Abstract
Background
ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of morbidity and mortality in developed countries. Therefore, understanding the prevalence and trends of major risk factors may facilitate primary and secondary prevention of STEMI.
Methods
In the present study, 2446 consecutive patients with STEMI admitted to Far Eastern Memorial Hospital from 2005 to 2016 were enrolled. A comprehensive analysis of the prevalence, distribution, and trends over time of major risk factors as well as Framingham risk scores of all patients was performed.
Results
The most prevalent risk factors were male sex, hypertension (HTN), smoking, age, dyslipidemia, and diabetes mellitus. Furthermore, 95%-97% of the patients had at least one modifiable risk factor, and < 1% of the patients did not have any identifiable risk factors. The prevalence trends of smoking, HTN, dyslipidemia, and metabolic syndrome increased significantly from 2005 to 2016. Seasonal variation analysis revealed a 15% increase in STEMI cases between January and March compared with those between April and December. Isolated low high- density lipoprotein-cholesterol syndrome was the second most common type of dyslipidemia, with a prevalence rate of 16.6%. Moreover, only 56.8% of the male and 32% of the female patients were in the Framingham high-risk group.
Conclusions
A high prevalence rate and an increasing trend of modifiable risk factors resulted in a high number of STEMI cases at our hospital. Controlling modifiable risk factors and improving nontraditional risk factor detection could facilitate primary and secondary preventions for STEMI.
Keywords: Acute coronary syndrome registry, Far Eastern Memorial Hospital, Isolated low high-density lipoprotein syndrome, Major risk factors, ST-segment elevation myocardial infarction
INTRODUCTION
ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of morbidity and mortality in developed countries.1 However, most studies on STEMI in Taiwan have exclusively reported the prevalence of major risk factors in the study population without analyzing all aspects.2-5 Therefore, the aim of the present study was to comprehensively analyze these risk factors, including the prevalence and trends of the clinical, demographic, and biochemical characteristics of patients with STEMI.
MATERIAL AND METHODS
We analyzed the data of 2446 consecutive patients with STEMI from the Far Eastern Memorial Hospital (FEMH)-Acute Coronary Syndrome (ACS) registry from 2005 to 2016. The clinical, demographic, and biochemical characteristics of the patients were recorded at initial presentation. The distribution and trends over time of major risk factors such as age, sex, smoking, body mass index (BMI), hypertension (HTN), a history of diabetes mellitus (DM), and a history of dyslipidemia were analyzed. STEMI at a young age was defined as STEMI in men and women aged < 45 and < 50 years, respectively. Obesity, overweight, normal weight, and underweight were defined as BMI > 27, 24-27, 18.5-24, and < 18.5 kg/m2, respectively.
Seasonal variations and distribution by month of the occurrence of STEMI were analyzed using data only from 2005 to 2015, as data from 2016 were not completely collected.
Framingham risk scores (FRSs) of all patients were calculated according to the formula published in the Framingham study (2008 version 3),6 with an assumption of a systolic blood pressure of 130-140 mmHg. Framingham high-, moderate-, and low-risk groups were defined as patients having a possibility of coronary artery disease in 10 years of > 20%, 10%-20%, and < 10%, respectively. Lipid profiles were classified as hypercholesterolemia [cholesterol total (Cho-T) > 200 mg/dL or low-density lipoprotein-cholesterol (LDL-C) > 130 mg/dL and triglyceride (TG) < 200 mg/dL], hypertriglyceridemia (Cho-T < 200 mg/dl, LDL-C < 130 mg/dl, and TG > 200 mg/dL), mixed dyslipidemia (Cho-T > 200 mg/dL or LDL-C > 130 mg/dL and TG > 200 mg/dL), isolated low high-density lipoprotein-cholesterol (HDL-C) syndrome (Cho-T < 200 mg/dL, LDL-C < 130 mg/dL, TG < 200 mg/dL, and HDL-C < 35 mg/dL in men and < 45 mg/dL in women), and normal. Because of the unavailability of abdominal circumference data, modified criteria based on the international Diabetes Federation consensus worldwide definition7 were used to define metabolic syndrome if at least three of the following five criteria were met: DM, HTN, BMI > 27 (which was used as a substitute for abdominal circumference), TG > 150 mg/dL, and HDL-C < 40 mg/dL for men and < 50 mg/dL for women.
