Association between PDW and Long Term Major Adverse Cardiac Events in Patients with Acute Coronary Syndrome

Association between PDW and Long Term Major Adverse Cardiac Events in Patients with Acute Coronary Syndrome

Şeref Ulucan a, Ahmet Keser a, Zeynettin Kaya a*, Hu¨ seyin Katlandur a, Hu¨ seyin  Ozdil a, Mustafa Bilgi b, I˙smail Ates¸ c, Mehmet Sıddık U¨lgen a

Background: The aim of the present study was to perform a preliminary evaluation of the potential association between platelet distribution width (PDW) and frequency of major adverse cardiovascular events (MACEs) devel-opment in an observational study of acute coronary syndrome (ACS) patients.

Methods: A total of 679 consecutive patients with ACS (498 (73.3%) males; mean age was 63.31  _ 11.2 years; study population composed of 320 patients with acute myocardial infarction and 359 patients with unstable angina pectoris) subjected to primary percutaneous coronary intervention with transradial approach (TRA) were retrospectively enrolled to the study. Tertiles were formed based on PDW levels. The associa-tions between PDW and in-hospital and long-term MACEs were analysed.

Results: The frequencies of in-hospital instent thrombosis (P=0.05), long-term instent restenosis (P=0.005) and long-term total MACEs (P=0.008) were higher in tertiles having a high PDW value. In multivariate analyses, PDW was an independent predictor of in-hospital and long-term MACEs (odds ratio 1.081, 95% confidence interval 1.003-1.165; p=0.042). The projected Kaplan-Meier incidence of a MACEs in the PDW tertiles groups were 12.8%, 12.1%, and 21.6% at 40 months (respectively, p=0.003).

 Conclusions: The pre-procedural PDW may be an independent predictor of both in-hospital and long-term adverse outcomes in patients with ACS.

 Keywords: Platelet distribution width - Acute coronary syndrome - Transradial - Primary percutaneous coronary intervention - Major adverse cardiac events.

Introduction

 Acute coronary syndrome (ACS) is a multi-factorial disease where multiple endogenous and exogenous risk factors are held responsible [1]. However, in the majority of the ACS cases, only some of such risk factors can be identified [1]. Thus, studies are being carried out to establish new risk factors to help predict both the diagnosis and the prognosis in ACS patients. Platelets have an important role in the pathogenesis of ACS [2]. Plaque rupture is followed by platelet activation and thrombus formation which cause coronary artery occlusion[2]. Anti-platelet agents have a significant role in the treatment of ACS. As acetylsalicylic acid, thienopyr- idine and glycoprotein 2b/3a inhibitors prevent the func- tions of platelets, they are used in the treatment of ACS [2,3].

Volume and activities of platelets vary [4]. Platelet size has been shown to increase once the platelet activation starts [5]. This activation increase is measured by mean platelet volume and platelet distribution width (PDW) [5]. Therefore, PDW is a marker of platelet activation [5,6]. Larger platelets are more adhesive and more prone to aggression [5–7]. An increase in platelet volume facilitates coronary thrombus formation in cases having ACS [5]. However, there are no sufficient data on the effects of PDW on the prognosis of ACS and on the frequency of major in-hospital and long-term adverse outcomes. The aim of the present study was to evaluate the associa-tion between PDW and frequency of major adverse cardio-vascular events (MACEs) development in patients with ACS.

 Method

 We retrospectively evaluated the data of a total of consecu-tive 816 ACS patients applying to the hospital between June 2009 and January 2013. Those admitted to the hospital with symptoms starting within the previous 24 hours of admis-sion were included in the study. Those undergoing femoral intervention or fibrinolytic treatment, having active infec-tions, systemic inflammatory disease or end-stage liver and kidney failure, having symptoms starting before the last 24 hours, having no laboratory findings and being lost to follow-up, namely a total of 137 patients, were excluded from the study. The final study group consisted of 679 patients. A typical chest pain lasting more than 30 min and 1 mm ST elevation in two consecutive leads at electrocardiography or newly developed left branch block was defined as acute myocardial infarction[8]. Additionally, ST-T alteration at electrocardiography and typical chest pain without any increase at cardiac enzymes was defined as unstable angına pectoris [8]. All the patients underwent a 12-electrode electrocardiography (ECG), and ischaemic ECG alterations were interpreted by senior cardiologists. 300 mg acetylsalicilic acid, 70U/Kg intravenous heparin and 300 mg loading dose of clopidogrel was administered after the initial diagnosis of ACS. All the patients underwent coronary angiography by transradial approach. Medical treatment, balloon angiography and stent, coronary artery bypass graft operation were performed based on the outcome of coronary angiography. Stent type was chosen by the operator during the operation. Maintenance therapies were performed in all patients according to the most up-to-date guidelines[9,10]. Blood samples for laboratory analysis were taken from all patients on admission. The blood samples obtained were drawn into standard test tubes containing dipotassium edetic acid (EDTA). All samples were analysed on Sysmex K-X-21N auto-analyser. Along with platelet count, mean platelet volume (MPV) showing that indicator of the platelet volume, PDW, platelet large cell ratio (PLCR) were checked too. Follow-up data was obtained from the hospital archive, the patients and relatives of the patients. In-stent stenosis or stent thrombosis, non-fatal myocardial infarction and cardiac related death were defined as MACEs.

