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Background: Local wound complications are among the most relevant sequelae after an abdominoperineal resection (APR) for low rectal cancer. One of the proposed techniques to improve the postoperative recovery and to accelerate the initiation of adjuvant chemotherapy is the mesh reinforcement of the perineal wound. The aim of the current study is to compare the surgical and oncological outcomes after APR performed with a biosynthetic mesh reconstruction versus the conventional procedure., Methods: From 2015 to 2020, in two tertiary centres, the surgical outcomes, the wound events (i.e., surgical site infections, wound dehiscence and the complete healing time) and the oncological outcomes (i.e., time length to start adjuvant chemo-radiotherapy, an over 8-week delay in chemotherapy and the recurrence rate) were retrospectively analysed in patients undergoing APR reinforced with biosynthetic mesh (Group A) and conventional APR (Group B). Results Sixty-one patients were treated with APR (25 in Group A and 36 in Group B). Patients in Group A presented lower time for: healing (16 versus 24 days, p = 0.015), inferior perineal wound dehiscence rates (one versus nine cases, p = 0.033), an earlier adjuvant therapy start (26 versus 70 days, p = 0.003) and a lower recurrence rate (16.6% vs. 33.3%, p = 0.152)., Conclusions: In our series, the use of a biosynthetic mesh for the neo-perineum reconstruction after a Miles' procedure has resulted in safe, reproducible results affected by limited complications, guarantying a rapid start of the adjuvant therapy with clear benefits in oncological outcomes. Further randomized clinical trials with long-term follow-up are needed to validate these results.

Background and Objectives: Recurrent laryngeal nerve (RLN) paralysis is a fearful complication during thyroidectomy. Intraoperative neuromonitoring (IONM) and optical magnification (OM) facilitate RLN identification and dissection. The purpose of our study was to evaluate the influence of the two techniques on the incidence of RLN paralysis and determine correlations regarding common outcomes in thyroid surgery. Materials and Methods: Two equally sized groups of 50 patients who underwent total thyroidectomies were examined. In the first group (OM), only surgical binocular loupes (2.5×−4.5×) were used during surgery, while in the second group (IONM), the intermittent NIM was applied. Results: Both the operative time and the length of hospitalization were shorter in the OM group than in the IONM group (median 80 versus 100 min and median 2 versus 4 days, respectively) (p < 0.05). The male patients were found to have a five-fold higher risk of developing transient dysphonia than the females (adjusted OR 5.19, 95% IC 0.99−27.18, p = 0.05). The OM group reported a four-fold higher risk of developing transient hypocalcemia than the IONM group (OR 3.78, adjusted OR 4.11, p = 0.01). Despite two cases of temporary bilateral RLN paralysis in the IONM group versus none in the OM group, no statistically significant difference was found (p > 0.05). No permanent RLN paralysis or hypoparathyroidism have been reported. Conclusions: Despite some limitations, our study is the first to compare the use of IONM with OM alone in the prevention of RLN injuries. The risk of recurrent complications remains comparable and both techniques can be considered valid instruments, especially if applied simultaneously by surgeons.

Sensing devices are increasingly being deployed to monitor the physical world around us. One class of application for which sensor data is pertinent is environmental decision support systems, e.g., flood emergency response. For these applications, the sensor readings need to be put in context by integrating them with other sources of data about the surrounding environment. Traditional systems for predicting and detecting floods rely on methods that need significant human resources. In this paper we describe a semantic sensor web architecture for integrating multiple heterogeneous datasets, including live and historic sensor data, databases, and map layers. The architecture provides mechanisms for discovering datasets, defining integrated views over them, continuously receiving data in real-time, and visualising on screen and interacting with the data. Our approach makes extensive use of web service standards for querying and accessing data, and semantic technologies to discover and integrate datasets. We demonstrate the use of our semantic sensor web architecture in the context of a flood response planning web application that uses data from sensor networks monitoring the sea-state around the coast of England.