher in diabetic patients with CAN, compared to those without.32 Thus, CAN may be one of the primary mechanisms by which IFG becomes a risk factor for UMI. Autonomic neuropathy associated with impaired fasting glucose may therefore predispose susceptible individuals to having a UMI. Diabetic individuals are noted to have a higher risk for both symptomatic and asymptomatic myocardial infarctions.7, 8 Because the definition of type 2 diabetes has changed over the years and is based on a continuum of blood glucose levels, it is not unexpected that some level of IFG is also a risk factor for myocardial infarction. In fact, studies have demonstrated this phenomenon.11, 12 In a clinical trial published in 2004, Zeymer et al. found that decreasing postprandial hyperglycemia reduced the incidence of silent MI in subjects with IGT.33 While this is a striking finding, it was based on only seven silent MIs. Many other investigations have found a general increased risk of coronary heart disease and vascular dysfunction among those with prediabetes.34-36 In 2004, Bartnik, et al. showed that abnormal glucose tolerance was almost twice as common among patients with acute MI as in matched controls.37
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ACCEPTED MANUSCRIPT While the relationship between DM with both recognized and unrecognized MIs has been well-described, the association between IFG and UMIs has been more challenging to understand. Another study demonstrated that those with IFG who experience UMIs are at increased risk for subsequent
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cardiovascular events.38 The prevalence of UMI among those with IFG remains unclear.
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Our baseline analysis revealed a statistically significant association between IFG and UMI overall and among men. Clearly there is growing evidence that the biological mechanism underlying the association between abnormal glucose metabolism and silent or unrecognized myocardial infarctions
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differs by gender. In a cross-sectional, population-based study conducted in northern Sweden, impaired glucose tolerance (IGT) was found to be associated with an increased risk of silent MIs among women
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(OR 4.10, 95% CI 1.10 to 15) but no such association was found among men.39 Because any such potential gender differences may have significant implications for clinical practice, additional prospective
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investigations are needed in order to better characterize and understand these differences and their underlying biological mechanisms.
Our study provides more support to the growing body of evidence that abnormal glucose
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metabolism at a level indicative of prediabetes is associated with UMIs. It is well demonstrated that individuals with UMIs are at increased risk of subsequent cardiovascular events.3, 4, 40, 41 In light of our findings, it is possible that individuals who have had an UMI may not be receiving appropriate care as
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mandated for their clinical situation. This suggests that a screening electrocardiogram may provide further risk assessment for prediabetic individuals. A resting 12-lead ECG may represent a cost-effective
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strategy to identify potential risk at the population level given the burden represented by prediabetes. The prevalence of prediabetes in the United States has increased substantially over recent
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decades, with the proportion of U.S. adolescent girls and women growing at a significantly higher rate than males.13, 14 In addition, the prevalence of prediabetes is rapidly rising among many other societies, marking this as a global epidemiological challenge.42, 43 Thus, the population potentially at an increased risk for cardiovascular events is on the rise, with many of these individuals being unaware of their prediabetic condition.44 Appreciating the level of risk associated with IFG can be difficult. Often, by the time an individual has a clinical event, they have already converted to diabetes mellitus.45 Our findings indicate that critical events can happen even within this initial period, prior to conversion to DM. Prior studies have demonstrated that individuals who presented with their first myocardial infarction had a significant likelihood of being diagnosed with impaired fasting glucose.46-48 Stronger efforts to optimize risk factors and prevent conversion to diabetes mellitus may help mitigate some of these potential risks. Further studies will be needed to best identify approaches for clinicians to help normalize abnormal glucose metabolism and reverse some of these initial changes.
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ACCEPTED MANUSCRIPT There are several limitations to our study. First, there is the potential concern for misclassification of participants. Our study based the exposure variable on single measurements of fasting glucose blood level. There is an inherent degree of variability present in this measure.49 A more robust method (although
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clinically less practical) is to assess impaired glucose tolerance with a glucose challenge, which may be
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able to more correctly identify individuals with abnormal glucose metabolism. Second, we were limited in the nature and degree of statistical analyses and questions that could be asked due to limited numbers of
sensitivity and specificity relative to other methods.