Statistical Analysis

 Normal distribution of data was evaluated using the Kolmo-gorov Smirnov test. For stratification analysis, the study population was divided into three tertiles according to PDW (1st tertile: <12, 2nd tertile: 12-13.7 and 3rd tertile: >13.7). Continuous data was reported as mean and standard deviation while the data that are not normally distributed were reported as median; and the groups were compared using the Student’s t-test or a Mann-Whitney U test. The measurements in PDW tertiles were compared with the one-way ANOVA. Categorical variables were summarised as percentages and compared using the Chi-square test. Post hoc analysis was performed by Tukey test. The association of different variables with in-hospital and long-term MACEs were calculated in the univariate analysis. The cumulative survival curve for one-year CV mortality was constructed using the Kaplan-Meier method and compared using the log-rank test. The variables having an unadjusted p value less than 0.10 were considered as potential risk factors. Then, these were included in the multivariate model. Backward elimination multivariate logistic regression analyses were utilised. A p value <0.05 was considered significant. All the statistical analyses were performed using SPSS version 15.0 (SPSS, Inc., Chicago, IL).

Results

 The study population consisted of 679 consecutive ACS patients (498 (73.3%) males, mean age = 63.31  _ 11.2 years). The baseline characteristics of the patients according to PDW tertiles are presented in Table 1. In terms of coronary risk factors, there were statistically significant differences regard-ing high density lypoprotein, serum glucose level and previ-ous coronary artery disease (p for trend, p<0.048, p<0.022, p<0.035 respectively). Coronary risk factors, including cur-rent smoking, diabetes mellitus, hypertension, low density lipoprotein, did not differ among tertiles. The ratio of patients to undergo percutaneous coronary intervention (PCI) and coronary artery bypass as a result of coronary angiography was statistically similar in each tertile. How-ever, the ratio of patients to receive medical treatment only was statistically significantly higher in tertile 1 when com-pared to the other groups (P=0.001). When it comes to angiographic characteristics, there were statistically significant differences in terms of one, two, three-vessel diseases and coronary slow flow among the PDW tertiles (p for trend, p<0.003, p<0.003, p<0.0003 and p<0.004 respectively). Incidence of left main coronary artery (LMCA) disease did not show any difference among the tertiles (p=0.0643) (Table 2). The Pearson correlation analysis revealed a statistically significant positive correlation between PDW values and three-vessel disease (r:0,321; p<0,001).

Table 1. Baseline characteristics of study patients according to PDW tertiles

Common blood counting parameters were analysed. There were statistically significant differences in terms of platelet count (/mm3), white blood cell count (103/uL) and PLCR between the PDW tertiles (p for trend, p<0.001, p<0.037, p<0.0001 and p<0.004 respectively). Neutrophil levels (7.0  _ 2.6, 7.5  _ 2.8, 7.4  _ 2.8, p for trend =0.196), and lymphocyte count were similar between tertiles (2.5  _ 1.5, 2.6  _ 1.5, 2.7  _ 1.5, p for trend =0.401) (Table 3). The mean follow-up period was 21 months (1-44 months). In-hospital and long-term MACEs stratified by tertiles are shown in Table 4. Non-fatal myocardial infarction and hospital mortality (p=0.617, p=0.628 respectively) during in-hospital

Table 2. Angiographic characteristics of study population according to PDW tertiles

Table 3. Common blood counting parameters of study population according to PDW tertiles

period did not show any statistically significant difference among three tertiles while in-stent thrombosis differed signif- icantly (p<0.050). When we evaluated the long-term follow-up results, in-stent thrombosis and MACEs were found to be high in tertile 3 (p<0.005, p<0.008 respectively) (Table 4). The projected Kaplan-Meier incidence for MACEs was 12.8%, 12.1%, and 21.6 at 40 months (respectively, p=0.0034). Also, the projected Kaplan-Meier incidence for late stent reste- nosis was 11.5%, 10.0%, and 19.8% at 40 months (respectively, p=0.0052;) (Figure 1). Among the tertiles, there were differences in terms of some variables possibly having an effect on both the in-hospital and long-term MACEs results. Therefore, we carried out multivar- iate analysis for the independence of predictors. The effects of different variables on the in-hospital and long-term MACEs were calculated by univariate analysis. The variables where the unadjusted p value was <0.10 in the logistic regression analysis were defined as potential risk markers and included in the full model. For in-hospital MACEs, PDW, body mass index and glycoprotein IIb/IIIa antagonist were analysed with multivariate logistic regression model. At multivariate analyses, PDW was an independent predictor of in-hospital MACEs (odds ratio 1.081, 95% confidence interval 1.003-1.165; p=0.042) (Table 5). For long-term MACEs, age and PDW were analysed with a multivariate logistic regression model. In multivariate analyses, PDW was the only independent predic- tor of long-term MACEs (odds ratio 1.218, 95% confidence interval 11.116-1.328; p<0.0001).

