Literature DB >> 26683970

Impact of Modifiable Cardiovascular Risk Factors on Mortality After Percutaneous Coronary Intervention: A Systematic Review and Meta-Analysis of 100 Studies.

Pravesh Kumar Bundhun1, Zi Jia Wu, Meng-Hua Chen.   

Abstract

Modifiable cardiovascular risk factors such as obesity, hypertension, dyslipidemia, smoking, diabetes mellitus, and metabolic syndrome can easily give rise to coronary heart disease (CHD). However, due to the existence of the so-called "obesity paradox" and "smoking paradox," the impact of these modifiable cardiovascular risk factors on mortality after percutaneous coronary intervention (PCI) is still not clear. Therefore, in order to solve this issue, we aim to compare mortality between patients with low and high modifiable cardiovascular risk factors after PCI. Medline and EMBASE were searched for studies related to these modifiable cardiovascular risk factors. Reported outcome was all-cause mortality after PCI. Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated, and the pooled analyses were performed with RevMan 5.3 software. A total of 100 studies consisting of 884,190 patients (330,068 and 514,122 with high and low cardiovascular risk factors respectively) have been included in this meta-analysis. Diabetes mellitus was associated with a significantly higher short and long-term mortality with RR 2.11; 95% CI: (1.91-2.33) and 1.85; 95% CI: (1.66-2.06), respectively, after PCI. A significantly higher long-term mortality in the hypertensive and metabolic syndrome patients with RR 1.45; 95% CI: (1.24-1.69) and RR 1.29; 95% CI: (1.11-1.51), respectively, has also been observed. However, an unexpectedly, significantly lower mortality risk was observed among the smokers and obese patients. Certain modifiable cardiovascular risk subgroups had a significantly higher impact on mortality after PCI. However, mortality among the obese patients and the smokers showed an unexpected paradox after coronary intervention.

Entities:  

Mesh:

Year:  2015        PMID: 26683970      PMCID: PMC5058942          DOI: 10.1097/MD.0000000000002313

Source DB:  PubMed          Journal:  Medicine (Baltimore)        ISSN: 0025-7974            Impact factor:   1.817


INTRODUCTION

Coronary heart disease, also known as coronary artery disease (CAD), is the most common type of heart disease in the elderly. Almost all over the world, it is the number 1 cause of death in both men and women. From the year 1990 to 2013, there has been a rise from 5.74 to 8.14 million deaths from CAD globally.[1] There are many risk factors associated with CAD. These risk factors include hypertension, dyslipidemia, smoking, obesity, old age, family history, diabetes mellitus (DM), and metabolic syndrome (MS).[2] These risk factors can still be subdivided into modifiable and nonmodifiable risk factors. Modifiable risk factors are those that can be changed; or simply, if careful precautions are taken, the risk for developing CAD will be lower in the susceptible population. For example, eating a healthy diet, doing regular exercises, avoiding smoking, and maintaining a healthy weight are all safety measures which can help to prevent CAD.[3,4] Except old age and a family history with cardiovascular disorders, factors such as a high body mass index (BMI), hypertension, dyslipidemia, smoking, DM, and MS are all considered as modifiable cardiovascular risk factors. Unfortunately, because of the unhealthy lifestyle adopted by people nowadays, they finally end up with conditions which expose them to a high risk for CAD. When symptoms become more severe, or intolerable, and when medications become ineffective, percutaneous coronary intervention (PCI) proves to be the most common invasive treatment in these patients.[5] However, due to the presence of the so-called phenomenon “obesity paradox” and “smoking paradox” whereby the mortality rate in the obese patients and smokers is unexpectedly lower compared to the normal weight patients and nonsmokers, respectively, the impact of these modifiable cardiovascular risk factors on mortality after PCI is still not clear. Therefore, in order to solve this issue, we aim to compare the short- and long-term mortality in patients with low and high modifiable cardiovascular risk factors after PCI.

