Patients with NSTE-ACS who underwent pre-intervention OCT examination during coronary angiography (CAG) admitted to the First Affiliated Hospital of Xinjiang Medical University from January 2015 to September 2018 were consecutively screened for study inclusion. NSTE-ACS was diagnosed according to previously established guidelines [12]. The flow chart for patient inclusion and exclusion is shown in Fig. 1. Demographic features, clinical characteristics, CAD risk factors, blood biochemical parameters, echocardiogram (ECG), echocardiography, coronary angiography (CAG), and OCT results were collected. Culprit vessels were determined by CAG, and we focused on plaque vulnerability evidenced by OCT in the culprit vessels. The study protocol was approved by the ethics committee of the First Affiliated Hospital of Xinjiang Medical University before patient enrollment.

Hypertension was diagnosed if the patient had a blood pressure ≥ 140/90 mmHg on at least three separate occasions or was being actively treated with antihypertensive drugs [13]. Diabetes mellitus was diagnosed if the patient had a fasting plasma glucose ≥7.1 mmol/L or a two-hour post load glucose ≥11.1 mmol/L [14], and in those with a definite history of diabetes and who were being treated with glucose-lowering agents. The diagnostic criteria for hyperlipidemia were based on the Guideline of Chinese Adult Dyslipidemia Prevention and Treatment (2016) [15]. Body mass index (BMI) was calculated by dividing a patient’s weight in kilograms by the height in meters squared. Smoking was defined as current smoking habit.

Blood samples from the included patients were drawn immediately after hospital admission,sent immediately for laboratory analysis. MPV was significantly reduced in response to biphasic antiplatelet agents [16, 17]. Therefore, blood collection was performed before the application of an anti-platelet aggregation drug. Blood tests were performed using standard methods in the Central Laboratory of the First Affiliated Hospital of Xinjiang Medical University.

All patients underwent coronary angiogram within 24 h of admission. All enrolled patients received CAG via a standard method by experienced cardiologists. Quantitative analysis of coronary artery stenosis was determined by experienced interventionists. A commercially available C7-XR OCT intravascular imaging system (C7-XR TM OCT Intravascular Imaging System, St. Jude Medical, St. Paul, MN, USA) was used for OCT examination. OCT images were analyzed based on established OCT diagnostic criteria. Specifically, plaque rupture was identified by fibrous cap discontinuity with a cavity formed inside the plaque (Fig. 2a) [18, 19]. Thin-cap fibroatheroma (TCFA) was defined as a plaque with a maximal lipid arc > 90° and the thinnest fibrous cap thickness was ≤65 μm (Fig. 2b) [18]. Two independent investigators (J.L and S. C.F) who were blinded to clinical angiographic data analyzed the OCT images and the laboratory data using a dedicated off-line review system (St. Jude Medical) at the core laboratory (Xinjiang Medical University). Disagreements were solved by consensus with a third investigator.

All analyses were performed using SPSS 23.0 for Windows statistical software (SPSS Inc., Chicago, IL, USA). Continuous variables are expressed as means and standard deviations, whereas categorical variables are presented as percentages. The Chi-square (χ²) test was used for comparing categorical variables. Significant variables in univariate analysis were subsequently included in the multivariate logistic analysis. A P value < 0.05 was considered statistically significant.

Overall, 94 patients with NSTE-ACS were included in this study, including 33 with non-ST-segment-elevation acute myocardial infarction, and 61 with unstable angina pectoris. OCT analyses for the culprit lesions indicated that 17 patients had plaque rupture, 10 had nonrupture with TCFA, and 67 had nonrupture and non-TCFA. ROC curve analysis showed that MPV was predictive of plaque rupture shown in Fig. 3, and a cut-off value of 10.5 fL of MPV conferred a sensibility of 88.2% and a specificity of 62.3%. The area under the ROC was 0.776, indicating good validity (P < 0.001, 95% confidence interval (CI): 0.671–0.880).

Patient characteristics according to MPV levels are presented in Table 1. Those with higher MPV (≥ 10.5 fL) had higher BMI and poorer lipid profiles compared to those with lower MPV levels. No other variables were significantly different with regards to MPV levels.

CAG and OCT findings of the included NSTE-ACS patients according to the MPV are presented in Table 2. The prevalence of plaque rupture and thrombosis was higher in the patients with higher MPV (≥ 10.5 fL) compared to those with lower MPV levels (P < 0.001 and P = 0.002, respectively). There was no significant difference in other CAG and OCT findings between those with higher and lower MPV levels.

Coronary risk factors and laboratory data based on plaque vulnerability, including plaque rupture, nonrupture with TCFA, and nonrupture and non-TCFA, are shown in Table 3. Gender, prevalence of diabetes, previous PCI, current smoking, BMI, MPV and platelet distribution width (PDW) (all P < 0.05) were statistically different among the groups. Patients with ruptured plaque, or non-rupture with TCFA are more likely to be male, diabetic, previous PCI, BMI, MPV, MPV ≥ 10.5 fL, PDW as compared with those with non-rupture and non-TCFA (P all < 0.05).

Significant variables in univariate analysis were subsequently included in the multivariate logistic analysis. Multivariate logistic regression analyses showed that diabetes, higher BMI, higher PDW, and higher MPV (≥ 10.5 fL) were independent predictors of plaque rupture (P all < 0.05; Model 1; Table 4), while diabetes and higher PDW were independent predictors of TCFA (both P < 0.05; Model 2; Table 4).