Statistical analysis
Parameters are represented as means, medians, and standard deviations for continuous data and counts or percentages for categorical data. One-way analysis of variance was performed to examine the trends of means, and the Cochran-Armitage test was used to analyze the trends of categorical variables. The Cochran-Armitage test for trend is used in categorical data analysis when the aim is to assess the presence of an association between a variable with two categories and a variable with k categories. It is a method of directing the chi-squared test toward narrow alternatives. The test is sensitive to linearity between responsive variables and experimental variables, and can detect trends that would not be noticed by more crude methods.8 Trend analysis was performed using SPSS (IBM Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0. Armonk, NY). All significance tests were two-sided, and p < 0.05 was considered to be statistically significant.
RESULTS
Table 1 shows the baseline characteristics of the patients. The mean age of the overall patient population was 58.98 ± 13.22 years. The most prevalent major risk factors were male sex (N = 2032, 83%), HTN (N = 1681, 68%), smoking (N = 1491, 61%), overweight and obesity (BMI > 25, N = 1117, 49%), dyslipidemia (N = 1165, 47%), and DM (N = 734, 30%). Only 13% of the overall population had been diagnosed with coronary artery disease (CAD) before STEMI presentation. Men aged 50-60 years (N = 702, 34%) and women aged 70-80 years (N = 115, 28%) comprised the highest proportions of the male and female patients, respectively (Figure 1).
Table 1. Baseline characteristics of the patients enrolled in the registry.
| Variables | Mean (SD), N (%) |
| Risk factors | |
| Age, years | 58.98 (13.22) |
| Gender, male | 2032 (83.07%) |
| BMI | 25.42 (3.87) |
| Smoking | 1491 (61.06%) |
| Hypertension | 1681 (68.81%) |
| Dyslipidemia | 1165 (47.67%) |
| Diabetes mellitus | 734 (30.03%) |
| Known CAD history | 319 (13.05%) |
| Creatinine, mg/dl | 1.26 (1.33) |
| cho-T, mg/dl | 181.25 (58.90) |
| TG, mg/dl | 135.78 (132.38) |
| HDL-C, mg/dl | 43.15 (13.47) |
| LDL-C, mg/dl | 118.35 (42.10) |
| Uric acid, mg/dl | 6.67 (3.26) |
| Family history | |
| AMI and CAD | 136 (5.57%) |
AMI, acute myocardial infarction; BMI, body mass index; CAD, coronary artery disease; Cho-T, cholesterol total; HDL, high-density lipoprotein; LDL, low-density lipoprotein; SD, standard deviation; TG, triglyceride.
Figure 1.
Age distribution over time. Distribution of men (blue) and women (red) with ST-segment elevation myocardial infarction (STEMI) in the Far Eastern Memorial Hospital -Acute Coronary Syndrome (FEMH-ACS) registry. Men aged 50-59 years and women aged 70-79 years comprised the highest proportions of male and female patients, respectively.
Obese and overweight patients comprised 30% and 31% (N = 753 and 775, respectively) of the total study population. The male and female patients had a peak BMI of 24 kg/m2. Only a small proportion (N = 70, 2.86%) of the study population was underweight (Table 2 and Figure 2).
Table 2. Body mass index distribution.
| BMI distribution | N (%) |
| ≥ 27 | 753 (30.78%) |
| 24-27 | 775 (31.68%) |
| 18.5-24 | 778 (31.81%) |
| < 18.5 | 70 (2.86%) |
| NA | 70 (2.86%) |
BMI, body mass index; NA, not available.