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Conclusion
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UMIs. Third, while no imaging or screening test can capture all UMIs, ECGs have a more limited
Impaired fasting glucose is associated with unrecognized myocardial infarctions in a multi-ethnic population free of baseline cardiovascular disease. This association differed by gender, with a significant
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baseline association demonstrated overall and among men. These findings from the gender-stratified analysis suggest the possibility of different underlying biological mechanisms for the IFG-UMI association among men and women. Given the high prevalence of impaired fasting glucose, the
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implications of these findings have significant ramifications for both clinical practice and public health
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alike.
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Table 1. Baseline characteristics presented by fasting glucose status stratified by presence of unrecognized myocardial infarction. (*) means p < 0.05 between normal fasting glucose participants with and without prior unrecognized myocardial infarction. (**) means p < 0.05 between impaired fasting glucose participants with and without prior unrecognized myocardial infarction. Impaired Fasting Glucose
Normal Fasting Glucose
(n=4883)
(n=72)
Age (yrs)
61 ± 10.3
66.7 ± 9*
BMI (kg/m2)
27.6 ± 5.2
28.6 ± 5.6
LDL (mmol/L)
118 ± 31
112 ± 32
HDL (mmol/L)
52.5 ± 15
Trig (mmol/Ll)
123 ± 74
SBP (mmHg)
124 ± 21
DBP (mmHg)
71 ± 10
Hypertension
1883 (39%)
Use of Lipid-Lowering Medication Race
652 (13%)
Unrecognized Myocardial Infarction
(n=900)
(n=30)
64.1 ± 9.8
67 ± 9
30.1 ± 5.7
29.7 ± 4
118.5 ± 31.2
116.7 ± 27
51 ± 15.8
47.4 ± 12.7
43.6 ± 12.3
129.6 ± 62
146.3 ± 91.5
156 ± 96
132 ± 19.3
131 ± 21
141.8 ± 25
74 ± 10.5
74 ± 10.5
81.8 ± 10.5
51 (70%)*
493 (55%)
24 (80%)**
20 (27%)
164 (18%)
6 (20%)
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No Prior Myocardial Infarction
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Unrecognized Myocardial Infarction
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No Prior Myocardial Infarction
2104 (43%)
36 (50%)
275 (30%)
10 (33%)
-Chinese
555 (11%)
4 (6%)
133 (14%)
4 (13%)
-African American
1244 (25%)
18 (25%)
266 (30%)
11 (37%)
980 (20%)
14 (19%)
226 (25%)
5 (17%)
2174 (45%)
40 (55%)
500 (56%)
22 (73%)**
2709 (55%)
32 (44%)
400 (44%)
8 (27%)
-Never
2456 (50%)
36 (50%)
455 (50%)
9 (30%)
-Former
1769 (36%)
26 (37%)
333 (37%)
17 (57%)
-Current
645 (13%)
9 (12.7%)
107 (12%)
4 (13%)
Gender -Male -Female
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-Hispanic
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-Caucasian
Smoking
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ACCEPTED MANUSCRIPT Table 2. Baseline crude and adjusted odds ratios for UMI by IFG, stratified by gender. (*) indicates p < 0.05. P-value
UMI adjusted for model 1
2.40
0.0027*
1.96
PValue
UMI adjusted for model 2
PValue
(1.35-5.45) Women
(1.11-3.38)
1.69
0.22
1.38
0.0009*
1.78
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2.26
0.45
(0.57-2.97)
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(0.61-4.57)
(1.12-2.77)
0.03*
(1.06-3.27) 1.24
0.6
(0.51-2.7) 1.60
0.0481*
(1.01-2.48)
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(1.50-3.50)
0.015*
1.89
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Combined
0.021*
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Men
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UMI on Baseline Exam
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ACCEPTED MANUSCRIPT Table 3. Odds ratios for model covariates in model 2 for an unrecognized myocardial infarction. For continuous variables, the odds ratios are derived from a single unit increase. Odds Ratio (95% Confidence Interval) 1.03 (1.01-1.06) 1.70 (1.07-2.71) 2.36 (1.2-4.68) 1.60 (1.01-2.48)
Male
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Hypertension Impaired Fasting Glucose
-Hispanic
Systolic Blood Pressure (mmHg)
Total Cholesterol (mmol/L)
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HDL Cholesterol (mmol/L)
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Anti-Hypertensive Medication
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BMI (kg/m2)
