Cardiovascular risk factor control and outcomes in peripheral artery disease patients in the Reduction of Atherothrombosis for Continued Health (REACH) Registry

OBJECTIVES: To examine differences in risk factor (RF) management between peripheral artery disease (PAD) and coronary artery (CAD) or cerebrovascular disease (CVD), as well as the impact of RF control on major 1-year cardiovascular (CV) event rates. METHODS: The REACH Registry recruited >68000 outpatients aged >/=45 years with established atherothrombotic disease or >/=3 RFs for atherothrombosis. The predictors of RF control that were evaluated included: (1) patient demographics, (2) mode of PAD diagnosis, and (3) concomitant CAD and/or CVD. RESULTS: RF control was less frequent in patients with PAD (n=8322), compared with those with CAD or CVD (but no PAD, n=47492) [blood pressure; glycemia; total cholesterol; smoking cessation (each P<0.001)]. Factors independently associated with optimal RF control in patients with PAD were male gender (OR=1.9); residence in North America (OR=3.5), Japan (OR=2.5) or Latin America (OR=1.5); previous coronary revascularization (OR=1.3); and statin use (OR=1.4); whereas prior leg amputation was a negative predictor (OR=0.7) (P<0.001). Optimal RF control was associated with fewer 1-year CV ischemic symptoms or events. CONCLUSIONS: Patients with PAD do not achieve RF control as frequently as individuals with CAD or CVD. Improved RF control is associated with a positive impact on 1-year CV event rates.

Placebo effect characteristics observed in a single, international, longitudinal study in Huntington's disease

BACKGROUND Classically, clinical trials are based on the placebo-control design. Our aim was to analyze the placebo effect in Huntington's disease. METHODS Placebo data were obtained from an international, longitudinal, placebo-controlled trial for Huntington's disease (European Huntington's Disease Initiative Study Group). One-hundred and eighty patients were evaluated using the Unified Huntington Disease Rating Scale over 36 months. A placebo effect was defined as an improvement of at least 50% over baseline scores in the Unified Huntington Disease Rating Scale, and clinically relevant when at least 10% of the population met it. RESULTS Only behavior showed a significant placebo effect, and the proportion of the patients with placebo effect ranged from 16% (first visit) to 41% (last visit). Nondepressed patients with better functional status were most likely to be placebo-responders over time. CONCLUSIONS In Huntington's disease, behavior seems to be more vulnerable to placebo than overall motor function, cognition, and function

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

Preliminary Experience in Treatment of Papillary and Macular Retinoblastoma: Evaluation of Local Control and Local Complications After Treatment with Linear Accelerator-Based Stereotactic Radiotherapy with Micromultileaf Collimator as Second-Line or Salvage Treatment after chemotherapy

To determine the local control and complication rates for children with papillary and/or macular retinoblastoma progressing after chemotherapy and undergoing stereotactic radiotherapy (SRT) with a micromultileaf collimator.

Genetic diversity in an indigenous horse breed: implications for mating strategies and the control of future inbreeding

The Franches-Montagnes is an indigenous Swiss horse breed, with approximately 2500 foalings per year. The stud book is closed, and no introgression from other horse breeds was conducted since 1998. Since 2006, breeding values for 43 different traits (conformation, performance and coat colour) are estimated with a best linear unbiased prediction (BLUP) multiple trait animal model. In this study, we evaluated the genetic diversity for the breeding population, considering the years from 2003 to 2008. Only horses with at least one progeny during that time span were included. Results were obtained based on pedigree information as well as from molecular markers. A series of software packages were screened to combine best the best linear unbiased prediction (BLUP) methodology with optimal genetic contribution theory. We looked for stallions with highest breeding values and lowest average relationship to the dam population. Breeding with such stallions is expected to lead to a selection gain, while lowering the future increase in inbreeding within the breed.