Figure 2.
Body mass index (BMI) distribution. Male and female patients had a peak BMI of 24.
Dyslipidemia, including hypercholesterolemia, hypertriglyceridemia, and mixed dyslipidemia, was observed in 44% of the overall study population, and most patients (30.7%) had hypercholesterolemia. The prevalence of isolated low HDL-C syndrome, which has been rarely described in previous Taiwanese or Asian studies, was observed in approximately 16% of the overall study population (Table 3).
Table 3. Lipid profile distribution.
| Lipid profile analysis | N (%) |
| Hypercholesterolemia (Cho-T ≥ 200 mg/dl or LDL-C > 130 mg/dl, TG < 200 mg/dl) | 751 (30.70%) |
| Hypertriglyceridemia (Cho-T < 200 mg/dl and LDL-C < 130 mg/dl, TG > 200 mg/dl) | 143 (5.85%) |
| Mixed type (High Cho-T ≥ 200 mg/dl and High TG > 200 mg/dl) | 210 (8.59%) |
| Isolated low HDL (Cho-T < 200 mg/dl, TG < 200 mg/dl, HDL-C < 35 mg/dl in male, HDL-C < 45 mg/dl in female) | 408 (16.68%) |
| Normal lipid profile | 816 (33.36%) |
Cho-T, cholesterol total; HDL-C, high-density-lipoprotein cholesterol; LDL-C, low-density-lipoprotein cholesterol; TG, triglyceride.
With regards to the Framingham risk groups, 56.8%, 27%, and 15% of the high-, moderate-, and low-risk groups of patients were male, compared to 32%, 47%, and 19% female patients, respectively. In addition, 97% of the male and 95.4% of the female patients had modifiable risk factors, whereas only 2.6% of the male and 3.62% of the female patients had non-modifiable risk factors. Very few male (0.34%) and female (0.97%) patients did not have any identifiable risk factors (Table 4).
Table 4. Estimated Framingham risk score of all patients.
| FRS risk score | Male (N, %) | Female (N, %) |
| High CVD risk | ||
| With MRF | 1139 (56.05%) | 134 (32.37%) |
| With NRF | 17 (0.84%) | 0 (0.00%) |
| Moderate CVD risk | ||
| With MRF | 538 (26.48%) | 191 (46.14%) |
| With NRF | 25 (1.23%) | 7 (1.69%) |
| Low CVD risk | ||
| With MRF | 295 (14.52%) | 70 (16.91%) |
| With NRF | 11 (0.54%) | 8 (1.93%) |
| Without any risk factors | 7 (0.34%) | 4 (0.97%) |
| Total | ||
| With MRF | 1972 (97.05%) | 395 (95.41%) |
| With NRF | 53 (2.61%) | 15 (3.62%) |
| Without any risk factors | 7 (0.34%) | 4 (0.97%) |
CVD, cardiovascular disease; MRF, modifiable risk factors; NRF, non-modifiable risk factors.
Seasonal variations and distribution by month of the occurrence of STEMI are shown in Figure 3. There were more STEMI events from January to March. The number of STEMI cases increased by an average 16% per month during January-March (N = 602, 200/month) compared to April-December (N = 1549, 172/month) (Figure 3).
Figure 3.
Seasonal variation and distribution by month of ST-segment elevation myocardial infarction (STEMI) during 2005-2015. X-axis, month; Y-axis, number of cases. The average number per month of STEMI cases during January and March (200/month) increased 16% compared to that during April and December (172/month).
Table 5 shows the trends over time of major risk factors, including mean age and BMI, the prevalence of smoking, HTN, DM, dyslipidemia, and metabolic syndrome, and the proportion of STEMI at a young age. The trends over time of mean age and BMI and the prevalence of DM and STEMI at a young age were not significant. However, the prevalence of smoking, HTN, dyslipidemia, and metabolic syndrome increased significantly.