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Lipid-Lowering Medication
Smoking Status (Relative to Never) -Former
0.0124 0.0481
0.51
1.08 (0.70-1.69) 1.32 (0.66-2.46)
0.71
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-Chinese-American
0.0245
0.84 (0.5-1.4) 0.64 (0.27-1.33) 0.82 (0.46-1.41) 0.99 (0.95-1.04) 0.99 (0.98-1.01) 1.22 (0.72-2.12) 1.00 (0.99-1.00) 0.99 (0.98-1.01) 1.45 (0.89-2.3)
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Race (Relative to Caucasian) -African-American
-Current
0.0091
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Age (years)
P-Value
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Covariate
0.24 0.49 0.79 0.48 0.47 0.81 0.58 0.13
0.41
15
S0002-8703(15)00513-X doi: 10.1016/j.ahj.2015.08.003 YMHJ 4978
To appear in:
American Heart Journal
Received date: Accepted date:
15 June 2015 5 August 2015
Please cite this article as: Stacey Richard Brandon, Leaverton Paul E., Schocken Douglas D., Peregoy Jennifer A., Bertoni Alain G., Prediabetes and the Association with Unrecognized Myocardial Infarction in the Multi-Ethnic Study of Atherosclerosis, American Heart Journal (2015), doi: 10.1016/j.ahj.2015.08.003
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Prediabetes and the Association with Unrecognized Myocardial Infarction in the Multi-Ethnic Study of Atherosclerosis
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R. Brandon Stacey, MD, MS1; Paul E. Leaverton, PhD3; Douglas D. Schocken, MD4; Jennifer A. Peregoy, MPH3; Alain G. Bertoni, MD, MPH2
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Running Title: Prediabetes and UMI
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From the Departments of Internal Medicine Section on Cardiology,1 Public Health Sciences2 at the Wake Forest University School of Medicine, Winston-Salem, North Carolina, 27157, USA; Department of Epidemiology and Biostatistics3, College of Public Health, University of South Florida, Tampa, Florida, USA; Division of Cardiology4, Department of Medicine, Duke University Medical Center, Durham, North Carolina
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Author Contributions: R.S. researched data/wrote manuscript; P.L researched data and contributed to discussion; D.D. contributed to discussion; J.P. wrote and edited manuscript; A.B. reviewed/edited manuscript.
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Research supported in part by NIH R01HL076438.
Address for Correspondence:
R. Brandon Stacey, MD, MS Cardiology Section Watlington Hall Wake Forest University School of Medicine Medical Center Boulevard Winston-Salem, North Carolina 27157-1045 Phone: (336) 716-2524 Fax: (336) 713-9188 E-mail: [email protected]
Financial Disclosures: None Conflicts of Interest: None Total Word Count: 4,056 Abstract Word Count: 254
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ACCEPTED MANUSCRIPT Abstract Background: With one-quarter of initial myocardial infarctions (MI) being unrecognized MI (UMI), recognition is critical to minimize further cardiovascular risk. Diabetes mellitus (DM) is an established
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risk factor for UMI. If impaired fasting glucose (IFG) also increased the risk for UMI, it would represent
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a significant public health challenge due to the rapid worldwide increase in IFG prevalence. We compared participants with IFG to those with normal fasting glucose (NFG) to determine if IFG was
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associated with UMIs.
Methods: We performed cross-sectional analyses from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort study. There were 6,814 participants recruited during July 2000 to
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September 2002 from the general community at 6 field sites. After excluding those with diabetes mellitus or missing variables, 5,885 participants were included. At baseline, there were 4,955 participants with
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NFG and 930 participants with IFG. The main outcome was an UMI defined by the presence of pathological Q waves or minor Q waves with ST-T abnormalities on initial 12-lead electrocardiogram (ECG). Logistic regression was used to generate crude odds ratios and adjust for covariates.