METHODS

Data Sources and Search Strategy

Medline and EMBASE were searched for randomized controlled trials (RCTs) and observational studies by typing the words or phrases “X and percutaneous coronary intervention/PCI” whereby X was interchangeable with these modifiable cardiovascular risk factors such as smoking, overweight/obesity/high BMI, hypertension, hyperlipidemia/hypercholesterolemia/high-density lipoprotein (HDL)/low-density lipoprotein (LDL), DM, and MS. To further enhance this search, the term “angioplasty” has also been used to replace PCI and the words “smoking paradox” and “obesity paradox” have been used to replace smoking and obesity, respectively. No language restriction was applied.

Inclusion and Exclusion Criteria

Studies were included if: They were RCTs or observational studies relating these modifiable cardiovascular risk factors with PCI. They reported mortality among their clinical endpoints. They included data for both the experimental and the control groups. For example, DM and non-DM, smokers and nonsmokers, overweight/obese and nonobese/normal weight, MS and non-MS, hypertensive and normotensive patients, increased LDL and normal/low LDL, or decreased high density lipoprotein (HDL) and increased HDL. Studies were excluded if: They did not include these modifiable cardiovascular risk factors. They were meta-analyses, case studies, or letter to editors. No control group was present. Mortality was not among the reported endpoints. Duplicates.

Types of Participants

All the patients were >18 years old and suffered from CAD. Enrolled patients in the experimental group had at least 1 modifiable cardiovascular risk factor (diabetes, MS, high BMI, dyslipidemia, cigarette smoking, or hypertension) whereas those patients in the control group did not suffer from the risk factor being analyzed in the corresponding subgroups. All patients underwent PCI.

Definitions, Outcomes, and Follow-Up Periods

Modifiable Cardiovascular Risk Factors: defined as cardiovascular risk factors that can be controlled or if prevented, can result in a lower risk of suffering from CAD. In our studies, these patients were considered as high risk patients. Low risk patients, who acted as controls for this meta-analysis, were those without these modifiable cardiovascular risk factors. DM: defined as a fasting blood glucose (FBG) level of >7.0 mmol/L or an oral glucose tolerance test (OGTT) >11.1 mmol/L observed at least on 2 different occasions. Overweight and obese: BMI of >25 and >30 kg/m2, respectively. Hypertension: a blood pressure of >130/80 mmHg on at least 2 separate occasions. Dyslipidemia: defined as an LDL level of (>130 mg/dL) or an HDL level of (<40 mg/dL). A borderline value was already considered as dyslipidemia in this study. MS: a condition diagnosed if at least 3 of the followings were present: central obesity, high blood pressure, high fasting plasma glucose, high serum triglyceride, and low-high-density lipoproteins. Smoking: included current smokers and late nonsmokers. Quitters, former smokers, pre- and post-PCI smoking quitters have not been included in the study. In-hospital mortality: included all-cause deaths during the hospital stay (≤30 days). Short-term mortality: included all-cause deaths during a follow-up period from 30 days to 1 year after PCI. Long-term mortality: included all-cause deaths during a follow-up period at 1 year or more than 1 year after PCI.

Data Extraction and Quality Assessment

Two authors (PKB and ZW) independently reviewed the data and assessed the eligibility and methodological quality of each eligible study. Information and data regarding the number of patients and patient characteristics, associated risk factors, intervention strategies, and the clinical outcomes, and respective follow-up periods (in-hospital, short-term, and long-term) were systematically extracted. If any of the 2 authors disagreed about the information or data extracted, disagreements were discussed between the authors, and if the authors could not reach a final decision, disagreements were resolved by the 3rd author (MHC). The bias risk of trials was assessed with the components recommended by the Cochrane Collaboration.[6]

Methodological Quality and Statistical Analysis

Study selection, data collection, analysis, and reporting of the results were performed using the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Heterogeneity across trials was assessed using the Cochrane Q-statistic (P ≤ 0.05 was considered significant) and I2-statistic. I2 described the percentage of total variation across studies, that is, due to heterogeneity rather than chance. A value of 0% indicated no heterogeneity, and larger values indicated increased heterogeneity. If I2 was <50%, fixed effect model was used. However, if I2 was >50%, a random effect model was used. Publication bias was visually estimated by assessing funnel plots. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for categorical variables. The pooled analyses were performed with RevMan 5·3 software. Since this is a systematic review and meta-analysis, ethical approval was not required.

