New perioperative fluid and pharmacologic management protocol results in reduced blood loss, faster return of bowel function, and overall recovery.

Cystectomy and urinary diversion have high morbidity, and strategies to reduce complications are of utmost importance. Epidural analgesia and optimized fluid management are considered key factors contributing to successful enhanced recovery after surgery. In colorectal surgery, there is strong evidence that an intraoperative fluid management aiming for a postoperative zero fluid balance results in lower morbidity including a faster return of bowel function. Recently, a randomized clinical trial focusing on radical cystectomy demonstrated that a restrictive intraoperative hydration combined with a concomitant administration of norepinephrine reduced intraoperative blood loss, the need for blood transfusion and morbidity. The purpose of this review is to highlight specific anesthesiological aspects which have been shown to improve outcome after RC with urinary diversion.

Passively Track WiFi Users with an Enhanced Particle Filter using Power-based Ranging

Passive positioning systems produce user location information for third-party providers of positioning services. Since the tracked wireless devices do not participate in the positioning process, passive positioning can only rely on simple, measurable radio signal parameters, such as timing or power information. In this work, we provide a passive tracking system for WiFi signals with an enhanced particle filter using fine-grained power-based ranging. Our proposed particle filter provides an improved likelihood function on observation parameters and is equipped with a modified coordinated turn model to address the challenges in a passive positioning system. The anchor nodes for WiFi signal sniffing and target positioning use software defined radio techniques to extract channel state information to mitigate multipath effects. By combining the enhanced particle filter and a set of enhanced ranging methods, our system can track mobile targets with an accuracy of 1.5m for 50% and 2.3m for 90% in a complex indoor environment. Our proposed particle filter significantly outperforms the typical bootstrap particle filter, extended Kalman filter and trilateration algorithms.

Non-surgical treatment of pain associated with posterior tibial tendon dysfunction: study protocol for a randomised clinical trial

BACKGROUND Symptoms associated with pes planovalgus or flatfeet occur frequently, even though some people with a flatfoot deformity remain asymptomatic. Pes planovalgus is proposed to be associated with foot/ankle pain and poor function. Concurrently, the multifactorial weakness of the tibialis posterior muscle and its tendon can lead to a flattening of the longitudinal arch of the foot. Those affected can experience functional impairment and pain. Less severe cases at an early stage are eligible for non-surgical treatment and foot orthoses are considered to be the first line approach. Furthermore, strengthening of arch and ankle stabilising muscles are thought to contribute to active compensation of the deformity leading to stress relief of soft tissue structures. There is only limited evidence concerning the numerous therapy approaches, and so far, no data are available showing functional benefits that accompany these interventions. METHODS After clinical diagnosis and clarification of inclusion criteria (e.g., age 40-70, current complaint of foot and ankle pain more than three months, posterior tibial tendon dysfunction stage I & II, longitudinal arch flattening verified by radiography), sixty participants with posterior tibial tendon dysfunction associated complaints will be included in the study and will be randomly assigned to one of three different intervention groups: (i) foot orthoses only (FOO), (ii) foot orthoses and eccentric exercise (FOE), or (iii) sham foot orthoses only (FOS). Participants in the FOO and FOE groups will be allocated individualised foot orthoses, the latter combined with eccentric exercise for ankle stabilisation and strengthening of the tibialis posterior muscle. Participants in the FOS group will be allocated sham foot orthoses only. During the intervention period of 12 weeks, all participants will be encouraged to follow an educational program for dosed foot load management (e.g., to stop activity if they experience increasing pain). Functional impairment will be evaluated pre- and post-intervention by the Foot Function Index. Further outcome measures include the Pain Disability Index, Visual Analogue Scale for pain, SF-12, kinematic data from 3D-movement analysis and neuromuscular activity during level and downstairs walking. Measuring outcomes pre- and post-intervention will allow the calculation of intervention effects by 3×3 Analysis of Variance (ANOVA) with repeated measures. DISCUSSION The purpose of this randomised trial is to evaluate the therapeutic benefit of three different non-surgical treatment regimens in participants with posterior tibial tendon dysfunction and accompanying pes planovalgus. Furthermore, the analysis of changes in gait mechanics and neuromuscular control will contribute to an enhanced understanding of functional changes and eventually optimise conservative management strategies for these patients. TRIAL REGISTRATION ClinicalTrials.gov Protocol Registration System: ClinicalTrials.gov ID NCT01839669.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.