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Results: There was a higher prevalence of UMI in those with IFG compared with those with NFG [3.5% (n=72) vs 1.4% (n=30)]. After adjustment for multiple risk factors, there was a higher odds of an UMI
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among those with IFG compared with those with NFG [OR: 1.60 (95% CI: 1.0-2.5); p = 0.048]. Conclusions: Impaired fasting glucose is associated with unrecognized myocardial infarctions in a multi-
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ethnic population free of baseline cardiovascular disease.
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Keywords: Impaired fasting glucose, myocardial infarction, ECG
Word count: 250
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ACCEPTED MANUSCRIPT Background Unrecognized myocardial infarctions (UMIs) are subclinical myocardial infarctions that by definition go unrecognized by both patient and physician, and may be either symptomatic or
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asymptomatic (i.e., “silent”). UMI is a prevalent condition with an estimated 25 percent of first
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myocardial infarctions being unrecognized.1 UMIs are predictive of later symptomatic infarctions and for other subsequent major cardiovascular events, including coronary death.2-4 A precise prevalence for UMIs in the United States is difficult to obtain; however, a recent study found the prevalence of silent
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MIs to be as high as 17%, which is higher than reported by previous studies.3
Unfortunately, there is a dearth of information about risk factors that may predispose one to an
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UMI as opposed to a clinically recognized myocardial infarction (MI).5 One of the most cited of the known MI risk factors is the presence of diabetes mellitus (DM).6, 7 In particular, it has been shown that
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the greater the duration of DM, the greater the risk of MI.8 Because of this observation, some have investigated whether or not persons in a prediabetic condition may also be at greater risk for cardiovascular disease (CVD), including MIs, as compared to those with normal glucose values.9-12 The
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results have been inconclusive and this possibility remains under-investigated. The prevalence of prediabetes in the United States has increased substantially in recent decades to over a third of the adult population, with the proportion of U.S. women and adolescent girls with
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prediabetes growing at a significantly higher rate than males.13, 14 Many will eventually progress to overt DM, and for those, the risks for UMI are well described. However, for those with impaired fasting
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glucose (IFG), an indicator of prediabetes, the risk for UMI is less certain. If IFG were associated with even a modest increase in risk of UMI, the public health ramifications would be substantial. To better
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assess whether such an association exists, we turned to the Multi-Ethnic Study of Atherosclerosis to examine this question quantitatively.
Methods The Multi-Ethnic Study of Atherosclerosis (MESA) Population - Study Participants The recruitment criteria for participants in MESA have been published previously.15 The MESA study is a population–based cohort of 6,814 men and women aged 45 to 84 years with four distinct ethnic groups (white, black, Hispanic, and Chinese) who were free of clinical cardiovascular disease and were recruited during 2000-2002. Of these participants, 24 were excluded who did not have electrocardiogram (ECG) data. Further, 905 participants with pre-existing diabetes mellitus or without known glucose status were excluded. Also, of note, no individuals with pacemakers were enrolled in the MESA study. The detailed protocols for exam-related blood pressure measurements16 and fasting laboratory blood analyses16 have been previously published.
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Fasting Blood Glucose Individuals in the study were initially classified into one of two groups using criteria based on the
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fasting glucose level established by the American Diabetes Association.17 These groups included normal
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fasting glucose (NFG; fasting glucose level < 100 mg/dL) and impaired fasting glucose (IFG; fasting glucose level 100-125 mg/dL).