Table 5. Trends over time of the major risk factors.
| Year | Age | BMI | Smoking | HTN | DM | Dyslipidemia | AMI at young age | Metabolic syndrome | Total patients’ number each year |
| Mean (SD) | N (%) | ||||||||
| 2005 | 59.77 (13.28) | 24.99 (3.45) | 80 (57.14%) | 78 (55.71%) | 56 (40.00%) | 48 (34.29%) | 17 (12.06%) | 43 (30.50%) | 140 |
| 2006 | 59.32 (13.24) | 25.20 (3.82) | 109 (55.33%) | 108 (54.82%) | 52 (26.40%) | 53 (26.90%) | 30 (15.23%) | 44 (22.34%) | 197 |
| 2007 | 60.06 (13.35) | 24.97 (3.94) | 106 (58.56%) | 83 (45.86%) | 55 (30.39%) | 27 (14.92%) | 22 (12.15%) | 34 (18.78%) | 181 |
| 2008 | 59.08 (14.02) | 25.02 (3.58) | 108 (57.14%) | 111 (58.73%) | 54 (28.42%) | 37 (19.47%) | 22 (11.52%) | 54 (28.27%) | 189 |
| 2009 | 58.97 (13.89) | 25.50 (4.09) | 110 (61.45%) | 101 (56.11%) | 51 (28.33%) | 27 (15.00%) | 26 (14.44%) | 53 (29.44%) | 179 |
| 2010 | 59.22 (13.12) | 25.48 (3.97) | 114 (61.62%) | 109 (58.92%) | 52 (28.11%) | 51 (27.57%) | 24 (12.97%) | 57 (30.81%) | 185 |
| 2011 | 58.62 (12.94) | 25.35 (3.77) | 129 (56.83%) | 130 (57.27%) | 65 (28.63%) | 47 (20.70%) | 34 (14.98%) | 67 (29.52%) | 227 |
| 2012 | 58.01 (12.91) | 25.52 (4.07) | 129 (55.84%) | 164 (71.00%) | 66 (28.57%) | 77 (33.33%) | 38 (16.45%) | 81 (35.06%) | 231 |
| 2013 | 58.98 (13.18) | 25.36 (3.52) | 140 (64.52%) | 190 (87.56%) | 71 (32.72%) | 148 (68.20%) | 34 (15.67%) | 75 (34.56%) | 217 |
| 2014 | 58.40 (13.70) | 26.13 (4.14) | 139 (67.48%) | 192 (93.20%) | 56 (27.18%) | 193 (93.69%) | 35 (16.99%) | 90 (43.69%) | 206 |
| 2015 | 58.65 (12.47) | 25.83 (3.70) | 128 (65.64%) | 171 (87.69%) | 60 (30.77%) | 188 (96.41%) | 25 (12.82%) | 68 (34.87%) | 195 |
| 2016 | 58.83 (13.03) | 25.54 (3.73) | 193 (68.68%) | 235 (83.63%) | 88 (31.32%) | 266 (94.66%) | 40 (14.23%) | 108 (38.43%) | 281 |
| p-value | 0.975 | 0.132 | < 0.001 | < 0.001 | 0.822 | < 0.001 | 0.325 | < 0.001 |
AMI, acute myocardial infarction; BMI, body mass index; DM, diabetes mellitus; HTN, hypertension; SD, standard deviation.
DISCUSSION
FEMH is located in New Taipei City and is a high volume center for percutaneous coronary interventions for ACS in Taiwan. The FEMH-ACS registry data comprises a significant portion of the Taiwan ACS full spectrum registry.2,3 Compared with this registry, the FEMH-ACS registry had a higher prevalence of smoking (50.57% vs. 61%), HTN (56.3% vs. 68.8%), and dyslipidemia (33.1% vs. 47.67%). Moreover, during the last 4 years, the prevalence of smoking, HTN, dyslipidemia, and metabolic syndrome in our study increased significantly, particularly HTN and dyslipidemia. This increased prevalence may be partially associated with the definition of HTN and dyslipidemia and how they were reported in this study. The substantially increased influence of multiple modifiable risk factors may explain why FEMH is a high volume center for ACS in Taiwan.