RESULTS

Selection of Studies for This Meta-Analysis

A total of 7456 articles were identified from search databases, and 32 articles were identified from references. After excluding the 1120 duplicates, 6030 articles were excluded by title and abstract since they were not related to our topic. Among the remaining articles, 79 were related to obesity, 142 to diabetes, 25 to MS, 36 to dyslipidemia, 29 to smoking, and 27 were related to hypertension. A total of 338 full text articles were assessed for eligibility. More articles were excluded since they were meta-analyses, case studies, data for the control group were not available, outcomes of interest were not reported and also dichotomous data which were very important for our statistical analysis were not provided. The flow diagram for the selection of studies has been represented in Figure 1.
FIGURE 1

Shows the flow diagram for the study selection.

Shows the flow diagram for the study selection. A total number of 100 articles from randomized controlled trials and observational studies have been included in this meta-analysis with a total number of 844,190 patients to be analyzed; among which, 330,068 patients were in the experimental group while 514,122 were in the control group. The total number of patients associated with the corresponding risk factors from this whole study have been given in Tables 1 and 2 shows the total number of patients in all the different subgroups (for both the experimental and control groups) as well as their follow-up periods.
TABLE 1

An Approximation∗ of the number of patients corresponding to these modifiable risk factors throughout this whole meta-analysis

TABLE 2

The Number of Patients in These Different Subgroups and the Corresponding Follow-Up Periods

An Approximation∗ of the number of patients corresponding to these modifiable risk factors throughout this whole meta-analysis The Number of Patients in These Different Subgroups and the Corresponding Follow-Up Periods The Number of Patients in These Different Subgroups and the Corresponding Follow-Up Periods Among these 330,068 patients analyzed in the experimental group, 76.2% had hypertension, 24% were smokers, 50.3% had dyslipidemia, 65.5% were overweight or obese, 1.5% had MS, and 47.6% had DM. Considering this whole study, pure data for only 27,415 (10.9%) hypertensive patients, 14,507 (18.3%) smokers, 15,008 (9.03%) patients with dyslipidemia, 215,834 (99.9%) patients with high BMI, 4741 (94.8%) patients with MS, and 52,563 (33.4%) patients with DM were available for subgroup analysis. Note that data which were not available in the original articles have been omitted. Table 2  has been divided into different subgroups of modifiable cardiovascular risk factors. Total number of patients in the experimental group, control group as well as the total number of patients in each study with their follow-up periods have been given in Table 2 . Five studies dealt with hypertension, 8 studies dealt with smoking, 6 studies dealt with dyslipidemia, 9 studies dealt with MS, 23 studies dealt with high BMI, and 51 studies dealt with DM. Two studies were common in both the hypertension and the diabetic groups since they analyzed both diabetic and hypertensive patients together. Follow-up periods were classified as in-hospital, short-term, and long-term follow-ups as mentioned in the “definition” section. The baseline characteristics of all the included studies have been represented in Table 3 .
TABLE 2 (Continued)

The Number of Patients in These Different Subgroups and the Corresponding Follow-Up Periods

Shows the Baseline Features of Each of the Included Studies Shows the Baseline Features of Each of the Included Studies Patients in the hypertensive group were older than the normotensive patients. There were more male patients in the control group compared to the experimental group. DM and dyslipidemia were more prominent among the hypertensive patients whereas cigarette smoking was more common in the control group. Majority of the smokers were males and they were younger than the nonsmokers. Apart from 1 study, hypertension was more prominent among the nonsmokers. Most of the nonsmokers suffered from DM too. Patients from both the experimental and the control groups were almost similar in age. If analyzed as a whole, there was no significant differences between genders, hypertension, and smoking between these 2 groups. However, except from 1 study, DM was more prominent among those with dyslipidemia. There was no significant difference in age between these 2 groups. Majority of those patients in the control group were males. Hypertension was more prominent in the experimental group. Smoking was almost similar in both groups. Except from 1 study which had no diabetic patients and 1 which had less patients with DM, DM was more common in the MS group. The overweight and obese patients were younger than the normal weight and underweight patients. There were more males than females in the experimental group. Hypertension, dyslipidemia, and DM were more prominent in the experimental group. Most of the patients in the high BMI category were nonsmokers. There was no significant difference in age between the diabetic and nondiabetic patients. Most of the patients in the control group were males. Hypertension and dyslipidemia were more prominent in the DM group. Most of the patients in the experimental group were nonsmokers.