CAG and OCT findings according to coronary plaque vulnerability, including patients with plaque rupture, nonrupture with TCFA, and nonrupture and non-TCFA, are shown in Table 5. The degree of macrophage accumulation, thrombus, and normal lumen area were significantly different among the three groups (P = 0.005, 0.001, and 0.003, respectively). No significant difference was observed for other CAG and OCT characteristics. Specifically, the macrophage accumulation in the plaque rupture group was higher than that in the non-plaque rupture with TCFA group (P = 0.005). The incidence rate of thrombus in the plaque rupture group was higher than that in the non-plaque rupture with TCFA group (P<0.001). The NLA of the nonrupture with non-plaque rupture with TCFA group was higher than that of the nonrupture and non-TCFA group (P = 0.003). The macrophage accumulation of the TCFA group was higher than that of the nonrupture and non-TCFA group (P = 0.005). The incidence rate of thrombus of non-TCFA group was higher than that of the nonrupture and non-TCFA group (P<0.001). The NLA of the nonrupture with non-plaque rupture with TCFA group was higher than that of the nonrupture and non-TCFA group (P = 0.003).

MPV is the most commonly used indicator of platelet size, which may reflect platelet activation [20]. Studies have demonstrated that an increase in MPV may confer similar risks as smoking and obesity for the incidence and prognosis of myocardial infarction and atherosclerosis [21]. Previous studies evaluating the association between MPV and CAD risk focused on clinical outcomes [22, 23]. Our study, using OCT, the “gold standard” of current vulnerable plaque judgment in vivo, provided the pathophysiological basis underlying the association between MPV and coronary events by showing that MPV is associated with plaque rupture. Higher MPV has also been associated with CAD risk factors such as hypertension, diabetes, old age, obesity, and smoking [24, 25]. In our study, higher MPV levels were associated with obesity and dyslipidemia, which is consistent with previous findings. However, after adjusting for confounding factors, we found that MPV independently predicted plaque rupture as evidenced by multivariate logistic regression analyses. These findings indicate that an incremental increase in MPV reflects platelet activation. Indeed, many recent studies have linked platelet activity to the development and progression of atherosclerosis [26], especially in patients with ACS. MPV has been found to be higher in ACS patients compared to those with stable CAD [27]. Our data also confirmed MPV as an independent predictor of 6-month mortality or nonfatal myocardial infarction in ACS patients [28]. Incorporating MPV in GRACE’s risk score has been suggested to improve the validity of risk stratification in ACS. Patients with high MPV and high troponin levels had a 4.8-fold increased risk of coronary artery disease [29]. However, a previous study suggested that lower MPV levels were associated with the incidence of MACE in patients with stable angina [30]. Taken together, the relationship between changes in platelet volume and the progression of coronary heart disease may be inconsistent in different subtypes of CAD, which should be confirmed in future studies with larger sample sizes.

Our results are consistent with previous experimental findings that demonstrated that large platelets may be more likely activated, leading to platelet adhesion and aggregation, resulting in a pro-atherosclerotic effect [30, 31]. Large platelets are rich in secretory granules and have a stronger metabolism and enzyme activity. Furthermore, increases in platelet volume lead to the release of young platelets in the bone marrow, which are more reactive and exhibit an enhanced pro-thrombotic activity [32]. In contrast, increased inflammatory factors during acute coronary events may further change platelet morphology and reactivity [33], leading to higher MPV levels. The result is a vicious cycle that exacerbates the course of the disease. However, more experiments are needed to explore the molecular mechanism for changes in MPV in patients with NSTE-ACS.

PDW refers to the degree of difference in platelet volume, expressed as the degree of variation in single platelet volume. Increased PDW indicates that platelet volume is not uniform and individual volumes vary greatly. When platelets are activated, they undergo morphological changes by forming pseudopodia, leading to changes in PDW. As a result, platelets become larger and reactive, thus increasing PDW. Furthermore, PDW has also been regarded as a more concrete parameter for platelet activation than MPV, as it does not increase during simple platelet swelling [34, 35]. Accordingly, some studies have suggested a potential relationship between PDW and CAD [36, 37]. Our study showed that PDW was an independent risk factor for plaque rupture as well as TCFA occurrence in NSTE-ACS patients. These results may reflect rapid platelet consumption and activation in patients with unstable coronary plaques. Although the accurate mechanism is unclear, our findings support that PDW confers more predicted efficacy to plaque vulnerability in NSTE-ACS patients since it was associated with plaque rupture and the formation of TCFA under OCT. Further studies are needed to confirm our findings and expand the role of PDW in risk stratification in NSTE-ACS patients.

There are several limitations in this study that should be acknowledged. First, this study is a retrospective observational single-center study, and results of our study should be confirmed with prospective cohort studies. Secondly, we focused on coronary plaques in culprit vessels. Predictors for the plaque composition of non-target lesions were not analyzed. Thirdly, large residual thrombi may blur the lumen boundary and the underlying plaques, making it difficult to assess the underlying plaque characteristics. Finally, this study attached undue importance to qualitative differences of coronary plaques and thus ignored the observation of spatial distribution of different plaques.