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Low mean platelet volume is associated with critical limb ischemia in peripheral arterial occlusive disease

Peter Rief1, Reinhard B Raggam2, Alexander Avian3

  • 1Division of Vascular Medicine, Department of Internal Medicine, Medical University Graz, Graz, Austria. peter.rief@medunigraz.at.

Scientific Reports
|May 2, 2018
PubMed

Insights

Low mean platelet volume (MPV) is a significant predictor of critical limb ischemia (CLI) in patients with peripheral arterial occlusive disease (PAOD). This finding suggests MPV can help identify patients at high risk for developing CLI.

Area of Science:

  • Vascular Medicine
  • Hematology
  • Cardiovascular Research

Background:

  • Platelets are implicated in atherosclerosis.
  • Mean platelet volume (MPV) has emerged as a potential marker for coronary artery disease.
  • The role of MPV in peripheral arterial occlusive disease (PAOD) and critical limb ischemia (CLI) requires further investigation.

Purpose of the Study:

  • To investigate the association between MPV and the risk of developing CLI in patients with PAOD.
  • To identify MPV as a potential predictive biomarker for CLI in this patient population.

Main Methods:

  • A cohort of 2124 PAOD patients was analyzed.
  • Univariate logistic regression was employed to identify predictors of CLI.
  • Receiver operating characteristic (ROC) analyses were conducted to determine the optimal MPV cutoff value for predicting CLI.

Main Results:

  • Diabetes, elevated hsCRP, older age, and thrombocytosis were significant independent predictors of CLI.
  • Mean platelet volume (MPV) was also a significant independent predictor (p=0.003, OR 0.84).
  • ROC analysis identified an MPV cutoff value of ≤10.2 fL as optimal for predicting CLI (AUC: 0.55, p<0.001).

Conclusions:

  • A significant relationship exists between lower MPV and an increased risk of CLI in PAOD patients.
  • MPV serves as a valuable biomarker for identifying PAOD patients at higher risk of developing CLI.
  • This finding supports the utility of MPV in risk stratification for CLI.

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