Result of the Main Analysis

Results from this meta-analysis showed that during the in-hospital follow-up, mortality in the hypertensive and DM patients were significantly higher with RR 1.43; 95% CI: (1.05–1.94); P = 0.02 and RR 1.86; 95% CI: (1.68–2.06); P < 0.00001, respectively. The in-hospital mortality for the patients with dyslipidemia did not reach statistical significance RR 1.39; 95% CI: (0.32–5.94); P = 0.66. However, surprizingly, the in-hospital mortality significantly favored patients with high BMI with RR 0.61; 95% CI: (0.58–0.64); P < 0.00001. Short-term mortality was significantly higher in the DM group with RR 2.11; 95% CI: (1.91–2.33); P < 0.00001. The result was not significant in the hypertensive group with RR 1.40; 95% CI: (0.95–2.06); P = 0.09; dyslipidemia group with RR 0.91; 95% CI: (0.47–1.76); P = 0.77 and MS group with RR 1.05; 95% CI: (0.88–1.25); P = 0.61. Unexpectedly, the short-term mortality significantly favored the smokers and high BMI groups with RR 0.53; 95% CI: (0.45–0.62); P < 0.00001 and 0.67; 95% CI: (0.52–0.86); P = 0.002, respectively. Long-term mortality was significantly higher in the DM, hypertensive, and MS groups with RR 1.85; 95% CI: (1.66–2.06); P < 0.00001, 1.45, 95% CI: (1.24–1.69); P < 0.00001, and 1.29; 95% CI: (1.11–1.51); P = 0.0009, respectively. The result for dyslipidemia was still not significant. However, the long-term mortality still significantly favored the smokers and high BMI patients with RR 0.49; 95% CI: (0.39–0.63); P < 0.00001 and 0.64; 95% CI: (0.54–0.75), P < 0.00001, respectively. The mortality risks within these subgroups have been summarized in Table 4, and the detailed results for mortality among these different subgroups have been shown in Figures 2–7.
TABLE 3

Shows the Baseline Features of Each of the Included Studies

FIGURE 2

(A) Forest plot showing the in-hospital and long-term mortality risk in Hypertensive patients. (B) Forest plot showing the short-term mortality risk in hypertensive patients.

FIGURE 7

(A) Forest plot showing the in-hospital and short-term mortality in overweight and obese patients. (B) Forest plot showing the long-term mortality in overweight and obese patients.

Summarizes the Results of This Meta-Analysis (A) Forest plot showing the in-hospital and long-term mortality risk in Hypertensive patients. (B) Forest plot showing the short-term mortality risk in hypertensive patients. Forest plot showing the mortality in dyslipidemia patients. (A) Forest plot showing the in-hospital and short-term mortality in diabetic patients. (B) Forest plot showing the long-term mortality in diabetic patients. Forest plot showing the mortality in patients with metabolic syndrome. (A) Forest plot showing the short-term mortality in smokers. (B) Forest plot showing the long-term mortality in smokers. (A) Forest plot showing the in-hospital and short-term mortality in overweight and obese patients. (B) Forest plot showing the long-term mortality in overweight and obese patients. For all of the above analyses, sensitivity analyses yielded consistent results. Based on a visual inspection of the funnel plots, there has been no evidence of publication bias for the included studies that assessed the subgroup mortality risk. Figure 8 shows the corresponding funnel plots.
FIGURE 8

Funnel plots for the subgroup analysis.

Funnel plots for the subgroup analysis.

