Abstract
Body mass index (BMI), as an important risk factor related to metabolic disease. However, in some studies higher BMI was emphasized as a beneficial factor in the clinical course of patients after acute myocardial infarction (AMI) in a concept known as the “BMI paradox.” The purpose of this study was to investigate how clinical outcomes of patients treated for AMI differed according to BMI levels. A total of 10,566 patients in the Korea Acute Myocardial Infarction Registry-National Institutes of Health (KAMIR-NIH) from May 2010 to June 2015 were divided into three BMI groups (group 1: BMI < 22 kg/m2, group 2: ≥ 22 and < 26 kg/m2, and group 3: ≥ 26 kg/m2). The primary outcome was major adverse cardiac and cerebrovascular event (MACCE) at 3 years of follow-up. At 1 year of follow-up, the incidence of MACCE in group 1 was 10.1% of that in group 3, with a hazard ratio (HR) of 2.27, and 6.5% in group 2, with an HR of 1.415. This tendency continued up to 3 years of follow-up. The study demonstrated that lower incidence of MACCE in the high BMI group of Asians during the 3-year follow-up period compared to the low BMI group. The results implied higher BMI could exert a positive effect on the long-term clinical outcomes of patients with AMI undergoing percutaneous coronary intervention (PCI).
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Introduction
The appropriate control of risk factors affecting the progression of cardiovascular (CV) disease and the incidence of complications is important to improving the clinical outcomes of patients diagnosed with acute myocardial infarction (AMI). Obesity has been considered a risk factor related to ischemic heart disease1,2. BMI, a parameter of obesity, has been used to estimate the degree of obesity. According to prior studies, obesity may contribute to atherosclerotic changes by activating inflammatory metabolism3. It may also be related to neurohormonal imbalance, predisposing left ventricular remodeling4. Higher BMI has been assumed to correlate with higher CV disease occurrence and worse patient prognosis. In contrast, several recent studies showed contrary results on the relationship between BMI and CV disease prognosis, which has been called the “BMI paradox”5,6,7,8. The relationship was confirmed not only in patients with AMI but also in the general population9. Our prior study also found that higher BMI was a protective factor in 1-year all-cause death after AMI10. However, large-scale, long-term studies of the BMI paradox concept in Asians are lacking. In this study, we aimed to identify the long-term occurrence of MACCE after AMI during 1-year and 3-year follow-up periods in Asians according to BMI.
Methods
Study design and population
The Korea Acute Myocardial Infarction Registry-National Institutes of Health (KAMIR-NIH) database was accessed for this study. Out of 13,104 patients, 10,566 with AMI who were treated with PCI from May 2010 to June 2015 were enrolled. They were divided into three groups according to BMI. Patients who were not treated with PCI (2230) and 308 patients with missing data were excluded (Fig. 1). The KAMIR-NIH was a prospective, multicenter, observational cohort study supported by a grant from 15 Korea Centers for Disease Control and Prevention. All of the centers that participated in the study were high-volume centers familiar with PCI procedures using the standard study protocol. This study was conducted according to the Declaration of Helsinki with the informed consent of the patients and approval of the institutional review board at each participating institution (IRB of the Catholic University of Korea, Daejeon, St. Mary’s hospital, IRB of the Catholic University of Korea, Seoul, St. Mary’s hospital, Gachon Gil Medical Center, IRB of Chonnam National University, Korea University Guro IVD Suppport Center, Seoul National University Hospital Biomedical Research Institute, Samsung Medical Center Clinical Trial Center, IRB of Chungnam National University Hospital, IRB of Chungbuk National University Hospital, IRB of Kyungpook National University Hospital, Clinical Trial Center of Keimyung University Dongsan Medical Center, Clinical Trial Center of Pusan National University Hospital, IRB of Wonkwang University Hospital and IRB of Chonbuk National University Hospital).
Percutaneous coronary intervention procedure and medical treatment
A standardized procedure protocol based on AMI guidelines was applied to patients diagnosed with AMI. The procedural process and selection of devices among operators were slightly different. However, the same regimen was adopted for pre/postprocedural antiplatelet therapy and periprocedural anticoagulation. Preprocedural antiplatelet therapy included aspirin (200 mg) and clopidogrel (300 or 600 mg), ticagrelor (180 mg), or prasugrel (60 mg). Postprocedural antiplatelet therapy was conducted. Aspirin (100 mg/day) with clopidogrel (75 mg/day), ticagrelor (90 mg twice/day), prasugrel (10 mg/day) was taken for at least 12 months, and after that aspirin (100–200 mg/day) was maintained11.
