Chronic pain assessments in children and adolescents : a systematic literature review of the selection, administration, interpretation, and reporting of unidimensional pain intensity scales

Background. Advances in pain assessment approaches now indicate which measures should be used to capture chronic pain experiences in children and adolescents. However, there is little guidance on how these tools should best be administered and reported, such as which time frames to use or how pain scores are categorised as mild, moderate, or severe. Objective. To synthesise current evidence on unidimensional, single-item pain intensity scale selection, administration, interpretation, and reporting. Methods. Databases were searched (inception: 18 January 2016) for studies in which unidimensional pain intensity assessments were used with children and adolescents with chronic pain. Ten quality criteria were developed by modifying existing recommendations to evaluate the quality of administration of pain scales most commonly used with children. Results. Forty-six studies met the inclusion criteria. The highest score achieved was 7 out of a possible 10 (median: 5; IQR: 4–6). Usage of scales varied markedly in administrator/completer, highest anchors, number of successive assessments, and time referent periods used. Conclusions. Findings suggest these scales are selected, administered, and interpreted inconsistently, even in studies of the same type. Furthermore, methods of administration are rarely reported or justified making it impossible to compare findings across studies. This article concludes by recommending criteria for the future reporting of paediatric chronic pain assessments in studies

Ordinary-derivative formulation of conformal totally symmetric arbitrary spin bosonic fields

Conformal totally symmetric arbitrary spin bosonic fields in flat space-time of even dimension greater than or equal to four are studied. Second-derivative (ordinary-derivative) formulation for such fields is developed. We obtain gauge invariant Lagrangian and the corresponding gauge transformations. Gauge symmetries are realized by involving the Stueckelberg and auxiliary fields. Realization of global conformal boost symmetries on conformal gauge fields is obtained. Modified de Donder gauge condition and de Donder-Stueckelberg gauge condition are introduced. Using the de Donder-Stueckelberg gauge frame, equivalence of the ordinary-derivative and higher-derivative approaches is demonstrated. On-shell degrees of freedom of the arbitrary spin conformal field are analyzed. Ordinary-derivative light-cone gauge Lagrangian of conformal fields is also presented. Interrelations between the ordinary-derivative gauge invariant formulation of conformal fields and the gauge invariant formulation of massive fields are discussed.Comment: 51 pages, v2: Results and conclusions of v1 unchanged. In Sec.3, brief review of higher-derivative approaches added. In Sec.4, new representations for Lagrangian, modified de Donder gauge, and de Donder-Stueckelberg gauge added. In Sec.5, discussion of interrelations between the ordinary-derivative and higher-derivative approaches added. Appendices A,B,C,D and references adde

Structural insights into the role of the Smoothened cysteine-rich domain in Hedgehog signalling.

Smoothened (Smo) is a member of the Frizzled (FzD) class of G-protein-coupled receptors (GPCRs), and functions as the key transducer in the Hedgehog (Hh) signalling pathway. Smo has an extracellular cysteine-rich domain (CRD), indispensable for its function and downstream Hh signalling. Despite its essential role, the functional contribution of the CRD to Smo signalling has not been clearly elucidated. However, given that the FzD CRD binds to the endogenous Wnt ligand, it has been proposed that the Smo CRD may bind its own endogenous ligand. Here we present the NMR solution structure of the Drosophila Smo CRD, and describe interactions between the glucocorticoid budesonide (Bud) and the Smo CRDs from both Drosophila and human. Our results highlight a function of the Smo CRD, demonstrating its role in binding to small-molecule modulators

Multi-site evaluation of a computer aided detection (CAD) algorithm for small acute intra-cranial hemorrhage and development of a stand-alone CAD system ready for deployment in a clinical environment

Timely detection of Acute Intra-cranial Hemorrhage (AIH) in an emergency environment is essential for the triage of patients suffering from Traumatic Brain Injury. Moreover, the small size of lesions and lack of experience on the reader's part could lead to difficulties in the detection of AIH. A CT based CAD algorithm for the detection of AIH has been developed in order to improve upon the current standard of identification and treatment of AIH. A retrospective analysis of the algorithm has already been carried out with 135 AIH CT studies with 135 matched normal head CT studies from the Los Angeles County General Hospital/ University of Southern California Hospital System (LAC/USC). In the next step, AIH studies have been collected from Walter Reed Army Medical Center, and are currently being processed using the AIH CAD system as part of implementing a multi-site assessment and evaluation of the performance of the algorithm. The sensitivity and specificity numbers from the Walter Reed study will be compared with the numbers from the LAC/USC study to determine if there are differences in the presentation and detection due to the difference in the nature of trauma between the two sites. Simultaneously, a stand-alone system with a user friendly GUI has been developed to facilitate implementation in a clinical setting. © 2010 Copyright SPIE - The International Society for Optical Engineering.published_or_final_versio

Views from within a narrative : Evaluating long-term human-robot interaction in a naturalistic environment using open-ended scenarios

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. Date of acceptance: 16/06/2014This article describes the prototyping of human–robot interactions in the University of Hertfordshire (UH) Robot House. Twelve participants took part in a long-term study in which they interacted with robots in the UH Robot House once a week for a period of 10 weeks. A prototyping method using the narrative framing technique allowed participants to engage with the robots in episodic interactions that were framed using narrative to convey the impression of a continuous long-term interaction. The goal was to examine how participants responded to the scenarios and the robots as well as specific robot behaviours, such as agent migration and expressive behaviours. Evaluation of the robots and the scenarios were elicited using several measures, including the standardised System Usability Scale, an ad hoc Scenario Acceptance Scale, as well as single-item Likert scales, open-ended questionnaire items and a debriefing interview. Results suggest that participants felt that the use of this prototyping technique allowed them insight into the use of the robot, and that they accepted the use of the robot within the scenarioPeer reviewe