DISCUSSION

Among these 844,190 patients who participated in this meta-analysis, an unexpected result has been obtained in certain subgroups of patients. A significantly higher mortality risk has been observed among the DM patients. A significantly higher in-hospital and long-term mortality risks have also been observed among the hypertensive patients. Moreover, a significantly higher long-term mortality has been observed in patients with MS whereas an almost similar mortality rate has been observed in patients with and without dyslipidemia. However, smokers and those patients with high BMI had an unexpectedly lower short and long-term mortality risk compared to non-smokers and low-BMI/normal weight patients, respectively, after PCI. Several possible reasons could be responsible for such an outcome. DM is associated with a higher risk of mortality after PCI.[59] A total of 3.02%, 4.12%, and 9.24% in-hospital, short-, and long-term deaths, respectively, occurred in these DM patients compared to 1.59%, 2.46%, and 5.35% in-hospital, short-, and long-term deaths in nondiabetics patients in our study. These patients have worse adverse clinical outcomes including mortality due to severe stent thrombosis, stroke, silent myocardial infarction, or other major adverse cardiac effects. Conditions such as multicoronary vessel diseases and chronic total occlusion which are associated with DM patients partly contribute to these worse clinical outcomes after PCI. The risk of restenosis after stent implantation is also higher in diabetic patients. DM patients also have platelet dysfunction which contribute to this expected increased risk of mortality in these patients.[107] A poor response to antiplatelet agents such as aspirin and clopidogrel after drug eluting stents implantation could be another reason for such a result.[108] The use of insulin could also be another reason for this higher mortality risk in these diabetic patients.[109] Comorbidities and severe diabetic complications are associated with these insulin-treated diabetic patients which finally result in a higher mortality in this category of patients after PCI. MS which is considered to be a modifiable cardiovascular risk factor, includes patients who can be obese, may have diabetes, may suffer from hypertension, and may also have dyslipidemia. The long-term mortality in these patients was significantly higher compared to those without MS after PCI. A significant increase in long-term mortality from 8.21% in non-MS to 12.1% in MS has been found in our study. Its association with comorbidities such as DM and hypertension maybe one of the reasons that lead to a higher mortality in these patients after PCI.[31] Hypertension is another major modifiable risk factor for CAD and acute coronary syndrome. Hypertensive patients had a higher mortality risk compared to normotensive patients after PCI. A significant long-term mortality of 8.51% has been observed in the hypertensive group, compared to the normotensive group which was only 5.88% after PCI. The reasons associated with this result could be an increased in diastolic dysfunction in these hypertensive patients which could lead to severe heart failure. Moreover, by hypertension, we refer to essential hypertension which is a disease that occurs in advanced age. Other comorbid conditions such as diabetic mellitus may be present in these hypertensive patients thus, strengthening/increasing the mortality risk in these patients after PCI.[8] Patients with high blood pressure are even prone to cerebral hemorrhage if their antiplatelet dosages are not adjusted after PCI. This can also contribute to death in these patients. Dyslipidemia is another well-known modifiable risk factor for coronary heart disease. It was expected to be associated with a higher mortality after PCI but however, the results were not significant in our study. A few studies have shown the existence of a “cholesterol paradox” whereby the mortality rate in hypercholesterolemia patients was lower compared to those with normal cholesterol levels.[20] The reasons for such a phenomenon is still not clear. However, even such a result was not evident in our study. Several factors could have been responsible for this insignificant result. The use of statin (lipid-lowering drugs) has not been studied in our meta-analysis.[110] Obesity is another modifiable risk factor for cardiovascular diseases. Surprizingly, our study showed an unexpectedly, significantly decreased mortality in these high BMI patients in all the follow-up categories after PCI. A significant 1.79% overall death has been observed in the overweight and obese patients whereas a higher overall mortality of 2.38% was observed among the combined normal weight/underweight patients. Several studies have shown the existence of an “obesity paradox” in such patients after cardiovascular intervention.[44] The baseline features in this study showed a higher rate of diabetes, dyslipidemia, and hypertension among the overweight and obese patients. Intensive medications and aggressive medical therapies, regular counselling about health benefits, younger age, and having a good storage for nutrients after PCI could all be responsible for such a phenomenon. Size of the coronary blood vessels could also be considered as one of the reasons for this “obesity paradox.”