Definitions and study end-points
We adopted the same definitions described in our prior study. The diagnosis of AMI was based on the value of cardiac biomarkers creatinine kinase-MB and troponin I or T, and other clinical findings, including patient’s symptoms, electrocardiogram (ECG) changes, and imaging, such as transthoracic echocardiogram12.
BMI was calculated as weight (kg) divided by height squared (m2). As in our previous study, the study groups were equally divided into quartile10. BMI was divided into three groups and two additional groups. Group 1 was a BMI of < 22 kg/m2, group 2 was 22 to < 26 kg/m2, group 3 was ≥ 26 kg/m2, with supplementary groups 4 (BMI ≥ 26 to < 30 kg/m2) and 5 (≥ 30 kg/m2).
The presence of underlying disease was evaluated on admission. Chronic kidney disease (CKD) was defined as a glomerular filtration rate (GFR) upon admission of 60 mL/min per 1.73m2, according to the Modification of Diet and Renal Disease Study formula13. Fasting glucose concentration of ≥ 7.0 mmol/L, a blood glucose concentration of ≥ 11.0 mmol/L in a 75 g, 2-h oral glucose tolerance test, or the use of antidiabetic therapy was defined as diabetes mellitus (DM). A history of systolic blood pressure ≥ 140 mmHg and a diastolic pressure of ≥ 90 mmHg, or the use of antihypertensive therapy were considered to indicate hypertension (HTN). A fasting total cholesterol concentration of ≥ 220 mg/dL, a fasting triglyceride concentration of ≥ 150 mg/dL, or the use of antihyperlipidemic therapy were regarded as hyperlipidemia.
The primary outcome was MACCE at 3 years of follow-up. The secondary outcome was all-cause death, heart failure, stent thrombosis, target vessel revascularization (TVR), TIMI (thrombolysis in myocardial infarction), and minor bleeding at 3 years of follow-up. MACCE, as the composite of cardiac and cerebrovascular events, included cardiac death, heart disease, and cerebrovascular disease. Death caused by cardiac dysfunction related to ischemic heart disease, heart failure, or arrhythmia, and unwitnessed death was considered to be cardiac death (CD). Death from causes except cardiac disease was defined as all-cause death (AD). MI was defined as mentioned above, and heart failure was considered an ejection fraction of < 40% during follow-up, with signs and symptoms of heart failure. A cerebrovascular event was defined as a stroke with accompanying neurological impairment lasting longer than 24 h. Percutaneous or surgical revascularization of the stent-inserted lesion, including 5 mm margin segments more proximally or distally, was regarded as TVR. Stent thrombosis was evaluated according to the Academic Research Consortium Definition14. Minor bleeding was considered overt clinical bleeding, which was regarded as a fall in hemoglobin less than 3 or equal to 5 g/dL or in hematocrit less than 9% or equal to 15%15.
Statistical analyses
Continuous variables are presented as the mean ± standard deviation and analyzed with the Kruskal–Wallis test. Categorical variables were analyzed by Pearson’s chi-squared test and shown as frequencies and percentages. Analysis of variance (ANOVA) was used to compare BMI groups. Bonferroni’s test was used for post-hoc tests.
The Cox-proportional hazard model was used to evaluate the primary outcome, and the hazard ratio (HR) with a 95% confidence interval (CI) was calculated. All of the variables in Tables 1, 2 and 3 were included and analyzed by univariate analysis. The multivariate logistic model was applied based on the variables in univariate analysis with statistical significance. The primary outcome and secondary outcome incidence in the three groups was compared by the long-rank test and expressed through Kaplan–Meier curves. P-values of < 0.05 were considered statistically significant. All statistical analyses were performed with SAS, version 9.2 (SAS Institute, Cary, NC, USA).
Results
Baseline characteristics of the study population
The low BMI group in the present study included old-aged patients with underlying diseases, such as CKD, prior history of congestive heart failure (CHF), cerebrovascular disease, and atrial fibrillation or flutter. The high BMI group had more CV risk factors, such as dyslipidemia, family history of coronary artery disease (CAD), HTN, and current smoking. There were no statistical differences among the groups in the presence of DM and past PCI treatment or prior MI history among the groups (Table 1). The location and number of lesions and TIMI grade, were not significantly different (Table 2).
