Journal
CLINICAL AND APPLIED THROMBOSIS-HEMOSTASIS
Volume 29, Issue -, Pages -Publisher
SAGE PUBLICATIONS INC
DOI: 10.1177/10760296231159113
Keywords
atherosclerosis; platelets; coronary calcification; CAD prevention; clinical cardiology
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Coronary calcium score (CCS) is a sensitive marker for coronary artery calcification (CAC) and coronary artery disease (CAD). This study found a strong association between mean platelet volume (MPV) and CAC severity, suggesting that MPV could be an independent predictor for CAD risk. These findings highlight the potential of using MPV as a routine blood test to detect patients at risk for CAD.
Coronary calcium score (CCS) is a highly sensitive marker for estimating coronary artery calcification (CAC) and detecting coronary artery disease (CAD). Mean platelet volume (MPV (is a platelet indicator that represent platelet stimulation and production. The aim of the current study was to examine the association between MPV values and CAC. We examined 290 patients who underwent coronary computerized tomography (CT) exam between the years 2017 and 2020 in a tertiary care medical center. Only patients evaluated for chest pain were included. The Multi-Ethnic Study of Atherosclerosis (MESA) CAC calculator was used to categorize patients CCS by age, gender, and ethnicity to CAC severity percentiles (<50, 50-74, 75-89, >= 90). Thereafter, the association between CAC percentile and MPV on admission was evaluated. Out of 290 patients, 251 (87%) met the inclusion and exclusion criteria. There was a strong association between higher MPV and higher CAC percentile (P = .009). The 90th CAC percentile was associated with the highest prevalence of diabetes mellitus (DM), hypertension, dyslipidemia, and statin therapy (P = .002, .003, .001, and .001, respectively). In a multivariate analysis (including age, gender, DM, hypertension, statin therapy, and low-density lipoprotein level) MPV was found to be an independent predictor of CAC percentile (OR 1.55-2.65, P < .001). Higher MPV was found to be an independent predictor for CAC severity. These findings could further help clinicians detect patients at risk for CAD using a simple and routine blood test.
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