[44] However, a few studies also showed different results. The study by Akin et al[35] in 2012 revealed no evidence of such a phenomenon. In his study, normal body weight patients and obese patients had similar rates of all-cause mortality. Such a different result in his study could be due to the fact that his study dealt with the comparison of different types of drug eluting stents and their corresponding adverse clinical outcomes after PCI. However, it is not clear whether or not this increased mortality risk could also have been more prominent among the underweight which could not be compensated by the normal weight population. Smoking, which is another modifiable cardiovascular risk factor, has proved to be associated with cardiovascular disorders. Unexpectedly, results from our study showed a significantly decreased risk of overall mortality in these smokers (3.37%) compared to nonsmokers (5.13%) after PCI. According to the baseline features in this study, most of the nonsmokers were diabetics and suffered from high blood pressure. The existence of a “smoking paradox” has also been observed in other studies. For example, the study by Hasdai and Holmes found lower adverse outcomes in smokers compared to nonsmokers after PCI.[111] The question about why smokers have a lower mortality rate compared to nonsmokers after PCI is more interesting than its answer. Reasons suggested for this smoking paradox could be younger age, a more favorable clinical and angiographic profile among these smokers, and less damage to microvascular function in these patients after PCI. However, many other studies had different results compared to our meta-analysis. The study Jang et al[112] showed that individuals who continue smoking after PCI experienced significantly poorer outcomes compared to patients who have never smoked. Another study by Castela et al showed a higher rate of vascular complications, but a similar mortality rate between smokers and nonsmokers at 1 year. However, a smaller population size and a different definition of smoker could be responsible for this different result in his study. Apart from these cardiovascular risk factors, an increased mortality in these patients after PCI could also have been due to factors such as drug eluting stents, which are associated with a higher long-term risk of stent thrombosis. Also, glucose-lowering drugs in DM patients have been associated with an increased risk of mortality in this modifiable cardiovascular risk group.[113,114] Moreover, a study by Yusuf et al[115] showed no difference in cardiovascular mortality even with intensive lifestyle intervention in DM patients indicating that there may be other factors such as socio-economic status which contribute to this increase in mortality in these high risk patients. This meta-analysis with a large number of patients is the one and only meta-analysis comparing mortality between patients with low and high modifiable cardiovascular risk factors after PCI. Including 100 studies consisting of 844,190 patients with several modifiable cardiovascular risk factors such as DM, high BMI, hypertension, dyslipidemia, smoking and MS, and their impact on mortality after PCI makes this meta-analysis a completely new research in the field of interventional cardiology. Several limitations in this meta-analysis were as follows: in a few studies, all-cause mortality was not among the clinical endpoints, however, being part of it, data concerning cardiac death has been considered. One study included mortality and myocardial infarction together. Because these data could not be separated, we have included them together in our meta-analysis. One study about smokers and PCI included data for the smokers undergoing fibrinolysis and PCI together. This may affect the result of our study to a certain extent. Moreover, in 1 study, overweight patients and obese patients were classified as a BMI >23.5 and 27.5 kg/m2 instead of 25 and 30 kg/m2, respectively. Another study classified a BMI of 25–35 kg/m2 to be considered as overweight and >35 kg/m2 to be considered as obese patients. Data for the baseline characteristics in several studies were not provided in the original article or could not be converted to dichotomous variables. Therefore, these data have been omitted in our meta-analysis. The baseline features of all the 100 studies have been analyzed and, the data concerning the number of patients with their corresponding risk factor in the whole study were obtained from the baseline features of each study. However, studies without dichotomous data at baseline, or if corresponding data were not available, have been omitted from this count. Therefore, except for the data being analyzed, the count for “modifiable cardiovascular risk factors for the whole study” is just an approximation for this study. However, despite these limitations, our data point to the urgent need for comprehensive comparison between these 2 groups of patients.