To test or to treat? an analysis of influenza testing and Antiviral treatment strategies using economic computer modeling

Background: Due to the unpredictable burden of pandemic influenza, the best strategy to manage testing, such as rapid or polymerase chain reaction (PCR), and antiviral medications for patients who present with influenza-like illness (ILI) is unknown. Methodology/Principal Findings: We developed a set of computer simulation models to evaluate the potential economic value of seven strategies under seasonal and pandemic influenza conditions: (1) using clinical judgment alone to guide antiviral use, (2) using PCR to determine whether to initiate antivirals, (3) using a rapid (point-of-care) test to determine antiviral use, (4) using a combination of a point-of-care test and clinical judgment, (5) using clinical judgment and confirming the diagnosis with PCR testing, (6) treating all with antivirals, and (7) not treating anyone with antivirals. For healthy younger adults (<65 years old) presenting with ILI in a seasonal influenza scenario, strategies were only cost-effective from the societal perspective. Clinical judgment, followed by PCR and point-of-care testing, was found to be cost-effective given a high influenza probability. Doubling hospitalization risk and mortality (representing either higher risk individuals or more virulent strains) made using clinical judgment to guide antiviral decision-making cost-effective, as well as PCR testing, point-of-care testing, and point-of-care testing used in conjunction with clinical judgment. For older adults (≥65 years old), in both seasonal and pandemic influenza scenarios, employing PCR was the most cost-effective option, with the closest competitor being clinical judgment (when judgment accuracy ≥50%). Point-of-care testing plus clinical judgment was cost-effective with higher probabilities of influenza. Treating all symptomatic ILI patients with antivirals was cost-effective only in older adults. Conclusions/Significance: Our study delineated the conditions under which different testing and antiviral strategies may be cost-effective, showing the importance of accuracy, as seen with PCR or highly sensitive clinical judgment. © 2010 Lee et al

Evidence Propagation and Consensus Formation in Noisy Environments

We study the effectiveness of consensus formation in multi-agent systems where there is both belief updating based on direct evidence and also belief combination between agents. In particular, we consider the scenario in which a population of agents collaborate on the best-of-n problem where the aim is to reach a consensus about which is the best (alternatively, true) state from amongst a set of states, each with a different quality value (or level of evidence). Agents' beliefs are represented within Dempster-Shafer theory by mass functions and we investigate the macro-level properties of four well-known belief combination operators for this multi-agent consensus formation problem: Dempster's rule, Yager's rule, Dubois & Prade's operator and the averaging operator. The convergence properties of the operators are considered and simulation experiments are conducted for different evidence rates and noise levels. Results show that a combination of updating on direct evidence and belief combination between agents results in better consensus to the best state than does evidence updating alone. We also find that in this framework the operators are robust to noise. Broadly, Yager's rule is shown to be the better operator under various parameter values, i.e. convergence to the best state, robustness to noise, and scalability.Comment: 13th international conference on Scalable Uncertainty Managemen

Non-centralized predictive control for drinking-water supply systems

The final publication is available at link.springer.comThis book presents a set of approaches for the real-time monitoring and control of drinking-water networks based on advanced information and communication technologies. It shows the reader how to achieve significant improvements in efficiency in terms of water use, energy consumption, water loss minimization, and water quality guarantees. The methods and approaches presented are illustrated and have been applied using real-life pilot demonstrations based on the drinking-water network in Barcelona, Spain. The proposed approaches and tools cover: - decision-making support for real-time optimal control of water transport networks, explaining how stochastic model predictive control algorithms that take explicit account of uncertainties associated with energy prices and real demand allow the main flow andpressure actuators—pumping stations and pressure regulation valves—and intermediate storage tanks to be operated to meet demand using the most sustainable types of source and with minimum electricity costs; - decision-making support for monitoring water balance and distribution network quality in real time, implementing fault detection anddiagnosis techniques and using information from hundreds of flow,pressure, and water-quality sensors together with hydraulic and quality-parameter-evolution models to detect and locate leaks in the network, possible breaches in water quality, and failures in sensors and/or actuators; - consumer-demand prediction, based on smart metering techniques, producing detailed analyses and forecasts of consumption patterns,providing a customer communications service, and suggesting economic measures intended to promote more efficient use of water at the household level. Researchers and engineers working with drinking-water networks will find this a vital support in overcoming the problems associated with increased population, environmental sensitivities and regulation, aging infrastructures, energy requirements, and limited water sources.Peer ReviewedPostprint (author's final draft

Acute encephalitis syndrome surveillance, Kushinagar district, Uttar Pradesh, India, 2011-2012

In India, quality surveillance for acute encephalitis syndrome (AES), including laboratory testing, is necessary for understanding the epidemiology and etiology of AES, planning interventions, and developing policy. We reviewed AES surveillance data for January 2011-June 2012 from Kushinagar District, Uttar Pradesh, India. Data were cleaned, incidence was determined, and demographic characteristics of cases and data quality were analyzed. A total of 812 AES case records were identified, of which 23\% had illogical entries. AES incidence was highest among boys<6 years of age, and cases peaked during monsoon season. Records for laboratory results (available for Japanese encephalitis but not AES) and vaccination history were largely incomplete, so inferences about the epidemiology and etiology of AES could not be made. The low-quality AES/Japanese encephalitis surveillance data in this area provide little evidence to support development of prevention and control measures, estimate the effect of interventions, and avoid the waste of public health resources