ArticleFrontiers in cardiovascular medicine2022
Size Distribution of Microparticles: A New Parameter to Predict Acute Lung Injury After Cardiac Surgery With Cardiopulmonary Bypass.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Machine learning for predicting acute lung injury after trauma: a systematic review and meta-analysis.Frontiers in medicine · 2026Article
- Circulating Extracellular Vesicles Predict Complications after Cardiac Surgery.Journal of cardiovascular translational research · 2025Review
- Effects of Ulinastatin on Inflammation Response and Lung Tissue Injury in Deep Hypothermic Circulatory Arrest.Interdisciplinary cardiovascular and thoracic surgery · 2025Article
- A Simple Modification Results in a Significant Improvement in Measuring the Size of Extracellular Vesicles.Current medical science · 2025Article
- Circulating extracellular microvesicles associated with electronic cigarette use increase endothelial cell inflammation and reduce nitric oxide production.Experimental physiology · 2024Article
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Authors and funding
12 authors.
Funding
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Abstract
Background: Acute lung injury (ALI) is a common complication after cardiac surgery with cardiopulmonary bypass (CPB). No precise way, however, is currently available to predict its occurrence. We and others have demonstrated that microparticles (MPs) can induce ALI and were increased in patients with ALI. However, whether MPs can be used to predict ALI after cardiac surgery with CPB remains unknown. Methods: In this prospective study, 103 patients undergoing cardiac surgery with CPB and 53 healthy subjects were enrolled. MPs were isolated from the plasma before, 12 h after, and 3 d after surgery. The size distributions of MPs were measured by the LitesizerTM 500 Particle Analyzer. The patients were divided into two subgroups (ALI and non-ALI) according to the diagnosis of ALI. Descriptive and correlational analyzes were conducted between the size distribution of MPs and clinical data. Results: Compared to the non-ALI group, the size at peak and interquartile range (IQR) of MPs in patients with ALI were smaller, but the peak intensity of MPs is higher. Multivariate logistic regression analysis indicated that the size at peak of MPs at postoperative 12 h was an independent risk factor for ALI. The area under the curve (AUC) of peak diameter at postoperative 12 h was 0.803. The best cutoff value of peak diameter to diagnose ALI was 223.05 nm with a sensitivity of 88.0% and a negative predictive value of 94.5%. The AUC of IQR at postoperative 12 h was 0.717. The best cutoff value of IQR to diagnose ALI was 132.65 nm with a sensitivity of 88.0% and a negative predictive value of 92.5%. Combining these two parameters, the sensitivity reached 92% and the negative predictive value was 96%. Conclusions: Our findings suggested that the size distribution of MPs could be a novel biomarker to predict and exclude ALI after cardiac surgery with CPB.
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