13,654 research outputs found
Opioid PrEscRiptions and usage After Surgery (OPERAS): protocol for a prospective multicentre observational cohort study of opioid use after surgery
No full textIntroductionPostoperative pain is common and frequently addressed through opioid analgesia. This practice must balance the benefits of achieving adequate pain relief against the harms of adverse effects such as opioid-induced ventilatory impairment and opioid use disorder. This student and trainee-led collaborative study aims to investigate and compare the prescription versus consumption of opioids at 7 days postdischarge after common surgical procedures and their impact on patient-reported outcomes regarding postoperative pain.Methods and analysisThis is a prospective multicentre observational cohort study of surgical patients in Australia, Aotearoa New Zealand and select international sites, conducted by networks of students, trainees and consultants. Consecutive adult patients undergoing common elective and emergency general, orthopaedic, gynaecological and urological surgical procedures are eligible for inclusion, with follow-up 7 days after hospital discharge. The primary outcome will be the proportion of prescribed opioids consumed by patients at 7 days postdischarge. Secondary outcomes will include patient-reported quality of life and satisfaction scores, rate of non-opioid analgesic use, rate of continuing use of opioids at follow-up, rates of opioid prescription from other sources and hospital readmissions at 7 days postdischarge for opioid related side-effects or surgery-related pain. Descriptive and multivariate analyses will be conducted to investigate factors associated with opioid requirements and prescription-consumption discrepancies.Ethics and disseminationOPERAS has been approved in Australia by the Hunter New England Human Research Ethics Committee (Protocol 2021/ETH11508) and by the Southern Health and Disability Ethics Committee (2021 EXP 11199) in Aotearoa New Zealand. Results will be submitted for conference presentation and peer-reviewed publication. Centre-level data will be distributed to participating sites for internal audit
Impact of Opioid-Free Analgesia on Pain Severity and Patient Satisfaction After Discharge From Surgery: Multispecialty, Prospective Cohort Study in 25 Countries
No full textBACKGROUND: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.
METHODS: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.
RESULTS: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P \u3c 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (β coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.
CONCLUSION: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely
Exploratory talk within collaborative small groups in mathematics
No full textThis report describes one aspect of a wider research study on exploratory talk within collaborative small groups in secondary mathematics lessons. It outlines students’ views of using collaborative activity to learn mathematics. The fuller research study explores the extent to which exploratory talk occurs in collaborative peer groups in secondary mathematics classrooms
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Collaborative Educational Systems in the Virtual Environment
No full textThe work leads to an original approach to the construction of collaborative systems metrics. The approach is based both on research already conducted by the author, on the experimental results obtained, and the foundation taken from the specific literature. The collaborative systems in knowledgebased economy are formalized and their characteristics are identified. The virtual campus structure is described and a comparison with the classical university is achieved. The architecture of virtual is designed and the categories of agents in virtual campus are analyzed.
Collaborative gym: A simulation benchmark for multi-robotic tasks
No full textThe design of multi-robot systems has gained increasing attention in recent years. The field of cooperative Multi-Agent Robot Systems (MARS) has shown the potential to provide reliable and cost-effective solutions to a wide range of automated applications. Communication and coordination between autonomous agents require robust and intelligent control systems in order to achieve high-quality performance. This paper presents Collaborative Gym, an open-source, physics-based simulation framework for multi-robot interaction. This simulation environment differs from existing robotic simulation environments in that it is designed to model the interaction between multiple robots. Despite the presence of a large number of single robotic environments, multi-robotic simulation environments for reinforcement learning are rare. Collaborative Gym contains four simulated tasks in which different commercial robots work in collaboration: poking, lifting, balancing, and passing. For each of the four tasks, baseline policies are presented for various combinations of commercial robots which have been trained using reinforcement learning. The study demonstrated that Collaborative Gym is a promising open-source framework for the development of multi-robotic collaborative robotic tasks.https://github.com/gabriansa/collaborative-gymMechanical Engineering | Multi-Machine Engineerin
Bayesian latent variable models for collaborative item rating prediction
No full textCollaborative filtering systems based on ratings make it easier for users to find content of interest on the Web and as such they constitute an area of much research. In this paper we first present a Bayesian latent variable model for rating prediction that models ratings over each user's latent interests and also each item's latent topics. We describe a Gibbs sampling procedure that can be used to estimate its parameters and show by experiment that it is competitive with the gradient descent SVD methods commonly used in state-of-the-art systems. We then proceed to make an important and novel extension to this model, enhancing it with user-dependent and item-dependant biases to significantly improve rating estimation. We show by experiment on a large set of real ratings data that these models are able to outperform 3 common baselines, including a very competitive and modern SVD-based model. Furthermore we illustrate other advantages of our approach beyond simply its ability to provide more accurate ratings and show that it is able to perform better on the common and important case where the user profile is short
Collaborative Systems – Finite State Machines
No full textIn this paper the finite state machines are defined and formalized. There are presented the collaborative banking systems and their correspondence is done with finite state machines. It highlights the role of finite state machines in the complexity analysis and performs operations on very large virtual databases as finite state machines. It builds the state diagram and presents the commands and documents transition between the collaborative systems states. The paper analyzes the data sets from Collaborative Multicash Servicedesk application and performs a combined analysis in order to determine certain statistics. Indicators are obtained, such as the number of requests by category and the load degree of an agent in the collaborative system.Collaborative System, Finite State Machine, Inputs, States, Outputs
Assessment of (computer-supported) collaborative learning
No full textWithin the Computer-Supported Collaborative Learning (CS)CL research community there has been an extensive dialogue on theories and perspectives on learning from collaboration, approaches to scaffold (script) the collaborative process, and most recently research methodology. In contrast, the issue of assessment of collaborative learning has received much less attention. This article discusses how assessment of collaborative learning has been addressed, provides a perspective on what could be assessed, and highlights limitations of current approaches. Since assessment of collaborative learning is a demanding experience for teachers and students alike, they require adequate computer-supported and intelligent tools for monitoring and assessment. A roadmap for the role and application of intelligent tools for assessment of (CS)CL is presented
iBingo mobile collaborative search
No full textThis paper describes a collaborative video search system for mobile devices, 'iBingo'. It supports division of labour among users, providing search results to colocated iPod Touch devices
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