Self-expanding metal stents in postoperative esophageal leaks

Background: Postoperative esophageal leaks have a high morbidity and mortality. Self-expanding metal stents (SEMS) have been used as an alternative to re-operation. Aim: Evaluating predictors of success of SEMS in postoperative esophageal leaks. Methods: Retrospective study of patients with postoperative esophageal leaks referred for SEMS placement in a reference center during a period of 3 years. Technical success was defined as closure of the leak in barium swallow at 15 days. Clinical success was considered as endoscopic and/or radiographic confirmation of closure after stent removal. Results: Thirteen patients placed SEMS. Median follow-up was 58 days. Leaks had a median size of 20 mm. Time between surgery and SEMS placement was 20 days. One patient died 2 days after SEMS placement and one had worsening of the fistula after SEMS expansion. Time till stent migration was 9 days. Technical success was achieved in 9 of 11 patients, with clinical success without recurrence in 5 patients. All leaks with less than 20 mm were solved endoscopically. Technical and clinical success was higher when time between surgery and SEMS placement was lower, even though without statistical significance (respectively, p = 0.228 and 0.374). In the 8 patients who died during follow-up, median survival was 59 days. Conclusions: Technical success of SEMS was higher than 80%; however, due to high morbidity and mortality, only 45% of patients had their stent removed. Lower time from diagnosis to SEMS placement and leak size less than 20 mm may be associated with better results.

Toward Self-Organising Service Communities

This paper discusses a framework in which catalog service communities are built, linked for interaction, and constantly monitored and adapted over time. A catalog service community (represented as a peer node in a peer-to-peer network) in our system can be viewed as domain specific data integration mediators representing the domain knowledge and the registry information. The query routing among communities is performed to identify a set of data sources that are relevant to answering a given query. The system monitors the interactions between the communities to discover patterns that may lead to restructuring of the network (e.g., irrelevant peers removed, new relationships created, etc.).