In this study, 95% of the patients with STEMI had at least one major risk factor, and the overall prevalence rate of this study was high compared to reports from other international studies.9-12 A few patients, most of whom were young and female,4,13 did not have any identifiable risk factors. Therefore, nontraditional risk factors and biomarkers such as inflammation, oxidative stress, and endothelial dysfunction markers or environmental pollutants, should be evaluated for secondary screening of such patients to improve therapeutic efficacy and predict specific groups that are likely to benefit from targeted interventions.14-18
Seasonal variations with a higher incidence of myocardial infarction in the winter have been reported, however the results for STEMI have been conflicting.19-21 Similar to most previous studies, our study demonstrated a higher incidence of STEMI in winter than in other seasons.
Substantial evidence has proven that low HDL-C levels are associated with an increased possibility of ACS.22,23 The causes of low HDL-C are multi-factorial and include DM, hypertriglyceridemia, smoking, sedentary lifestyle, lack of exercise, obesity, a poor diet lacking unsaturated fatty acids, genetic factors and treatment with statins. However, because drug-induced HDL elevation does not provide any cardiovascular benefits,24-26 isolated low HDL-C syndrome has received less attention, particularly compared with other types of dyslipidemia, and has been frequently less emphasized in clinical practice. In addition, Taiwanese studies have yet to address this syndrome. However, one study on Asia-Pacific populations suggested that this syndrome may be more prevalent (up to 22.4%) in Asian populations.27-29 In our study, the prevalence of isolated low HDL-C syndrome was approximately 16.7%, which was second only to that of pure hypercholesterolemia and almost three times that of pure hypertriglyceridemia.30,31 We were unable to explain the exact causes of the high prevalence rate of isolated low HDL-C syndrome in our population because all of the causes mentioned above were possible. Therefore, we suggest that this syndrome warrants further exploration. Furthermore, low HDL-C levels can be improved by exercise and polyunsaturated fatty acid-containing diets.32-34 Regarding primary or secondary prevention of STEMI, interventions for HDL-C elevation are a future direction to minimize the risk of CAD.
Several studies have investigated the predictive accuracy or prediction power of the FRS.35,36 In our study, 57% of the male patients with STEMI were classified in the high-risk group, compared to 43% in the moderate- and low-risk groups. Of the female patients with STEMI, only 34% were classified in the high-risk group, compared to 66% in the moderate- and low-risk groups. This finding may be because female patients tend to have a lower FRS according to the current formula, and because different pathophysiologic mechanisms such as chronic inflammation and microvascular dysfunction are not considered in the FRS.37,38 To precisely predict the high risk of STEMI, a new scoring system encompassing other risk factors such as inflammation, oxidative stress, and endothelial dysfunction markers is required.
Study limitations
There are some limitations to the present study. First, this study used a database from a single center. Second, only patients who were successfully admitted to the hospital were enrolled in this registry, and patients who died at the emergency department were not enrolled. Third, some major risk factors such as HTN and the presence of dyslipidemia were not precisely recorded. Moreover, lipid profile can be influenced by medication, but medication histories before the onset of STEMI were usually not available. During the early years of this registry, HTN and dyslipidemia may have been under-diagnosed due to the patients being unaware of their condition. However, during the latter years of this registry, the extremely high prevalence of these two risk factors may have been due to loose criteria being applied by the physicians. Therefore, the trends over time of these two factors could have been influenced.
