Department of Pediatrics, Chang Gung Memorial Hospital, Keelung, Taiwan; Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Division of Pediatric Pulmonology, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
Department of Clinical Proteomics Center, Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Taoyuan, Taiwan.
J Microbiol Immunol Infect. 2015 Oct;48(5):483-9. doi: 10.1016/j.jmii.2013.11.013. Epub 2014 Feb 21.
BACKGROUND/PURPOSE: Infectious parapneumonic effusion (PE) contains proteins originating from circulation as well as proteins locally released by inflammatory pulmonary cells. The purpose of this study was to investigate the value of total protein analysis in guiding management of infectious PE by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
Fifty-seven children with pneumonia followed by PE were consecutively enrolled into our study. Protein profiles generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry after fractionating samples with functionalized magnetic beads (C8) were used for differentiating complicated PE (CPE) from non-CPE. A training set was used to generate classification models and the clinical efficacy of these models in detecting CPE and the need for intervention was then evaluated in an independent set.
The MS spectra derived from PE were analyzed, and classification models were constructed in the training set. A total of 123 mass/charge (m/z) values were identified and 23 m/z values which were significant with p < 0.05 were used as classifiers. An optimized genetic algorithm model containing enforced selection of three significant downregulated m/z values (2127, 2232, and 2427) was able to classify CPE with 100% positive predictive value and predict the need of aggressive therapeutic intervention with 77% positive predictive value.
A diagnostic model construction comprising three potential biomarkers can predict CPE and need for surgical intervention rapidly and precisely. Pleural fluid proteins downregulated during the progression of pneumonia could potentially guide the management of infectious PE.
背景/目的:感染性肺炎旁胸腔积液(PE)中含有源自循环的蛋白质以及由炎症性肺细胞局部释放的蛋白质。本研究旨在通过基质辅助激光解吸/电离飞行时间质谱法来研究总蛋白分析在指导感染性 PE 管理中的价值。
连续纳入 57 例肺炎后继发 PE 的儿童。使用功能化磁珠(C8)对样品进行分级后,基质辅助激光解吸/电离飞行时间质谱法生成的蛋白质谱用于区分复杂性 PE(CPE)和非 CPE。使用训练集生成分类模型,然后在独立集中评估这些模型在检测 CPE 和干预需求方面的临床疗效。
分析了来自 PE 的 MS 光谱,并在训练集中构建了分类模型。共鉴定出 123 个质荷比(m/z)值,其中 23 个 m/z 值与 p<0.05 有显著差异,被用作分类器。一个包含强制选择三个显著下调的 m/z 值(2127、2232 和 2427)的优化遗传算法模型能够以 100%的阳性预测值分类 CPE,并以 77%的阳性预测值预测需要积极的治疗干预。
由三个潜在生物标志物组成的诊断模型可以快速、准确地预测 CPE 和手术干预的需求。肺炎进展过程中下调的胸腔积液蛋白可能有助于指导感染性 PE 的管理。