Bogado Pascottini Osvaldo, Hostens Miel, Dini Pouya, Vandepitte Jan, Ducatelle Richard, Opsomer Geert
Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Merelbeke, Belgium.
Theriogenology. 2016 Oct 1;86(6):1550-1556. doi: 10.1016/j.theriogenology.2016.05.014. Epub 2016 May 26.
The aim of the present study was to compare endometrial cytology with histopathology to diagnose subclinical endometritis (SCE) in dairy cows. Endometrial cytology samples were collected from Holstein-Friesian cows (n = 32) just before slaughtering. Half of them were obtained by in vivo cytobrush (IV-CB), whereas the other half by in vivo low-volume lavage (IV-LVL). After slaughtering, reproductive tracts were collected, and the endometrium was sampled at eight locations. At each location, both a ex vivo cytobrush sample (EV-CB) and a tissue sample for histopathologic examination were taken. In the histopathology slides, polymorphonuclear (PMN) cell counts were differentiated as PMN cells in direct contact with the epithelial cells of the endometrium (PMN-EP), and PMN cells present in the deeper stratum compactum (PMN-SC). Summation of both countings was referred to as PMN-total. Pearson's correlation and Cohen's kappa coefficient were used to assess the correlation and agreement between both sampling methods (in vivo cytology [IV-CB and IV-LVL] with EV-CB and PMN-total). A Poisson mixed effect model was used to analyze the PMN cells' distribution. The prevalence of SCE was 18.75% (n = 6/32) for in vivo cytology. The SCE prevalence based on EV-CB analyses and on the assessment of PMN-total was determined both at the sample (n = 256) as well as at the cow level (n = 32): EV-CB 25% (n = 64/256) and 35.5% (n = 12/32), and PMN-total 37.11% (n = 95/256) and 59.38% (n = 19/32). Correlation and agreement between IV-CB and EV-CB were r = 0.81 and k = 0.97, whereas between IV-CB and PMN-total r = 0.15 and k = 0.23, respectively. In vivo low-volume lavage correlation and agreement were r = 0.52 and k = 0.66 with EV-CB, and r = 0.45 and k = 0.44 with PMN-total. Moreover, correlation and agreement between EV-CB and PMN-total were r = 0.60 and k = 0.50, respectively. More PMN cells (P < 0.05) were detected in PMN-SC when compared to PMN-EP and EV-CB. A higher SCE prevalence was found using histopathology, rendering the latter as a more sensitive method to diagnose SCE in comparison to in vivo and ex vivo cytology. Although cytology had low and/or moderate sensitivity to diagnose SCE when compared with histopathology, its specificity is 100%, implying that all cows that were indicated to suffer from SCE using in vivo cytology were confirmed to do so by histopathologic examination. There is an uneven distribution of PMN cells throughout the endometrium, generally more PMN cells being found in the deeper stratum compactum than in contact with the superficial layers of the endometrium.
本研究的目的是比较子宫内膜细胞学与组织病理学在诊断奶牛亚临床子宫内膜炎(SCE)方面的差异。在即将屠宰前,从荷斯坦 - 弗里生奶牛(n = 32)采集子宫内膜细胞学样本。其中一半通过体内细胞刷(IV - CB)采集,另一半通过体内低容量灌洗(IV - LVL)采集。屠宰后,收集生殖道,并在八个部位采集子宫内膜样本。在每个部位,同时采集体外细胞刷样本(EV - CB)和用于组织病理学检查的组织样本。在组织病理学切片中,多形核(PMN)细胞计数分为直接与子宫内膜上皮细胞接触的PMN细胞(PMN - EP)和存在于较深致密层的PMN细胞(PMN - SC)。两种计数的总和称为PMN总数。使用Pearson相关性和Cohen卡方系数评估两种采样方法(体内细胞学[IV - CB和IV - LVL]与EV - CB和PMN总数)之间的相关性和一致性。使用泊松混合效应模型分析PMN细胞的分布。体内细胞学诊断的SCE患病率为18.75%(n = 6/32)。基于EV - CB分析和PMN总数评估的SCE患病率在样本(n = 256)以及奶牛水平(n = 32)上均有确定:EV - CB分别为25%(n = 64/256)和35.5%(n = 12/32),PMN总数分别为37.11%(n = 95/256)和59.38%(n = 19/32)。IV - CB与EV - CB之间的相关性和一致性分别为r = 0.81和k = 0.97,而IV - CB与PMN总数之间的相关性和一致性分别为r = 0.15和k = 0.23。体内低容量灌洗与EV - CB的相关性和一致性分别为r = 0.52和k = 0.66,与PMN总数的相关性和一致性分别为r = 0.45和k = 0.44。此外,EV - CB与PMN总数之间的相关性和一致性分别为r = 0.60和k = 0.50。与PMN - EP和EV - CB相比,在PMN - SC中检测到更多的PMN细胞(P < 0.05)。使用组织病理学发现SCE患病率更高,这表明与体内和体外细胞学相比,组织病理学是诊断SCE更敏感的方法。尽管与组织病理学相比,细胞学诊断SCE的敏感性较低和/或中等,但其特异性为100%,这意味着所有通过体内细胞学表明患有SCE的奶牛经组织病理学检查均被证实患病。PMN细胞在整个子宫内膜中分布不均,通常在较深的致密层中发现的PMN细胞比与子宫内膜表层接触的更多。