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Electrocardiography
Standard 12 lead ECGs were digitally acquired using a Marquette MAC–PC electrocardiograph
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(Marquette electronics, Milwaukee, Wisconsin) at 10 mm/mV calibration and speed of 25 mm/secs. All ECGs were read centrally and visually inspected for technical errors or inadequate quality. Participants baseline exam (2000-2002).18
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Unrecognized Myocardial Infarction
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with pacemakers were excluded from the study. Standard 12 lead ECGs were obtained during the
The definition employed for UMI was that used by previous publications.19 In summary, an unrecognized myocardial infarction was defined as the presence of major Q waves that met the specific
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standards for the Minnesota code (codes 1 – 1 through 1 – 2, except 1 – 2 – 8) or the presence of smaller Q waves (code 1 – 2 – 8 or 1 – 3) when combined with significant ST–T–wave abnormalities (codes 4-1
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Covariates
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through 4-3 or codes 4-2 through 5–3).
As part of the baseline exam, participants submitted fasting blood samples. Total cholesterol and HDL-C were measured in EDTA plasma on the Roche/Hitachi 911 Automatic Analyzer (Roche Diagnostics Corporation, Indianapolis, IN) using a cholesterol esterase, cholesterol oxidase reaction (Chol R1, Roche Diagnostics Corporation). Before measurement of HDL-C, the non-HDL-C fractions were precipitated with magnetic 50,000 MW dextran sulfate and magnesium chloride. Triglycerides were measured using a glycerol blanked enzymatic method (Trig/GB, Roche Diagnostics Corporation). During baseline exam, histories and physical exams were performed to obtain covariate clinical information. Resting, seated systolic and diastolic blood pressure was measured 3 times using a Dinamap automated oscillometric sphygmomanometer (Model pro100l Critkon, Tampa Fl); the last 2 measures were averaged for analyses. Hypertension was defined on the basis of use of an antihypertensive medications or BP>= 140/90. Use of lipid-lowering medication was used as an indicator of being
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ACCEPTED MANUSCRIPT diagnosed wtih high cholesterol. Cigarette use was divided into 3 groups: never, former, and current, which was defined as having smoked within the past 30 days.
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Statistical Analysis
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Baseline characteristics were described for NFG and IFG by presence of UMI. T-tests and chi square tests were performed to identify statistical differences in baseline characteristics between the groups, with no prior myocardial infarction serving as our reference for NFG and IFG separately. A p
software version 9.1 (SAS Institute, Inc.; Cary, NC).
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value of <0.05 was considered statistically significant. All statistical analyses were performed using SAS
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The unadjusted relationship between fasting glucose status and unrecognized myocardial infarction was quantified by overall prevalence and crude odds ratios. Next, two logistic regression
glucose status as an independent variable:
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models were used to adjust for covariates with baseline UMI as the dependent variable and fasting
Model 1: age, race, gender, and body mass index
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Model 2: Model 1 + hypertension, systolic blood pressure, anti-hypertensive medication use, total cholesterol, high-density lipoprotein cholesterol, lipid-lowering medication use, and cigarette use The Multi-Ethnic Study of Atherosclerosis is funded by the NIH R01HL076438. The authors are
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solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of
Results
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the paper and its final contents.
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After exclusions, the study population consisted of 5,885 participants. Their characteristics by fasting glucose status and UMI are shown in Table 1. Among participants with normal fasting glucose, those with an UMI tended to be older. Among participants with impaired fasting glucose, those with an UMI were more likely to be male. There was a slightly higher representation of African-Americans overall in the impaired fasting glucose group compared to the normal fasting glucose group. There was a higher prevalence of UMI in those with IFG compared with those with NFG [3.5% (n=72) vs 1.4% (n=30); p<0.001; Table 1]. For model 1, there was a higher odds for an UMI among those with IFG compared with those with NFG [OR: 1.78 (95% confidence interval: 1.12-2.77); p = 0.015; see Table 2]. For model 2, this relationship persisted after further adjustment [OR: 1.60 (95% confidence interval: 1.01-2.48); p = 0.048; see Table 2]. Results from gender-stratified analyses showed that both men and women had a tendency towards increased UMIs among those with IFG compared to those with NFG, but this result was only statistically significant among men (Table 2). For further comparison of IFG as a risk factor for UMI, the ORs and their p-values from model 2 are presented (Table 3).