CONCLUSIONS
We comprehensively analyzed the prevalence and trends of current major risk factors. Most patients with STEMI had at least one modifiable risk factor and did not have a history of CAD. The prevalence of multiple modifiable risk factors, including smoking, HTN, dyslipidemia, and metabolic syndrome, has increased significantly in recent years. However, a considerable number of patients did not have a high FRS according to the current FRS formula. Furthermore, we reported the prevalence of isolated low HDL-C syndrome in patients with STEMI in Taiwan. To facilitate primary or secondary preventions of STEMI, several measures can be adopted, including improvements in lifestyle and dietary habits, the promotion of exercise, and the evaluation of nontraditional risk factors such as chronic inflammation, endothelial dysfunction, and oxidative stress markers.
Acknowledgments
The current study was accepted as a poster presentation in the Annual Convention & Scientific Session of the Taiwan Society of Cardiology (TSOC 2017). We acknowledge Wallace Academic Editing for editing this manuscript.
DECLARATION OF CONFLICT OF INTERESTS
All the authors declare that they have no conflict of interest. And this research received no grant from any funding agency in the public, commercial or not-for-profit sectors.
REFERENCES
- 1.Mozaffarian D, Benjamin EJ, Go AS, et al. Heart disease and stroke statistics--2016 update: a report from the American Heart Association. Circulation. 2016;133:e38–360. doi: 10.1161/CIR.0000000000000350. [DOI] [PubMed] [Google Scholar]
- 2.Shyu KG, Wu CJ, Mar GY, et al. Clinical characteristics, management and in-hospital outcomes of patients with acute coronary syndrome – observations from the Taiwan ACS Full Spectrum Registry. Acta Cardiol Sin. 2011;27:135–144. [Google Scholar]
- 3.Chiang FT, Shyu KG, Wu CJ, et al. Predictors of 1-year outcomes in the Taiwan Acute Coronary Syndrome Full Spectrum Registry. J Formos Med Assoc. 2014;113:794–802. doi: 10.1016/j.jfma.2013.08.001. [DOI] [PubMed] [Google Scholar]
- 4.Tsai WC, Wu KY, Lin GM, et al. Clinical charateristics of patients less than forty years old with coronary artery disease in Taiwan: a cross-sectional study. Acta Cardiol Sin. 2017;33:233–240. doi: 10.6515/ACS20161026A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Li YH, Chiu YW, Cheng JJ, et al. Changing practice pattern of acute coronary syndromes in Taiwan from 2008 to 2015. Acta Cardiol Sin. 2019;35:1–10. doi: 10.6515/ACS.201901_35(1).20180716B. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.D’Agostino RB, Vasan RS, Pencina MJ, et al. General cardiovascular risk profile for use in primary care. The Framingham Heart Study. Circulation. 2008;117:743–753. doi: 10.1161/CIRCULATIONAHA.107.699579. [DOI] [PubMed] [Google Scholar]
- 7.Alberti KGMM, Zimmet P, Shaw J. The International Diabetes Federation consensus worldwide definition of metabolic syndrome. https://www.idf.org/e-library/consensus-statements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome.html [Google Scholar]
- 8.Alan A. Categorical Data Analysis (second edition) Wiley, ISBN 0-471-36093-7; 2002. [Google Scholar]
- 9.Khot UN, Khot MB, Bajzer CT, et al. Prevalence of conventional risk factors in patients with coronary heart disease. JAMA. 2003;290:898–904. doi: 10.1001/jama.290.7.898. [DOI] [PubMed] [Google Scholar]
- 10.Pesek K, Pesek T, Rados M, et al. The prevalence of cardiovascular risk factors in patients from Croatian Zagorje County treated at Department of Medicine, Zabok General Hospital from 2000-2006. Coll Antrpol. 2007;31:709–715. [PubMed] [Google Scholar]