Model-based control of neuromuscular block using mivacurium: design and clinical verification

BACKGROUND: Short-acting agents for neuromuscular block (NMB) require frequent dosing adjustments for individual patient's needs. In this study, we verified a new closed-loop controller for mivacurium dosing in clinical trials. METHODS: Fifteen patients were studied. T1% measured with electromyography was used as input signal for the model-based controller. After induction of propofol/opiate anaesthesia, stabilization of baseline electromyography signal was awaited and a bolus of 0.3 mg kg-1 mivacurium was then administered to facilitate endotracheal intubation. Closed-loop infusion was started thereafter, targeting a neuromuscular block of 90%. Setpoint deviation, the number of manual interventions and surgeon's complaints were recorded. Drug use and its variability between and within patients were evaluated. RESULTS: Median time of closed-loop control for the 11 patients included in the data processing was 135 [89-336] min (median [range]). Four patients had to be excluded because of sensor problems. Mean absolute deviation from setpoint was 1.8 +/- 0.9 T1%. Neither manual interventions nor complaints from the surgeons were recorded. Mean necessary mivacurium infusion rate was 7.0 +/- 2.2 microg kg-1 min-1. Intrapatient variability of mean infusion rates over 30-min interval showed high differences up to a factor of 1.8 between highest and lowest requirement in the same patient. CONCLUSIONS: Neuromuscular block can precisely be controlled with mivacurium using our model-based controller. The amount of mivacurium needed to maintain T1% at defined constant levels differed largely between and within patients. Closed-loop control seems therefore advantageous to automatically maintain neuromuscular block at constant levels.

An insulin infusion advisory system for type 1 diabetes patients based on non-linear model predictive control methods

In this paper, an Insulin Infusion Advisory System (IIAS) for Type 1 diabetes patients, which use insulin pumps for the Continuous Subcutaneous Insulin Infusion (CSII) is presented. The purpose of the system is to estimate the appropriate insulin infusion rates. The system is based on a Non-Linear Model Predictive Controller (NMPC) which uses a hybrid model. The model comprises a Compartmental Model (CM), which simulates the absorption of the glucose to the blood due to meal intakes, and a Neural Network (NN), which simulates the glucose-insulin kinetics. The NN is a Recurrent NN (RNN) trained with the Real Time Recurrent Learning (RTRL) algorithm. The output of the model consists of short term glucose predictions and provides input to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. For the development and the evaluation of the IIAS, data generated from a Mathematical Model (MM) of a Type 1 diabetes patient have been used. The proposed control strategy is evaluated at multiple meal disturbances, various noise levels and additional time delays. The results indicate that the implemented IIAS is capable of handling multiple meals, which correspond to realistic meal profiles, large noise levels and time delays.

Vibrations, Posture, and the Stabilization of Gaze: An Experimental Study on Impedance Control

Vibrations, Posture, and the Stabilization of Gaze: An Experimental Study on Impedance Control R. KREDEL, A. GRIMM & E.-J. HOSSNER University of Bern, Switzerland Introduction Franklin and Wolpert (2011) identify impedance control, i.e., the competence to resist changes in position, velocity or acceleration caused by environmental disturbances, as one of five computational mechanisms which allow for skilled and fluent sen-sorimotor behavior. Accordingly, impedance control is of particular interest in situa-tions in which the motor task exhibits unpredictable components as it is the case in downhill biking or downhill skiing. In an experimental study, the question is asked whether impedance control, beyond its benefits for motor control, also helps to stabi-lize gaze what, in turn, may be essential for maintaining other control mechanisms (e.g., the internal modeling of future states) in an optimal range. Method In a 3x2x4 within-subject ANOVA design, 72 participants conducted three tests on visual acuity and contrast (Landolt / Grating and Vernier) in two different postures (standing vs. squat) on a platform vibrating at four different frequencies (ZEPTOR; 0 Hz, 4 Hz, 8 Hz, 12 Hz; no random noise; constant amplitude) in a counterbalanced or-der with 1-minute breaks in-between. In addition, perceived exertion (Borg) was rated by participants after each condition. Results For Landolt and Grating, significant main effects for posture and frequency are re-vealed, representing lower acuity/contrast thresholds for standing and for higher fre-quencies in general, as well as a significant interaction (p < .05), standing for in-creasing posture differences with increasing frequencies. Overall, performance could be maintained at the 0 Hz/standing level up to a frequency of 8 Hz, if bending of the knees was allowed. The fact that this result is not only due to exertion is proved by the Borg ratings showing significant main effects only, i.e., higher exertion scores for standing and for higher frequencies, but no significant interaction (p > .40). The same pattern, although not significant, is revealed for the Vernier test. Discussion Apparently, postures improving impedance control not only turn out to help to resist disturbances but also assist in stabilizing gaze in spite of these perturbations. Con-sequently, studying the interaction of these control mechanisms in complex unpre-dictable environments seems to be a fruitful field of research for the future. References Franklin, D. W., & Wolpert, D. M. (2011). Computational mechanisms of sensorimotor control. Neuron, 72, 425-442.

