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Low mean platelet volume is associated with critical limb ischemia in peripheral arterial occlusive disease
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AbstractMean platelet volume (MPV) was recently published as a possible marker of coronary artery disease in patients at high risk for major adverse cardiac events. Because platelets play an important role in atherosclerosis, we examined the relationship between critical limb ischemia (CLI) and MPV in patients with peripheral arterial occlusive disease (PAOD). Our study comprised 2124 PAOD patients. Univariate logistic regression was performed to analyze potential predictors for CLI. Nagelkerke’s R² is reported. Cross validation was performed using the leave-one-out principle. ROC analyses were performed to identify the best cut off value for MPV predicting CLI; to this end, Youden’s index was calculated. For CLI diabetes (p < 0.001, OR 2.44, 95% CI 1.97–3.02), hsCRP (p < 0.001, OR 1.01, 95% CI 1.01–1.01), age (p < 0.001, OR 1.05, 95% CI 1.04–1.06), thrombocytosis (p = 0.025, OR 1.84, 95%CI 1.08–3.14), and MPV (p = 0.003, OR 0.84, 95% CI 0.75–0.94) were significant independent predictors for CLI. ROC analysis (AUC: 0.55, 95% CI 0.52–0.58, p < 0.001) showed ≤10.2 as the best cut off value for MPV to predict CLI. As there is a significant relationship between low MPV and a high risk for CLI in PAOD patients, MPV can be used to identify patients who are likely to develop CLI.
Springer Science and Business Media LLC
Title: Low mean platelet volume is associated with critical limb ischemia in peripheral arterial occlusive disease
Description:
AbstractMean platelet volume (MPV) was recently published as a possible marker of coronary artery disease in patients at high risk for major adverse cardiac events.
Because platelets play an important role in atherosclerosis, we examined the relationship between critical limb ischemia (CLI) and MPV in patients with peripheral arterial occlusive disease (PAOD).
Our study comprised 2124 PAOD patients.
Univariate logistic regression was performed to analyze potential predictors for CLI.
Nagelkerke’s R² is reported.
Cross validation was performed using the leave-one-out principle.
ROC analyses were performed to identify the best cut off value for MPV predicting CLI; to this end, Youden’s index was calculated.
For CLI diabetes (p < 0.
001, OR 2.
44, 95% CI 1.
97–3.
02), hsCRP (p < 0.
001, OR 1.
01, 95% CI 1.
01–1.
01), age (p < 0.
001, OR 1.
05, 95% CI 1.
04–1.
06), thrombocytosis (p = 0.
025, OR 1.
84, 95%CI 1.
08–3.
14), and MPV (p = 0.
003, OR 0.
84, 95% CI 0.
75–0.
94) were significant independent predictors for CLI.
ROC analysis (AUC: 0.
55, 95% CI 0.
52–0.
58, p < 0.
001) showed ≤10.
2 as the best cut off value for MPV to predict CLI.
As there is a significant relationship between low MPV and a high risk for CLI in PAOD patients, MPV can be used to identify patients who are likely to develop CLI.
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