41 research outputs found

    Transperineal repair of obstetric-related anovaginal fistula

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    The definitive version is available at www.blackwell-synergy.comBackground: To describe an operative technique for the repair of anovaginal fistulae secondary to obstetric injury and to assess its functional outcome and patient satisfaction. Methods: An operative repair involving division of the anovaginal fistula, closure of rectal and vaginal walls, anterior levatoplasty and overlapping sphincteroplasty is described. Postoperative complications and recurrence were recorded. A telephone interview was carried out to assess the functional outcome and the satisfaction score. Results: Seven consecutive patients had a repair of an obstetric-related anovaginal fistula. Their mean age was 34 years (range: 22–72). They had a mean duration of symptoms of 14 months (range: 1.5–54). Four patients did not have any previous repair and no stoma was necessary in any of the seven patients. There was no significant postoperative complication and only one recurrence. Telephone interviews were conducted for six patients and one was lost to follow-up. The mean follow-up period was 24 months (11–35). The Wexner's continence score improved from a mean preoperative score of 13.4 to a mean postoperative score of 5.6. With satisfaction scores ranging from +3 to −3 (+3 indicating complete satisfaction and −3 indicating complete dissatisfaction), five patients scored 1 and one scored 0. Conclusion: This technique is straightforward and effective in healing obstetric-related anovaginal fistula. It achieves improved continence and reasonable satisfaction.Anovaginal fistula; obstetric; sphincter repair; transperineal repai

    Intrinsic Point Cloud Interpolation via Dual Latent Space Navigation

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    We present a learning-based method for interpolating and manipulating 3D shapes represented as point clouds, that is explicitly designed to preserve intrinsic shape properties. Our approach is based on constructing a dual encoding space that enables shape synthesis and, at the same time, provides links to the intrinsic shape information, which is typically not available on point cloud data. Our method works in a single pass and avoids expensive optimization, employed by existing techniques. Furthermore, the strong regularization provided by our dual latent space approach also helps to improve shape recovery in challenging settings from noisy point clouds across different datasets. Extensive experiments show that our method results in more realistic and smoother interpolations compared to baselines
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