CONCLUSION

Certain modifiable cardiovascular risk subgroups had a significantly higher impact on mortality after PCI. However, mortality among the obese patients and the smokers showed an unexpected paradox after coronary intervention.
TABLE 3 (Continued)

Shows the Baseline Features of Each of the Included Studies

TABLE 4

Summarizes the Results of This Meta-Analysis

  113 in total

1.  Association of body mass index with outcome after percutaneous coronary intervention.

Authors:  Brian D Powell; Ryan J Lennon; Amir Lerman; Malcolm R Bell; Peter B Berger; Stuart T Higano; David R Holmes; Charanjit S Rihal
Journal:  Am J Cardiol       Date:  2003-02-15       Impact factor: 2.778

2.  Platelet response to clopidogrel is attenuated in diabetic patients undergoing coronary stent implantation.

Authors:  Tobias Geisler; Nicole Anders; Maria Paterok; Harald Langer; Konstantinos Stellos; Stephan Lindemann; Christian Herdeg; Andreas E May; Meinrad Gawaz
Journal:  Diabetes Care       Date:  2007-02       Impact factor: 19.112

3.  Effect of obesity on repeat revascularization in patients undergoing percutaneous coronary intervention with drug-eluting stents.

Authors:  Zhi Jian Wang; Yu Jie Zhou; Ying Xin Zhao; Yu Yang Liu; Dong Mei Shi; Xiao Li Liu; Miao Yu; Fei Gao
Journal:  Obesity (Silver Spring)       Date:  2011-06-30       Impact factor: 5.002

4.  Prognostic influence of diabetes mellitus on long-term clinical outcomes and stent thrombosis after drug-eluting stent implantation in asian patients.

Authors:  Duk-Woo Park; James D Flaherty; Charles J Davidson; Sung-Cheol Yun; Seung-Whan Lee; Young-Hak Kim; Cheol Whan Lee; Myeong-Ki Hong; Sang-Sig Cheong; Jae-Joong Kim; Seong-Wook Park; Seung-Jung Park
Journal:  Am J Cardiol       Date:  2009-01-17       Impact factor: 2.778

5.  Impact of metabolic syndrome among patients with and without diabetes mellitus on long-term outcomes after percutaneous coronary intervention.

Authors:  Takatoshi Kasai; Katsumi Miyauchi; Takeshi Kurata; Shinya Okazaki; Kan Kajimoto; Naozumi Kubota; Hiroyuki Daida
Journal:  Hypertens Res       Date:  2008-02       Impact factor: 3.872

6.  Impact of body mass index on outcomes after percutaneous coronary intervention in patients with acute myocardial infarction.

Authors:  Laxmi Mehta; William Devlin; Peter A McCullough; William W O'Neill; Kimberly A Skelding; Gregg W Stone; Judith A Boura; Cindy L Grines
Journal:  Am J Cardiol       Date:  2007-02-12       Impact factor: 2.778

7.  Impact of diabetes on 10-year outcomes of patients with multivessel coronary artery disease in the Medicine, Angioplasty, or Surgery Study II (MASS II) trial.

Authors:  Eduardo Gomes Lima; Whady Hueb; Rosa Maria Rahmi Garcia; Alexandre Costa Pereira; Paulo Rogério Soares; Desiderio Favarato; Cibele Larrosa Garzillo; Ricardo D'Oliveira Vieira; Paulo Cury Rezende; Myrthes Takiuti; Priscyla Girardi; Alexandre Ciappina Hueb; José A F Ramires; Roberto Kalil Filho
Journal:  Am Heart J       Date:  2013-06-15       Impact factor: 4.749

8.  Smoking status on outcomes after percutaneous coronary intervention.

Authors:  Tao Chen; Wei Li; Yang Wang; Bo Xu; Jin Guo
Journal:  Clin Cardiol       Date:  2012-05-15       Impact factor: 2.882

9.  Impact of body mass index on the clinical outcomes after percutaneous coronary intervention in patients ≥ 75 years old.

Authors:  Pei-Yuan He; Yue-Jin Yang; Shu-Bin Qiao; Bo Xu; Min Yao; Yong-Jian Wu; Yuan Wu; Jin-Qing Yuan; Jue Chen; Hai-Bo Liu; Jun Dai; Wei Li; Yi-Da Tang; Jin-Gang Yang; Run-Lin Gao
Journal:  Chin Med J (Engl)       Date:  2015-03-05       Impact factor: 2.628

10.  Explaining the decrease in U.S. deaths from coronary disease, 1980-2000.

Authors:  Earl S Ford; Umed A Ajani; Janet B Croft; Julia A Critchley; Darwin R Labarthe; Thomas E Kottke; Wayne H Giles; Simon Capewell
Journal:  N Engl J Med       Date:  2007-06-07       Impact factor: 91.245

View more
  17 in total

1.  Personal Protective Equipment for COVID-19 and Beyond: Occupational and Environmental Exposure Considerations in Primary Care.

