Histological criteria for encapsulating peritoneal sclerosis - a standardized approach.

Histological criteria for encapsulating peritoneal sclerosis - a standardized approach.
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DOI:
10.1371/journal.pone.0048647
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Alscher MD
Alscher MD
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Braun N;Fritz P;Ulmer C;Latus J;Kimmel M;Biegger D;Ott G;Reimold F;Thon KP;Dippon J;Segerer S;Alscher MD

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与长期腹膜透析(PD)最相关的两种病理疾病是单纯性硬化症和包裹性腹膜硬化症(EPS)。这两个实体在组织学上的区别是困难的。本研究的目的是建立一种标准化和便于鉴别单纯性硬化和EPS的方法。我们调查了58例腹膜活检--31例EPS和27例PD患者。两名盲人研究人员分析了EPS和PD患者的20个组织学特征。以下表现在帕金森病患者中明显更为常见:成纤维细胞样细胞(p<0.0001)、间皮细胞剥脱(p<0.0001)、细胞密度降低(p<0.008)、纤维蛋白沉积(p<0.008)、铁沉积(p<0.05)、足普兰血管(p<0.0001)、足普兰无血管(p<0.0001)。利用所有的预测变量,我们训练了随机森林分类方法来对未来的病例进行分类。足普兰血管和无血管结合在一起(p<0.0001)、FLC(p<0.0001)、间皮剥脱(p = 0.0005)、钙化(p = 0.0026)、无细胞面积(p = 0.0094)和纤维蛋白沉积(p = 0.0336)显示为显著的重要预测变量。在对新病例进行分类时,估计错误分类错误率为14%。引入的统计方法允许区分单纯性硬化症和EPS。随着数据库中每增加一个新病例,错误分类错误可能会有所改善。
The two most relevant pathologies of long-term peritoneal dialysis (PD) are simple sclerosis and encapsulating peritoneal sclerosis (EPS). The histological differentiation of those two entities is difficult. The Aim of the study was to establish a method to standardize and facilitate the differentiation between simple sclerosis and EPS We investigated 58 peritoneal biopsies - 31 EPS patients and 27 PD patients. Two blinded investigators analyzed 20 histological characteristics in EPS and PD patients. The following findings were significantly more common in EPS than in patients on PD without EPS: fibroblast like cells (FLC) (p<0.0001), mesothelial denudation (p<0.0001), decreased cellularity (p = 0.008), fibrin deposits (p<0.03), Fe deposits (p = 0.05), podoplanin vascular (p<0.0001), podoplanin avascular (p<0.0001). Using all predictor variables we trained the classification method Random Forest to categorize future cases. Podoplanin vascular and avascular were taken together (p<0.0001), FLC (p<0.0001), mesothelial denudation (p = 0.0005), calcification (p = 0.0026), acellular areas (p = 0.0094), and fibrin deposits (p = 0.0336) showed up as significantly important predictor variables. Estimated misclassification error rate when classifying new cases turned out to be 14%. The introduced statistical method allows discriminating between simple sclerosis and EPS. The misclassification error will likely improve with every new case added to the database.
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