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Discussion Several key findings are demonstrated in this investigation. Most importantly, this study reveals
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an association between impaired fasting glucose and unrecognized myocardial infarctions. Among the
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MESA multi-ethnic cohort, persons with IFG have an increased risk of an UMI, and this relationship persists with adjustment for potentially confounding variables. This observation suggests that the association may be mediated by pathways not shared with other covariates, such as BMI, cholesterol, and
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systolic blood pressure. This finding further substantiates the central role of IFG and its associated sequelae in the causal pathway for UMI.
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One of the most common complications of long-standing diabetes mellitus is the development of peripheral neuropathy,20 which can also affect cardiac autonomic nerves.21 Vinik and Ziegler stated that,
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“one of the most overlooked of all serious complications of diabetes is cardiovascular autonomic neuropathy (CAN), which encompasses damage to the autonomic nerve fibers that innervate the heart and blood vessels.” 22 This is part of the mechanism that may increase the risk of diabetics having clinically
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unrecognized myocardial infarctions. Many studies have suggested that even during initial stages of abnormal glucose metabolism, nerve function may already be impaired.23-27 Papanas and Ziegler found that almost 25% of prediabetics experienced peripheral neuropathy.28 Boulton and Malik suggested that
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impaired glucose tolerance (IGT) can cause neuropathy in both small and large nerve fibers.26 In a 2011 cohort study, Laitinen, et al. found that CAN was common in persons with IGT.29 Because CAN implies
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the potential for some degree of cardiac pain suppression,22, 29-31 it is reasonable to expect that such a condition could suppress the pain usually felt during a myocardial infarction.32 Indeed, one small study of
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diabetic patients demonstrated that the incidence of silent MI was significantly higher in diabetic patients with CAN, compared to those without.32 Thus, CAN may be one of the primary mechanisms by which IFG becomes a risk factor for UMI. Autonomic neuropathy associated with impaired fasting glucose may therefore predispose susceptible individuals to having a UMI. Diabetic individuals are noted to have a higher risk for both symptomatic and asymptomatic myocardial infarctions.7, 8 Because the definition of type 2 diabetes has changed over the years and is based on a continuum of blood glucose levels, it is not unexpected that some level of IFG is also a risk factor for myocardial infarction. In fact, studies have demonstrated this phenomenon.11, 12 In a clinical trial published in 2004, Zeymer et al. found that decreasing postprandial hyperglycemia reduced the incidence of silent MI in subjects with IGT.33 While this is a striking finding, it was based on only seven silent MIs. Many other investigations have found a general increased risk of coronary heart disease and vascular dysfunction among those with prediabetes.34-36 In 2004, Bartnik, et al. showed that abnormal glucose tolerance was almost twice as common among patients with acute MI as in matched controls.37
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ACCEPTED MANUSCRIPT While the relationship between DM with both recognized and unrecognized MIs has been well-described, the association between IFG and UMIs has been more challenging to understand. Another study demonstrated that those with IFG who experience UMIs are at increased risk for subsequent
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cardiovascular events.38 The prevalence of UMI among those with IFG remains unclear.
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Our baseline analysis revealed a statistically significant association between IFG and UMI overall and among men. Clearly there is growing evidence that the biological mechanism underlying the association between abnormal glucose metabolism and silent or unrecognized myocardial infarctions
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differs by gender. In a cross-sectional, population-based study conducted in northern Sweden, impaired glucose tolerance (IGT) was found to be associated with an increased risk of silent MIs among women
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(OR 4.10, 95% CI 1.10 to 15) but no such association was found among men.39 Because any such potential gender differences may have significant implications for clinical practice, additional prospective
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investigations are needed in order to better characterize and understand these differences and their underlying biological mechanisms.