- 11.Veeranna V, Pradhan J, Niraj A, et al. Traditional cardiovascular risk factors and severity of angiographic coronary artery disease in the elderly. Prev Cardiol. 2010;13:135–140. doi: 10.1111/j.1751-7141.2009.00062.x. [DOI] [PubMed] [Google Scholar]
- 12.González-Pacheco H, Vargas-Barron J, Vallejo M, et al. Prevalence of conventional risk factors and lipid profiles in patients with acute coronary syndrome and significant coronary disease. Ther Clin Risk Manag. 2014;10:815–823. doi: 10.2147/TCRM.S67945. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Qian G, Zhou Y, Liu HB, et al. Clinical profile and long-term prognostic factors of a young Chinese han population (≤ 40 years) having ST-segment elevation myocardial infarction. Acta Cardiol Sin. 2015;31:390–397. doi: 10.6515/ACS20140929D. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Lin Hj, Wang TD. Profilling the evolution of inflammatory response and exploring its prognostic significance in acute myocardial infarction: the first step to establishing anti-inflammatory strategy. Acta Cardiol Sin. 2017;33:486–488. doi: 10.6515/ACS20170731A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Balagopal PB, de Ferranti SD, Cook S, et al. Nontraditional risk factors and biomarkers for cardiovascular disease: mechanistic, research, and clinical considerations for youth-a scientific statement from the American Heart Association. Circulation. 2011;123:2749–2769. doi: 10.1161/CIR.0b013e31821c7c64. [DOI] [PubMed] [Google Scholar]
- 16.Ford ES, Li C, Zhao G, et al. Trends in the prevalence of low risk factor burden for cardiovascular disease among United States adults. Circulation. 2009;120:1181–1188. doi: 10.1161/CIRCULATIONAHA.108.835728. [DOI] [PubMed] [Google Scholar]
- 17.Chen WQ, Shao DH, Gu HY, et al. Has-mir-499 rs 3746444 T/C polymorphism is associated with increased risk of coronary artery disease in a Chinese population. Acta Cardiol Sin. 2017;33:34–40. doi: 10.6515/ACS20160303A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Doganay B, Okutucu S, Cetin M, et al. Association of serum copeptin levels with patency of infarct-related arteries in patients with ST-segment elevation myocardial infarction. Acta Cardiol Sin. 2019;35:360–368. doi: 10.6515/ACS.201907_35(4).20181101A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Swampillai J, Wijesinghe N, Sebastian C, Devlin GP. Seasonal variations in hospital admissions for ST-elevation myocardial infarction in New Zealand. Cardiol Res. 2012;3:205–208. doi: 10.4021/cr223e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Nagarajan V, Fonarow GC, Ju C, et al. Seasonal and circadian variations of acute myocardial infarctions: findings from the get with the guidelines-Coronary Artery Disease (GWTG-CAD) program. Am Heart J. 2017;189:85–93. doi: 10.1016/j.ahj.2017.04.002. [DOI] [PubMed] [Google Scholar]
- 21.Ornato JP, Peberdy MA, Chandra NC, Bush DE. Seasonal pattern of acute myocardial infarction in the national registry of myocardial infarction. J Am Coll Cardiol. 1996;28:1684–1688. doi: 10.1016/s0735-1097(96)00411-1. [DOI] [PubMed] [Google Scholar]
- 22.Bruckert E. Epidemiology of low HDL-cholesterol: results os studies and surveys. Eur Heart J Suppl. 2006;8 (suppl_F):F17–F22. [Google Scholar]
- 23.Huxley RR, Barzi F, Lam TH, et al. Isolated low levels of high-density lipoprotein cholesterol are associated with an increased risk of coronary heart disease-an individual participant data meta-analysis of 23 studies in the Asia-Pacific region. Circulation. 2011;124:2056–2064. doi: 10.1161/CIRCULATIONAHA.111.028373. [DOI] [PubMed] [Google Scholar]