Table 4. In-hospital and long-term major adverse cardiac events

Discussion

 In our study, the association between PDW and the fre-quency of MACEs was investigated. It was found that PDW level was associated with increased frequency of in-hospital instent thrombosis, long-term stent restenosis and MACEs. Moreover, there was a statistically significant posi-tive correlation between PDW values and three-vessel dis-ease. Similarly, it was found that PDW was an independent predictor of in-hospital and long-term MACEs. In ACS, thrombocyte activation is increased as a result of increased thrombocyte consumption due to thrombosis occurring after plaque rupture. Increased thrombocyte con-sumption causes an increase in large, granule-rich thrombo-cytes expressed from the bone marrow into the blood circulation. Through this activation pathway, the shape of thrombocytes change through a kind of metamorphism [11] and secrete thromboxane A2 and ADP to circulation more actively. These enlarged thrombocytes are more adhesive, and also more active compared to smaller thrombocytes due to their secretory granules, and mitochondria content is increased [12]. Free released thromboxane A2 and ADP activate to adja-cent cells and start a cycle. Activated thrombocytes not only release secreted thromboxane A2 and ADP but also bind to fibrinogen, a coagulation protein, through abundant platelet integrin and glycoprotein 2b/3a [13]. Platelet-fibrinogen-platelet interaction starts platelet aggregation and thus ACS occurs through coronary thrombosis formation[14]. Up to today, many thrombocyte parameters have been studied [15]. Among these, PDW may be more reliable as MPV can be affected from the timing of blood collection, some medicines and pathological conditions. On the other hand, even though MPV has been studied comprehensively, new thrombocyte activation parameters such as PDW have been studies less [16,17]. For this reason, the prognostic value of PDW in ACS patients was analysed in our study, and it was found that PDW was statistically associated with an increase in the frequency of in-hospital in-stent thrombosis and long-term MACEs and in-stent restenosis. In a study on patients having ST-segment-elevation myo-cardial infarction, Tomasz Rechcinski et al. reported that PDW was an indicator of recurrent revascularisation, recur-rent myocardial infarction and cardiac mortality[18]. Our study group contained all ACS patients regardless of the treatment. Moreover, we found that PDW was an indepen-dent indicator for in-hospital and long-term MACEs. These results are consistent with the hypothesis that thrombocyte activation is a marker of bad prognosis in ACS patients. In our study, platelet count was the lowest in tertile 3 having the highest PDW values and the difference was sta-tistically significant (p>0.001). This is consistent with the previous studies showing that the platelet count is decreased in ACS patients having increased platelet activation [5,19]. We found that the frequency of multiple-vessel disease increased by an increase in PDW value. In a wide population composed of stable coronary artery disease, De Luca et al. studied the association between PDW and prevalence of coronary artery disease and claimed that there was no sig-nificant association between them [20]. In our study, contrary to the study performed by De Luca, we found a significant association between PDW and coronary artery disease.

Table 5. Effects of multiple variables on the in-hospital MACE in univariate and multivariate logistic regression analyses

Adjusted for platelet distribution width, glycoprotein IIb/IIIa antagonist, body mass index on admission.

The design of our study does not allow analysis of the cause and effect of this association. However, it can be suggested that increased prevalence of atherosclerosis and tendency of thrombosis in ACS patients can be be associated with an increase in thrombocyte activation. Moreover, N/L ratio was found to be 3.68  _ 2.5. As the said ratio was above 3.5, it was compatible with the results obtained in previous studies conducted on patients having ACS [21]. Another difference of our study is that it employs a trans-radial approach which reduces the ratio of short- and long-term MACEs when compared to a transfemoral approach both in angiography and in primary PCI.

Limitations

 The limitations of our study are those known to be associated with a retrospective study design. The number of cases was believed to be sufficient for a statistical evaluation. However, having results from a single centre and not analysing the patients individually based on the type of ACS were among our limitations.

Conclusions

 Pre-procedural PDW may be one of the independent prog-nostic factors for both in-hospital and long-term adverse outcomes among ACS patients undergoing primary PCI, by-pass operation or medical therapy. Platelet distribution width is a simple and widely used haematological marker. Our results suggest that such a novel marker should be used in addition to other markers for risk stratification in ACS patients.

Conflict of Interest

 All authors have no conflict of interest to report.

 Acknowledgements

No funding to declare.

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