Clinical outcomes of the study population
At 1 year of follow-up, the incidence of MACCE were higher in low BMI group than high BMI group comparing to group 3 (group 1; 266 [10.1%] vs group 2; 348 [6.5%], P < 0.001) and the results were continued up to 3 years of follow-up (MACCE;aHR 1.230, [1.030–1.469], P = 0.022, CD;aHR 1.583, [1.215–2.062]). In the lower BMI group, the greater increase in MACCE and CD incidence at 3 years of follow-up was identified, which showed incremental effects on MACCE and CD with time according to the BMI. At 1 year of follow-up, in multivariate regression analysis, low BMI behaved as a risk factor related to the incidence of MACCE, CD, AD, and minor bleeding (MACCE; group 1 aHR = 1.274 [1.014–1.601], P = 0.038; Table 3). CD and AD played a major role in the meaningful results among the groups (aHR = 1.518 [1.107–2.081], P = 0.010, aHR = 1.543, [1.184–2.011], P = 0.001; Table 3). Other components, such as the incidence of MI, TVR, CVA, and new-onset HF and ST, were not statistically significantly different among the three groups. The incidence of ST and minor bleeding events was higher in the lower BMI group (ST: aHR = 4.177 [1.095–15.940], P = 0.036; minor bleeding: aHR = 1.784, [1.259–2.528, P = 0.001], but the difference was not statistically significant at 3 years of follow-up (Table 3). The probability of MACCE-free survival was shown on Kaplan–Meier curves. The low BMI group was more susceptible to MACCE than the high BMI group.However, the probability between groups 4 and 5 was not significantly different (Fig. 2A–D).
Predictors of overall mortality
Univariable and multivariable logistic regression analyses were conducted to evaluate the independent predictive factors influencing the primary outcome. Killip classification, DM, HTN, smoking history, CKD, cerebrovascular disease, atrial fibrillation, the use of beta blockers, ACE or ARB inhibitors, and statins, age, Hb, hsCRP, LVED, and stent diameter were identified as the independent predictors of the primary outcome (Table 4).
Subgroup analysis
The positive effect of high BMI on the primary outcome was maintained in subgroup analysis regardless of the independent predictive factors, except DM. When stratified by DM, patients with low BMI without DM had statistically higher risks of MACCE incidence (HR = 2.544 [2.035–3.181], P = 0.026) than those with DM (HR = 1.594, [1.235–2.057], P = 0.026). A marginal interaction with dyslipidemia was seen (P = 0.063 for interaction) (Fig. 3).
Discussion
Our previous study showed lower all-cause death and cardiac death high BMI group during 1 year of follow-up10. Analyzing MACCE as the primary outcome and additional meaningful implications were possible using the detailed information included in the KAMIR registry. First, group 1 showed a higher incidence of MACCE than group 3 at 1 year of follow-up, and it was maintained at 3 years of follow-up. Group 2 also showed poor prognosis in the primary outcome at 3 years of follow-up, although the difference was not statistically significant at 1 year of follow-up. The better clinical outcome in the higher BMI groups and the discrepancy of the results according to the follow-up period in group 2 might be attributed to differences in the incidence of CD. (Table 3) The tendency toward increases in the absolute number of MACCE events over time also showed a positive relationship with CD occurrence. High BMI could be considered a protective factor in the occurrence of CD and MACCE because the results remained after adjustment for other confounding factors. Second, higher BMI had a positive effect on the incidence of AD with statistical significance (417 in group 1, 430 in group 2, and 120 in group 3) than that of our previous study (262 in group 1, 261 in group 2, 77 in group 3)10. Third, at 1 year of follow-up, the incidence of ST was significantly higher in group 1 than in group 3, but not at 3 years of follow-up. A prior study identified several risk factors related to the incidence of ST16. Statistically significant differences in the baseline characteristics among the groups, such as CKD and heart failure, might have affected ST incidence even after further adjustment. Also, in older people, especially those ≥ 65 years of age, medication compliance could be decreased due to concerns related to adverse reactions with antiplatelet agents17. Compliance with medication-taking might have been poor in group 1 because it was the oldest age (group 1, 69.1 ± 11.7 years; group 2, 63.0 ± 11.6 years; and group 3, 58.1 ± 12.4 years, P < 0.001). Clopidogrel was prescribed more often than ticagrelor or prasugrel in group 1 and vice versa in the case of groups 2 and 3. Different drug potencies could be one reason for the differences during 1 year of follow-up because taking DAPT for 1 year after PCI is generally recommended11. The incidence of new-onset HF was higher in group 1 than in group 3, and the proportion of prescription medications was higher in group 3 than in group 1. Therefore, it is necessary to closely monitor cardiac function and prescribe appropriate medications to improve cardiac function and long-term prognosis. The incidence of MI, TVR, and CVA was not significantly different among the BMI groups, perhaps due to the small number of cases. Finally, more minor bleeding events occurred in group 1 than in group 3 at both 1 and 3 years of follow-up. The characteristics of the patients in group 1, including low body weight, old age (≥ 65 years), and underlying disease, could predispose them to bleeding events (Table 1).