- 24.Hourcade-Potelleret F, Laporte S, Lehnert V, et al. Clinical benefit from pharmacological elevation of high-density lipoprotein cholesterol: meta-regression analysis. Heart. 2015;101:847–853. doi: 10.1136/heartjnl-2014-306691. [DOI] [PubMed] [Google Scholar]
- 25.Meyers CD, Kashyap ML. Pharmacologic elevation of high-density lipoproteins: recent insights on mechanism of action and atherosclerosis protection. Curr Opin Cardiol. 2004;19:366–373. doi: 10.1097/01.hco.0000126582.27767.87. [DOI] [PubMed] [Google Scholar]
- 26.Wright RS. Recent clinical trials evaluating benefit of drugs therapy for modification of HDL cholesterol. Curr Opin Cardiol. 2013;28:389–398. doi: 10.1097/HCO.0b013e328362059d. [DOI] [PubMed] [Google Scholar]
- 27.Rutherford JN, McDade TW, Feranil A, et al. High prevalence of low HDL-c in the Philippines compared to the U.S.: population differences in associations with diet and BMI. Asia Pac J Clin Nutr. 2010;19:57. [PMC free article] [PubMed] [Google Scholar]
- 28.Frank ATH, Zhao B, Jose PO, et al. Racial/ethic differences in dyslipidemia patterns. Circulation. 2014;129:570–579. doi: 10.1161/CIRCULATIONAHA.113.005757. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Cheung BM, Li M, Ongk L, et al. High density lipoprotein-cholesterol levels increase with age in American women but not in Hong Kong Chinese women. Clin Endo Crinol (oxf) 2009;70:561–568. doi: 10.1111/j.1365-2265.2008.03361.x. [DOI] [PubMed] [Google Scholar]
- 30.Toth PP, Potter D, Ming EE. Prevalence of lipid abnormalities in United States: the National Health and Nutrition Examination Survey 2003-2006. J Clin Lipidol. 2012;6:325–330. doi: 10.1016/j.jacl.2012.05.002. [DOI] [PubMed] [Google Scholar]
- 31.Zhao WH, Zhang J, Zhai Y, et al. Blood lipid profile and prevalence of dyslipidemia in Chinese adults. Biomed Environ Sci. 2007;20:329–335. [PubMed] [Google Scholar]
- 32.Leon AS, Sanchez OA. Respond of blood lipids to exercise training alone or combined with dietary intervention. Med Sci Sports Exerc. 2001;33(6 suppl):S502–S515; discussion S528-9. doi: 10.1097/00005768-200106001-00021. [DOI] [PubMed] [Google Scholar]
- 33.Durstine JL, Grandjean PW, Davis PG, et al. Blood lipid and lipoprotein adaptations to exercise. Sports Med. 2001;31:1033. doi: 10.2165/00007256-200131150-00002. [DOI] [PubMed] [Google Scholar]
- 34.Tapsell LC, Gillen LJ, Patch CS, et al. Including walnuts in a low-fat/modified-fat diet improves HDL cholesterol-to-total cholesterol ratios in patients with type 2 diabetes. Diabetes Care. 2004;27:2777–2783. doi: 10.2337/diacare.27.12.2777. [DOI] [PubMed] [Google Scholar]
- 35.Brindle P, Emberson J, Lampe F, et al. Predictive accuracy of the Framingham coronary risk score in British men: prospective cohort study. BMJ. 2003;327:1267. doi: 10.1136/bmj.327.7426.1267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Mukete B, Eid S, Moran L, et al. Framingham risk score inadequately identifies patients at risk of a first ST elevation myocardial infarction. Internet J Cardiol. 2008;7 [Google Scholar]
- 37.Çağdaş M, Karakoyun S, Yesin M, et al. The association between monocyte HDL-C ratio and SYNTAX score and SYNTAX score II in STEMI patients treated with primary PCI. Acta Cardiol Sin. 2018;34:23–30. doi: 10.6515/ACS.201801_34(1).20170823A. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Diao J, Xie J, Feng J, et al. Study on connective tissue growth factor expressed in patients with ST-segment elevation myocardial infarction. Acta Cardiol Sin. 2019;35:355–359. doi: 10.6515/ACS.201907_35(4).20180922A. [DOI] [PMC free article] [PubMed] [Google Scholar]