The effectiveness of preoperative diagnostic methods in predicting intra-abdominal adhesions before repeat cesarean section delivery

术前诊断方法在预测再次剖宫产前腹腔内粘连方面的有效性

阅读:1

Abstract

OBJECTIVE: This study aimed to evaluate the effectiveness of skin appearance, striae gravidarum severity, and ultrasonographic "sliding sign" in predicting preoperative adhesions before repeat cesarean section delivery on the same patient and find the most useful one. METHODS: This was a prospective cohort study conducted on pregnant women with a history of cesarean section delivery. Davey's scoring system was used for stria evaluation. The scar was assessed using their visual appearance, and transabdominal ultrasonography was applied to detect sliding sign existence. Surgeons blinded to preoperative assessment graded the severity of intra-abdominal adhesions intraoperatively using Nair's scoring system. RESULTS: Of the 164 pregnant women with at least one previous cesarean section delivery, 73 (44.5%) had filmy or dense intra-abdominal adhesions. Statistically significant association was found between three groups regarding parity, previous cesarean number, scar appearance, total stria score, and sliding sign existence. Negative sliding sign had a likelihood ratio of 4.198 (95%CI 1.178-14.964) for the detection of intra-abdominal adhesions. Stria score and scar appearance were also valuable for detection adhesions with likelihood ratios of 1.518 (95%CI 1.045-2.205) and 2.405 (95%CI 0.851-6.796), respectively. After receiver operator characteristics curve analysis, striae score cutoff value in adhesion prediction was determined as 3.5. CONCLUSION: Stria score, scar appearance, and sliding sign are all significant predictors for intraperitoneal adhesions, and sliding sign, as an easy-to-apply, inexpensive, useful sonographic marker, is the most effective adhesion predictor before repeat cesarean section delivery compared to other known adhesion markers.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。