Mean platelet volume and coronary plaque vulnerability: an optical coherence tomography study in patients with non-ST-elevation acute coronary syndrome

Abstract

Background The association between mean platelet volume (MPV) and coronary plaque vulnerability in patients with non-ST-elevation ACS (NSTE-ACS) has not been investigated. We performed a retrospective study to evaluate the association between MPV and plaque vulnerability using optical coherence tomography (OCT). Methods Consecutive NSTE-ACS patients who underwent pre-intervention OCT examination in our center were included in this study. Features of coronary plaques in the culprit arteries were classified as rupture, nonrupture with thin-cap fibroatheroma (TCFA), and nonrupture and non-TCFA. ROC analyses were used to determine the predictive efficacy of MPV for plaque rupture, and multivariate logistic regression analysis was performed to evaluate the potential independent predictors of plaque vulnerability. Results Overall, 94 patients were included in this study. We identified 17 patients with plaque rupture, 10 with nonrupture with TCFA, and 67 with nonrupture and non-TCFA. ROC analyses showed that MPV ≥ 10.5 fL was predictive of plaque rupture in NSTE-ACS patients. Univariate analyses indicated that patients with higher MPV (≥ 10.5 fL) had higher body mass index and poorer lipid profiles compared to those with lower MPV. Moreover, those with higher MPV had higher incidences of plaque rupture and thrombosis (both P < 0.05). Results of multivariate analyses showed that diabetes and higher platelet distribution width (PDW) were independent risk factors of TCFA ( P = 0.032 and 0.046, respectively), while diabetes, higher BMI, higher PDW, and higher MPV were independent determinants of plaque rupture in our cohorts (P all < 0.05). Conclusions Higher MPV is independently associated with higher risk of plaque rupture as evidenced by OCT in our cohort of NSTE-ACS patients.

Predictive efficacy of neutrophil-to-lymphocyte ratio for long-term prognosis in new onset acute coronary syndrome: a retrospective cohort study

“…The key pathophysiologic processes for ACS include the rupture of a vulnerable plaque and subsequent formation of thrombosis [ 25 , 26 ], and the role of inflammation in these processes has not only been confirmed by pathological studies, but also shown in some optical coherence tomography-based studies [ 6 , 27 ]. Therefore, it has been proposed that the NLR, a novel but easily obtained marker of inflammation, may be a prognostic factor for ACS patients.…”

“…The current understanding of the pathogenesis of atherosclerosis is focused on the "inflammatory hypothesis of atherothrombosis" theory [ 1 , 2 ]. Inflammatory cells and inflammatory signaling pathways play complex roles in the process of atherosclerosis, including initiating repair after vascular injury and mediating plaque instability and rupture, finally leading to acute coronary events [ 3 – 6 ]. Patients with acute coronary syndrome (ACS), particularly those with new-onset ACS, often have an unstable clinical status and a poor prognosis, and optimization of risk stratification is clinically important in this patient group [ 7 , 8 ].…”

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“…Patients with coronary artery disease (CAD), particularly those with acute coronary syndrome (ACS), often exhibit unstable disease progression and unfavorable prognosis. Therefore, risk stratification of these patients is of much clinical relevance (Jun et al, 2019 ; Khot et al, 2003 ; Messerli Franz et al, 2019 ). Numerous studies have confirmed the direct relationship between the onset of left bundle‐branch block (LBBB) and outcome measures such as all‐cause mortality, cardiac death, acute myocardial infarction (MI), sudden cardiac death, and congestive heart failure, both in patients with and without pre‐existing CAD (Bristow et al, 2004 ; Di Marco et al, 2020 ; Kiehl Erich et al, 2019 ; Moss et al, 2009 ; Witt et al, 2016 ).…”

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“…Further, a prospective cohort study has confirmed that incorporating available clinical variables into the existing predictive score is important for prognostic estimation after myocardial infarction [ 37 ]. While there have been a variety of approaches to create a more effective method and identification of new risk factors to discriminate at high risk for CAD [ 38 – 42 ], no specific prediction model has been developed to identify CCS patients who are at risk for moderate to severe OSAS. Besides, previous studies have demonstrated that Berlin and STOP-BANG questionnaire provides convenient and reliable score tools for OSAS risk assessment, but lack of reliable biomarkers to improve prediction accuracy [ 17 – 19 ].…”