Numerical solution of optimal control problems with constant control delays

We investigate a class of optimal control problems that exhibit constant exogenously given delays in the control in the equation of motion of the differential states. Therefore, we formulate an exemplary optimal control problem with one stock and one control variable and review some analytic properties of an optimal solution. However, analytical considerations are quite limited in case of delayed optimal control problems. In order to overcome these limits, we reformulate the problem and apply direct numerical methods to calculate approximate solutions that give a better understanding of this class of optimization problems. In particular, we present two possibilities to reformulate the delayed optimal control problem into an instantaneous optimal control problem and show how these can be solved numerically with a stateof- the-art direct method by applying Bock’s direct multiple shooting algorithm. We further demonstrate the strength of our approach by two economic examples.

Evaluating the optimal timing of surgical antimicrobial prophylaxis: study protocol for a randomized controlled trial

BACKGROUND Surgical site infections are the most common hospital-acquired infections among surgical patients. The administration of surgical antimicrobial prophylaxis reduces the risk of surgical site infections . The optimal timing of this procedure is still a matter of debate. While most studies suggest that it should be given as close to the incision time as possible, others conclude that this may be too late for optimal prevention of surgical site infections. A large observational study suggests that surgical antimicrobial prophylaxis should be administered 74 to 30 minutes before surgery. The aim of this article is to report the design and protocol of a randomized controlled trial investigating the optimal timing of surgical antimicrobial prophylaxis.Methods/design: In this bi-center randomized controlled trial conducted at two tertiary referral centers in Switzerland, we plan to include 5,000 patients undergoing general, oncologic, vascular and orthopedic trauma procedures. Patients are randomized in a 1:1 ratio into two groups: one receiving surgical antimicrobial prophylaxis in the anesthesia room (75 to 30 minutes before incision) and the other receiving surgical antimicrobial prophylaxis in the operating room (less than 30 minutes before incision). We expect a significantly lower rate of surgical site infections with surgical antimicrobial prophylaxis administered more than 30 minutes before the scheduled incision. The primary outcome is the occurrence of surgical site infections during a 30-day follow-up period (one year with an implant in place). When assuming a 5 surgical site infection risk with administration of surgical antimicrobial prophylaxis in the operating room, the planned sample size has an 80% power to detect a relative risk reduction for surgical site infections of 33% when administering surgical antimicrobial prophylaxis in the anesthesia room (with a two-sided type I error of 5%). We expect the study to be completed within three years. DISCUSSION The results of this randomized controlled trial will have an important impact on current international guidelines for infection control strategies in the hospital. Moreover, the results of this randomized controlled trial are of significant interest for patient safety and healthcare economics.Trial registration: This trial is registered on ClinicalTrials.gov under the identifier NCT01790529.

Ego depletion and persistent performance in a cycling task

We tested the assumption that persistent performance in an exhausting indoor cycling task would depend on momentarily available self-control strength (N = 20 active participants). In a within-subjects design (two points of measurement, exactly seven days apart), participants’ self-control strength was experimentally manipulated (depletion: yes vs. no; order counterbalanced) via the Stroop test before the participants performed a cycling task. In line with our hypothesis, hierarchical linear modelling (HLM) revealed that participants consistently performed worse over a period of 18 minutes when they were ego depleted. In addition, HLM analysis revealed that depleted participants invested less effort in the cycling task, as indicated by their lower heart rate. This effect escalated over time, as indicated by a time × condition interaction. These results indicate that self-control strength is necessary to obtain an optimal level of performance in endurance tasks requiring high levels of persistence. Practical implications are discussed.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.