Our study provides more support to the growing body of evidence that abnormal glucose
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metabolism at a level indicative of prediabetes is associated with UMIs. It is well demonstrated that individuals with UMIs are at increased risk of subsequent cardiovascular events.3, 4, 40, 41 In light of our findings, it is possible that individuals who have had an UMI may not be receiving appropriate care as
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mandated for their clinical situation. This suggests that a screening electrocardiogram may provide further risk assessment for prediabetic individuals. A resting 12-lead ECG may represent a cost-effective
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strategy to identify potential risk at the population level given the burden represented by prediabetes. The prevalence of prediabetes in the United States has increased substantially over recent
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decades, with the proportion of U.S. adolescent girls and women growing at a significantly higher rate than males.13, 14 In addition, the prevalence of prediabetes is rapidly rising among many other societies, marking this as a global epidemiological challenge.42, 43 Thus, the population potentially at an increased risk for cardiovascular events is on the rise, with many of these individuals being unaware of their prediabetic condition.44 Appreciating the level of risk associated with IFG can be difficult. Often, by the time an individual has a clinical event, they have already converted to diabetes mellitus.45 Our findings indicate that critical events can happen even within this initial period, prior to conversion to DM. Prior studies have demonstrated that individuals who presented with their first myocardial infarction had a significant likelihood of being diagnosed with impaired fasting glucose.46-48 Stronger efforts to optimize risk factors and prevent conversion to diabetes mellitus may help mitigate some of these potential risks. Further studies will be needed to best identify approaches for clinicians to help normalize abnormal glucose metabolism and reverse some of these initial changes.
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ACCEPTED MANUSCRIPT There are several limitations to our study. First, there is the potential concern for misclassification of participants. Our study based the exposure variable on single measurements of fasting glucose blood level. There is an inherent degree of variability present in this measure.49 A more robust method (although
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clinically less practical) is to assess impaired glucose tolerance with a glucose challenge, which may be
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able to more correctly identify individuals with abnormal glucose metabolism. Second, we were limited in the nature and degree of statistical analyses and questions that could be asked due to limited numbers of
sensitivity and specificity relative to other methods.
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Conclusion
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UMIs. Third, while no imaging or screening test can capture all UMIs, ECGs have a more limited
Impaired fasting glucose is associated with unrecognized myocardial infarctions in a multi-ethnic population free of baseline cardiovascular disease. This association differed by gender, with a significant
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baseline association demonstrated overall and among men. These findings from the gender-stratified analysis suggest the possibility of different underlying biological mechanisms for the IFG-UMI association among men and women. Given the high prevalence of impaired fasting glucose, the
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implications of these findings have significant ramifications for both clinical practice and public health
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alike.
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(44) Gregg EW, Boyle JP, Thompson TJ, Barker LE, Albright AL, Williamson DF. Modeling the impact of prevention policies on future diabetes prevalence in the United States: 2010-2030. Popul Health Metr 2013 September 18;11(1):18-1.
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(47) Knudsen EC, Seljeflot I, Abdelnoor M et al. Impact of newly diagnosed abnormal glucose regulation on long-term prognosis in low risk patients with ST-elevation myocardial infarction: A follow-up study. BMC Endocr Disord 2011 July 29;11:14. doi: 10.1186/1472-6823-11-14.:141. (48) Tamita K, Katayama M, Takagi T et al. Newly diagnosed glucose intolerance and prognosis after acute myocardial infarction: comparison of post-challenge versus fasting glucose concentrations. Heart 2012 June;98(11):848-54. (49) Harris MI, Flegal KM, Cowie CC et al. Prevalence of diabetes, impaired fasting glucose, and impaired glucose tolerance in U.S. adults. The Third National Health and Nutrition Examination Survey, 1988-1994. Diabetes Care 1998 April;21(4):518-24.