In subgroup analysis, poor clinical outcomes were identified in the low BMI groups. In particular, low BMI had worse effects on the clinical outcomes in patients without DM than with DM (Fig. 3). It is possible that the accumulation of central fat in DM patients offsets the positive effects of a high BMI18,19. Also, considering that the HbA1C levels were lowest in group 1, there might be few DM patients with low BMIs, and the different number of DM patients between the low and high BMI groups might have influenced the HRs. In addition, the primary outcomes in groups 4 and 5 were not statistically significantly different because the number of patients classified into these groups was insufficient to demonstrate statistically significant results.
The positive effect on clinical outcomes in the high BMI groups could be explained by several theories. First, it is possible that patients classified into the low BMI groups had unhealthy metabolic status with cachexic status. Second, as mentioned above, patients in the high BMI group had a tendency to be actively prescribed medication. The regular prescription of medications and appropriate post-PCI monitoring might have had positive effects on their long-term clinical prognosis.
The study had several limitations. First, it inevitably had the limitations of a nonrandomized retrospective study. Second, it is questionable whether BMI can adequately reflect metabolic status. In previous studies, obesity was divided into metabolically “healthy” and “unhealthy” groups. Total body fat accumulation, especially abdominal fat related to metabolic syndrome, was an important factor in the clinical prognosis20. Because the registry of the study did not include information on peripheral fat deposition, it could act as a confounding factor. However, despite the limitation, the effect of BMI on the primary outcome could have clinical implications, as several other studies reported a positive correlation between BMI and abdominal circumference21,22. An additional limitation is that the proportion of Asian patients with extreme obesity was too small to conclude statistically significant outcomes. Based on the Korea-NIH data, only 0.89% of the general population was classified as having class III obesity23. This is why large-scale studies, including other Asian countries besides Korea, are needed in the future. In spite of these limitations, the study has clinically significant implications. First, it was a large-scale study in Asians and it showed 3-year long-term clinical outcomes. Second, the study demonstrated meaningful results in that the study assessed clinical outcomes, which included not only all-cause mortality and cardiovascular events but also cerebrovascular events and various clinical events such as minor bleeding and stent thrombosis. Additionally, we demonstrated independent predictors of overall mortality and evaluated whether the effect of BMI on clinical outcomes was influenced by the independent predictors.
Conclusion
The present large-scale study showed a lower incidence of MACCE in the high BMI group of Asians during the 3-year follow-up period compared to the low BMI group. In conclusion, a high BMI had a protective effect on long-term clinical outcomes in patients with AMI undergoing PCI, and strict monitoring might be essential for low BMI groups.
Data availability
The present study analyzed the KAMIR-NIH data in South Korea. The data are accessible to any researchers after permission of the Disease Control and Prevention and the Korea Health Technology R & D Project, Ministry of Health & Welfare (NIH URL http://icreat.nih.go.kr).
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Acknowledgements
Korean Acute Myocardial Infarction Registry National Institutes of Health (KAMIR-NIH). Investigators: Myung Ho Jeong, Young Keun Ahn, Sung Chull Chae, Kiyuk Chang, Tae Hoon Ahn, Seung Woon Rha, Hyo-Soo Kim, Hyeon Cheol Gwon, In Whan Seong, Kyung Kuk Hwang, Kwon-Bae Kim, Kwang Soo Cha, Seok Kyu Oh, Jei Keon Chae.
Funding
The funding was supported by Research of Korea Centers for Disease Control and Prevention and the Korea Health Technology R & D Project, Ministry of Health & Welfare, 2016-ER6304-01.
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S.Y.P.: Formal analysis, Writing of the manuscript, Review of the manuscript investigation, D.W.K.: Formal analysis, Review of the manuscript, Investigation, L.K.S.: Methodology, P.M.W.: Supervision, M.H.J.: Conceptualization, Investigation, Project administration, Funding acquisition, Resources, K.Y.C.: Supervision, Y.K.A., S.C.C., W.S.C., T.H.A., S.W.R., H.S.K., H.C.G., I.W.S., K.K.H., K.B.K., K.S.C., S.K.O., J.K.C.: Investigation.
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Park, S., Kim, DW., Lee, K. et al. Association between body mass index and three-year outcome of acute myocardial infarction. Sci Rep 14, 365 (2024). https://doi.org/10.1038/s41598-023-43493-0
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DOI: https://doi.org/10.1038/s41598-023-43493-0
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