The Relationship Between Mean Platelet Volume, Platelet Distribution Width And Risk Factors For Coronary Heart Disease

Objective: Acute coronary syndromes (ACS) are known to be associatedwith the rupture or fissuring of unstable plaque, accompanied by series ofplatelet reactions. Platelets adhered, aggregated to the injury endothelial,leading to thrombus formation of varying degrees and finally clinicalcomplications. Platelets play a pivotal role in both initiation and propagationof ACS. Mean platelet volume (MPV) and platelet distribution width (PDW)，as biological indicators of platelet activation, can be used in the assessment ofplatelet function. MPV refers to the mean volume of platelets, reflects plateletsize. PDW is the coefficient of variation of platelet volume, reflects the degreeof difference of the platelet size.Platelets are quite heterogeneous blood elements within an individual,diverging in terms of size, density and reactivity. Larger platelets aremetabolically and enzymatically more active, contain more granules andproduce greater amounts of vasoactive factors and prothrombotic factors, sothe size of platelet might be a potential biological markers of plateletactivation. Recent studies have shown that MPV increased in unstable angina,acute myocardial infarction, acute ischemic stroke, pre-eclampsia and renalartery stenosis. An elevated PDW can also be found in acute myocardialinfarction. Otherwise, an elevated MPV predicts a poor outcome followingmyocardial infarction, restenosis after percutaneous coronary intervention.MPV and PDW are independent risk factors and prognostic indicators inpatients with acute coronary syndromes.The most common risk factors of coronary heart disease include highblood pressure, obesity, high fasting blood glucose, hypercholesterolemia, theaged, smoking, diabetes mellitus, and so on. Current researches suggest thatthe increase in platelet size occur before the acute coronary syndrome and may play an important role in the pathogenesis of the disease. Otherwise, thenumbers of the risk factors of coronary heart disease are closely related to thevalue of MPV. There are few studies about the relationshio between PDW andrisk factors for coronary heart disease, according to our knowledge. The aimof this current study is to investigate the relationship between MPV, PDW andthe risk factors.Methods: A total of5006subjects who underwent annual routine healthexamination in the second Hospital of Hebei Medical University betweenApril to June2006was retrospectively analyzed, of whom1966individualsfulfilled the inclusion criteria of our study. Of all these1966enrolled subjects,1160cases (59%) are male, and806cases (41%) are female, with the age of24-80years (55.4±10.8years). Blood samples were drawn after a fastingperiod of12hours, and platelet count (PLC), mean platelet volume, andplatelet distribution width measured with a hematology autoanalyzer. MPV,PDW and PLC in subjects with or without the risk factors of coronary heartdisease (i.e. men, aged, smoking, hypertension, diabetes, obesity (body massindex, BMI≥25kg/m2), serum total cholesterol (TC), triglycerides (TG), lowdensity lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol(HDL-C) and fasting blood glucose) were compared. Based on6of the mostcommon risk factors, including smoking history, hypertension (systolic bloodpressure≥140mmHg and/or diastolic blood pressure≥90mmHg), highfasting blood glucose (≥7.0mmol/L), obesity (body mass index, BMI≥25kg/m2), aged (male≥45yrs, female≥55yrs), and dyslipidemia (LDL-C≥4.1mmol/L or HDL-C <1.04mmol/L), subjects were divided according to thenumbers of risk factors within an individual, using multiple variance analysisto find out the changes of MPV and PDW with risk factors’ number increased.Statistical analysis was performed with SPSS19.0software. Parametricvariables were expressed as mean±standard deviation (SD), and categoricalvariables were expressed as percentages (%). An independent sample t testwas used to indicate differences of parametric variables. One-Way analysis ofvariance (ANOVA) was used to compare more than two parametric variables, followed by SNK for post hoc analysis. A P value less than0.05was acceptedas statistically significant difference.Results: Finally1966individuals were included in our study,1160ofthem were male (59.0%), and806subjects were female (41%), with a meanage of55.4±10.8years (ranging from24to80years) at the time of analysis.The platelet indices have gender-dependent differences, with a higher MPVand PDW value in female compared with the male (P <0.05). Subjects withsustained smoking, high blood pressure (systolic blood pressure≥140mmHgand/or diastolic blood pressure≥90mmHg), obesity (BMI≥25kg/m2), theaged (males≥45yrs, females≥55yrs), hyperglycemia (fasting plasma glucose≥7.0mmol/L), or diabetes mellitus, had an increased MPV compared withthose without the above-mentioned risk factors (P <0.05). PDW increasedsignificantly in subjects with obesity, aging, hyperglycemia, or diabetesmellitus (P <0.05). There were no significant differences between those whohad dyslipidemia (TC≥6.3mmol/L, TG≥2.26mmol/L, LDL-C≥4.1mmol/L,HDL-C <1.04mmol/L) and those without dyslipidemia, with respect to eitherMPV or PDW. With the increase of the number of risk factors, the PLCreduced gradually, while MPV and PDW continuously increased. PLC isnegatively correlated to the MPV and PDW (r=-0.33, r=-0.27, P=0.00,respectively), while MPV and PDW are positively correlated (r=0.77, P=0.00).Conclusion: MPV and PDW are closely correlated with the risk factorsof coronary heart disease. With the increase in the number of risk factorswithin an individual, the PLC decreases gradually, while MPV and PDWincreases continuously. PLC correlates negatively with MPV and PDW, andMPV and PDW are positively correlated.