Authors:  Onyemaechi Nwanaji-Enwerem; Jamaji C Nwanaji-Enwerem; Brian Antono
Journal:  Perm J       Date:  2022-04-05

2.  The impact of diabetes mellitus and hypertension on clinical outcomes in a population of Iranian patients who underwent percutaneous coronary intervention: A retrospective cohort study.

Authors:  Mohammad Javad Zibaeenezhad; Seyyed Saeed Mohammadi; Mehrab Sayadi; Soorena Khorshidi; Ehsan Bahramali; Iman Razeghian-Jahromi
Journal:  J Clin Hypertens (Greenwich)       Date:  2019-09-25       Impact factor: 3.738

3.  Mir-1, miR-122, miR-132, and miR-133 Are Related to Subclinical Aortic Atherosclerosis Associated with Metabolic Syndrome.

Authors:  Agnė Šatrauskienė; Rokas Navickas; Aleksandras Laucevičius; Tomas Krilavičius; Rūta Užupytė; Monika Zdanytė; Ligita Ryliškytė; Agnė Jucevičienė; Paul Holvoet
Journal:  Int J Environ Res Public Health       Date:  2021-02-04       Impact factor: 3.390

Review 4.  Are women with type 2 diabetes mellitus more susceptible to cardiovascular complications following coronary angioplasty?: a meta-analysis.

Authors:  Pravesh Kumar Bundhun; Manish Pursun; Feng Huang
Journal:  BMC Cardiovasc Disord       Date:  2017-07-27       Impact factor: 2.298

5.  Cardiovascular risk factors in Middle Eastern patients undergoing percutaneous coronary intervention: Results from the first Jordanian percutaneous coronary intervention study.

Authors:  Ayman J Hammoudeh; Imad A Alhaddad; Yousef Khader; Ramzi Tabbalat; Eyas Al-Mousa; Akram Saleh; Mohamad Jarrah; Assem Nammas; Mahmoud Izraiq
Journal:  J Saudi Heart Assoc       Date:  2016-10-20

6.  Cardiovascular Outcomes Post Percutaneous Coronary Intervention in Patients with Obstructive Sleep Apnea and Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis.

Authors:  Hong Wang; Xinxin Li; Zhangui Tang; Guoping Gong
Journal:  Diabetes Ther       Date:  2020-06-26       Impact factor: 2.945

7.  Subclinical Inflammation and Endothelial Dysfunction in Young Patients with Diabetes: A Study from United Arab Emirates.

Authors:  Elhadi H Aburawi; Juma AlKaabi; Taoufik Zoubeidi; Abdullah Shehab; Nader Lessan; Awad Al Essa; Javed Yasin; Hussain Saadi; Abdul-Kader Souid
Journal:  PLoS One       Date:  2016-07-26       Impact factor: 3.240

8.  Mortality and causes of death in a national sample of type 2 diabetic patients in Korea from 2002 to 2013.

Authors:  Yu Mi Kang; Ye-Jee Kim; Joong-Yeol Park; Woo Je Lee; Chang Hee Jung
Journal:  Cardiovasc Diabetol       Date:  2016-09-13       Impact factor: 9.951

Review 9.  Biodegradable polymer drug-eluting stents versus first-generation durable polymer drug-eluting stents: A systematic review and meta-analysis of 12 randomized controlled trials.

Authors:  Pravesh Kumar Bundhun; Manish Pursun; Feng Huang
Journal:  Medicine (Baltimore)       Date:  2017-11       Impact factor: 1.817

10.  The impact of clinical and angiographic factors on percutaneous coronary angioplasty outcomes in patients with acute ST-elevation myocardial infarction.

Authors:  Mindaugas Barauskas; Ramunas Unikas; Egle Tamulenaite; Ruta Unikaite
Journal:  Arch Med Sci Atheroscler Dis       Date:  2016-12-30
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.