Evidence map›Paper›PMID 41552273›Full record

ArticleAJOG global reports2026

Transabdominal ultrasound sliding sign for predicting intra-abdominal adhesions in repeat cesarean delivery: a prospective observational study from Vietnam.

Hoang Lam Vo, Lam Huong Le, Minh Phuong Nguyen, Tran Thao Nguyen Nguyen, Minh Tam Le, Vu Quoc Huy Nguyen

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Article in AJOG global reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hoang Lam VoDepartment of Obstetrics and Gynecology, University of Medicine and Pharmacy, Hue University, Hue, Vietnam (Vo, Le, T. Nguyen, Le, V. Nguyen).
Lam Huong LeDepartment of Obstetrics and Gynecology, University of Medicine and Pharmacy, Hue University, Hue, Vietnam (Vo, Le, T. Nguyen, Le, V. Nguyen).
Minh Phuong NguyenCenter of Obstetrics and Gynecology, Hue Central Hospital, Hue, Vietnam (Le, M. Nguyen).
Tran Thao Nguyen NguyenDepartment of Obstetrics and Gynecology, University of Medicine and Pharmacy, Hue University, Hue, Vietnam (Vo, Le, T. Nguyen, Le, V. Nguyen).
Minh Tam LeDepartment of Obstetrics and Gynecology, University of Medicine and Pharmacy, Hue University, Hue, Vietnam (Vo, Le, T. Nguyen, Le, V. Nguyen).
Vu Quoc Huy NguyenDepartment of Obstetrics and Gynecology, University of Medicine and Pharmacy, Hue University, Hue, Vietnam (Vo, Le, T. Nguyen, Le, V. Nguyen).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Intra-abdominal adhesions are a common complication in repeat cesarean sections and can increase surgical risks and operative time. The ultrasound sliding sign is a non-invasive technique that may help predict adhesions by assessing the movement of the uterus relative to surrounding structures, offering a safer alternative to traditional diagnostic methods. Objective: To evaluate the diagnostic accuracy of the transabdominal ultrasound sliding sign in predicting intra-abdominal adhesions and its association with maternal and neonatal outcomes in women undergoing repeat cesarean delivery in Vietnam. Methods: This prospective observational study was conducted at the Obstetrics and Gynecology Center of Hue Central Hospital from April 2022 to December 2024. The study included 400 pregnant women with a previous cesarean section scar who underwent elective repeat cesarean delivery at or beyond 28 weeks of gestation. The sliding sign was assessed using transabdominal ultrasound during the third trimester. Intra-abdominal adhesions were classified intraoperatively by blinded surgeons according to Nair's criteria as no (70.25%, 281/400), mild/moderate (13.25%,53/400), or severe (16.50%, 66/400) adhesions. A Results: The sliding sign showed strong diagnostic performance in predicting intra-abdominal adhesions. For adhesion, the area under the curve (AUC) was 79.29% (95% confidence interval [CI]: 73.91%-84.68%), sensitivity 68.91% (95% CI: 60.11-76.52), and specificity 89.68% (96% CI: 85.57-92.72). For severe adhesions, AUC was 83.48% (95% CI: 77.21-89.76), specificity was 89.68% (95% CI: 85.57-92.72) and the negative predictive value was 94.38% (95% CI: 91.96-96.80). The absence of the sliding sign was significantly more frequent in women with severe adhesions (51/66, 77.23%) compared to mild/moderate (31/53, 58.49%) and no adhesions (26/281, 10.32%) ( Conclusion: Transabdominal ultrasound assessment of the sliding sign provides a reliable, non-invasive method of predicting intra-abdominal adhesions prior to repeat cesarean delivery and is particularly useful for excluding severe adhesions. Its use can improve preoperative risk stratification, reduce maternal surgical risks, and maintain positive neonatal outcomes.

Indexed as

adhesionscesarean sectionpregnancy outcomesliding signultrasonography

Identifiers

PMID41552273
PMCPMC12809066

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.