首页> 外文期刊>Journal of Thoracic Disease >Galactomannan detection in bronchoalveolar lavage fluid corrected by urea dilution for the diagnosis of invasive pulmonary aspergillosis among nonneutropenic patients
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Galactomannan detection in bronchoalveolar lavage fluid corrected by urea dilution for the diagnosis of invasive pulmonary aspergillosis among nonneutropenic patients

机译:尿素稀释校正的支气管肺泡灌洗液中半乳甘露聚糖检测,以诊断非中性粒细胞减少性患者的侵袭性肺曲霉病

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Background: To investigate the diagnostic performance of galactomannan (GM) detection in bronchoalveolar lavage fluid (BALF) corrected by urea dilution and modification of the AspICU clinical algorithm. Methods: GM detection in serum and BALF samples was performed in nonneutropenic patients on the day of clinically suspected invasive pulmonary aspergillosis (IPA) between January 2016 and June 2018, and urea was measured in the plasma and BALF. The BALF GM concentration was corrected by urea dilution, and receiver operating characteristic (ROC) curves were generated to determine the optimal cut-off value. Results: A total of 184 patients who were suspected of IPA, were enrolled in this prospective study together with 30 patients with lung cancer as a control group. Seventy-eight patients were diagnosed with IPA, including 37 who were verified by pathology. The urea plasma-to-urea BALF ratio in the IPA group [4.18 (IQR, 3.52–4.91)] was greater than that in the non-IPA group [3.42 (IQR, 3.12–3.76), P Conclusions: The corrected BALF GM was valuable for diagnosing IPA in nonneutropenic patients. The modified AspICU clinical algorithm based on this measurement represents a reliable diagnostic instrument in clinical settings.
机译:背景:探讨半乳甘露聚糖(GM)检测在尿素稀释和改良AspICU临床算法校正后的支气管肺泡灌洗液(BALF)中的诊断性能。方法:在2016年1月至2018年6月的临床怀疑为侵袭性肺曲霉病(IPA)当天,对非中性粒细胞减少的患者进行血清和BALF样品中的GM检测,并在血浆和BALF中测定尿素。通过尿素稀释校正BALF GM浓度,并生成接收器工作特性(ROC)曲线以确定最佳临界值。结果:总共184例疑似IPA的患者入选了该前瞻性研究,其中30例肺癌患者作为对照组。诊断为IPA的患者共78例,其中37例经病理证实。 IPA组[4.18(IQR,3.52–4.91)]的尿素血浆/尿素BALF比值大于非IPA组[3.42(IQR,3.12–3.76)],P结论:校正后的BALF GM对于非中性粒细胞减少症患者的IPA诊断具有重要意义。基于此测量值的改进的AspICU临床算法代表了在临床环境中可靠的诊断工具。

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