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ACCEPTED MANUSCRIPT
T
Table 1. Baseline characteristics presented by fasting glucose status stratified by presence of unrecognized myocardial infarction. (*) means p < 0.05 between normal fasting glucose participants with and without prior unrecognized myocardial infarction. (**) means p < 0.05 between impaired fasting glucose participants with and without prior unrecognized myocardial infarction. Impaired Fasting Glucose
Normal Fasting Glucose
(n=4883)
(n=72)
Age (yrs)
61 ± 10.3
66.7 ± 9*
BMI (kg/m2)
27.6 ± 5.2
28.6 ± 5.6
LDL (mmol/L)
118 ± 31
112 ± 32
HDL (mmol/L)
52.5 ± 15
Trig (mmol/Ll)
123 ± 74
SBP (mmHg)
124 ± 21
DBP (mmHg)
71 ± 10
Hypertension
1883 (39%)
Use of Lipid-Lowering Medication Race
652 (13%)
Unrecognized Myocardial Infarction
(n=900)
(n=30)
64.1 ± 9.8
67 ± 9
30.1 ± 5.7
29.7 ± 4
118.5 ± 31.2
116.7 ± 27
51 ± 15.8
47.4 ± 12.7
43.6 ± 12.3
129.6 ± 62
146.3 ± 91.5
156 ± 96
132 ± 19.3
131 ± 21
141.8 ± 25
74 ± 10.5
74 ± 10.5
81.8 ± 10.5
51 (70%)*
493 (55%)
24 (80%)**
20 (27%)
164 (18%)
6 (20%)
NU
MA
ED
PT
No Prior Myocardial Infarction
RI P
Unrecognized Myocardial Infarction
SC
No Prior Myocardial Infarction
2104 (43%)
36 (50%)
275 (30%)
10 (33%)
-Chinese
555 (11%)
4 (6%)
133 (14%)
4 (13%)
-African American
1244 (25%)
18 (25%)
266 (30%)
11 (37%)
980 (20%)
14 (19%)
226 (25%)
5 (17%)
2174 (45%)
40 (55%)
500 (56%)
22 (73%)**
2709 (55%)
32 (44%)
400 (44%)
8 (27%)
-Never
2456 (50%)
36 (50%)
455 (50%)
9 (30%)
-Former
1769 (36%)
26 (37%)
333 (37%)
17 (57%)
-Current
645 (13%)
9 (12.7%)
107 (12%)
4 (13%)
Gender -Male -Female
AC
-Hispanic
CE
-Caucasian
Smoking
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ACCEPTED MANUSCRIPT Table 2. Baseline crude and adjusted odds ratios for UMI by IFG, stratified by gender. (*) indicates p < 0.05. P-value
UMI adjusted for model 1
2.40
0.0027*
1.96
PValue
UMI adjusted for model 2
PValue
(1.35-5.45) Women
(1.11-3.38)
1.69
0.22
1.38
0.0009*
1.78
MA
2.26
0.45
(0.57-2.97)
NU
(0.61-4.57)
(1.12-2.77)
0.03*
(1.06-3.27) 1.24
0.6
(0.51-2.7) 1.60
0.0481*
(1.01-2.48)
CE
PT
ED
(1.50-3.50)
0.015*
1.89
AC
Combined
0.021*
SC
Men
RI P
T
UMI on Baseline Exam
14
ACCEPTED MANUSCRIPT Table 3. Odds ratios for model covariates in model 2 for an unrecognized myocardial infarction. For continuous variables, the odds ratios are derived from a single unit increase. Odds Ratio (95% Confidence Interval) 1.03 (1.01-1.06) 1.70 (1.07-2.71) 2.36 (1.2-4.68) 1.60 (1.01-2.48)
Male
SC
Hypertension Impaired Fasting Glucose
-Hispanic
Systolic Blood Pressure (mmHg)
Total Cholesterol (mmol/L)
CE
HDL Cholesterol (mmol/L)
PT
Anti-Hypertensive Medication
ED
BMI (kg/m2)
AC
Lipid-Lowering Medication
Smoking Status (Relative to Never) -Former
0.0124 0.0481
0.51
1.08 (0.70-1.69) 1.32 (0.66-2.46)
0.71
MA
-Chinese-American
0.0245
0.84 (0.5-1.4) 0.64 (0.27-1.33) 0.82 (0.46-1.41) 0.99 (0.95-1.04) 0.99 (0.98-1.01) 1.22 (0.72-2.12) 1.00 (0.99-1.00) 0.99 (0.98-1.01) 1.45 (0.89-2.3)
NU
Race (Relative to Caucasian) -African-American
-Current
0.0091
RI P
Age (years)
P-Value
T
Covariate
0.24 0.49 0.79 0.48 0.47 0.81 0.58 0.13
0.41
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