Duration Of State Research Articles

Small-variance asymptotics for non-parametric online robot learning

Small-variance asymptotics is emerging as a useful technique for inference in large-scale Bayesian non-parametric mixture models. This paper analyzes the online learning of robot manipulation tasks with Bayesian non-parametric mixture models under small-variance asymptotics. The analysis yields a scalable online sequence clustering (SOSC) algorithm that is non-parametric in the number of clusters and the subspace dimension of each cluster. SOSC groups the new datapoint in low-dimensional subspaces by online inference in a non-parametric mixture of probabilistic principal component analyzers (MPPCA) based on a Dirichlet process, and captures the state transition and state duration information online in a hidden semi-Markov model (HSMM) based on a hierarchical Dirichlet process. A task-parameterized formulation of our approach autonomously adapts the model to changing environmental situations during manipulation. We apply the algorithm in a teleoperation setting to recognize the intention of the operator and remotely adjust the movement of the robot using the learned model. The generative model is used to synthesize both time-independent and time-dependent behaviors by relying on the principles of shared and autonomous control. Experiments with the Baxter robot yield parsimonious clusters that adapt online with new demonstrations and assist the operator in performing remote manipulation tasks.

Q-TWiST Analysis to Assess Benefit-Risk of Pembrolizumab in Patients with PD-L1-Positive Advanced or Metastatic Non-small Cell Lung Cancer.

ObjectivesPembrolizumab monotherapy showed significantly longer overall survival and fewer treatment-related adverse events compared to chemotherapy in patients with advanced or metastatic non-small cell lung cancer (NSCLC) with programmed death ligand-1 (PD-L1)–positive tumors in the first-line setting in KEYNOTE (KN)-024 and in those previously treated in KN010. The objective of this analysis was to assess the benefit–risk of pembrolizumab in terms of quality-adjusted survival amongst patients in these trials.MethodsThe Quality-adjusted Time Without Symptoms of disease progression or Toxicity of treatment (Q-TWiST) analysis was used to compare treatments. Survival time was partitioned into three health states: with toxicity before disease progression, without toxicity before disease progression, and disease progression until death. Health state utilities were estimated using EuroQol-5 Dimensions, 3 Levels (EQ-5D-3L) data collected in the trials. Q-TWiST was calculated as the utility-weighted sum of the mean health state durations. Trial data analyzed included the primary analysis and subsequent data cutoffs. The base-case analysis was based on the most recent analysis of the trials.ResultsPatients randomized to pembrolizumab had 2.49 months greater Q-TWiST (P value < 0.001) compared to those randomized to platinum-based chemotherapy at a follow-up of 24 months in KN024, and 2.29 months greater Q-TWiST (P value < 0.001) compared to docetaxel over 30 months follow-up in KN010. Results across the trial analyses showed an increase in trend for the Q-TWiST improvement of pembrolizumab over time.ConclusionsPembrolizumab showed significant improvement in Q-TWiST compared to chemotherapy in advanced or metastatic NSCLC in both previously untreated and treated patients. The benefits of pembrolizumab continued to accrue with longer follow-ups.

Affective States Influence Sport Performance in Swimming

Abstract Introduction . Sports activity involves experiencing affective states, which have a substantial effect on actions taken by the athlete. The results of previous studies on the relationship between emotional states and sport performance outcomes are ambiguous. The aim of the study was to establish the relationships between affective states (both emotional states and moods) and performance in swimming. Material and methods . The study examined 9 female swimmers and 22 male swimmers competing at the national level aged from 15 to 23 years (M = 18.1; SD = 2.397). Affective states were evaluated by means of the Profile of Mood States (POMS) completed once a day before the competition and the Positive and Negative Affect Schedule (PANAS) completed before each race. The subject’s life record was divided by the time obtained in each race and expressed as a percentage. Results . Immediately before the races where the best results were obtained, the swimmers experienced the strongest positive emotions and the lowest level of negative emotions. The lowest level of positive states was recorded before the races with the worst performance. The lower the level of negative moods (fatigue, depression, anger, and tension) and the higher the level of positive moods (vigour and kindness) were, the better the results obtained by swimmers were. One exception was confusion, which unexpectedly correlated positively with the swimmers’ results. Preliminary analyses showed no indication of statistically significant differences between the women and men surveyed. Conclusions . The results of the study suggest that affective states influence performance outcomes in swimming. This influence may vary according to the valence and content as well as duration of affective states (emotional states vs. mood). On the basis of the results obtained, guidelines for coaches and their athletes can be formulated. A properly prepared trainer can choose training tasks in such a way as to optimise the intensity and content of the emotions experienced by athletes. Emotions seem to be important not only with regard to athletes’ well-being, but also as indirect and direct predictors of the results they achieve. Expression of emotion and emotional awareness in persons connected with sport should be included in training work.

Predictive Multi-user Dynamic Spectrum Allocation Using Hidden Semi-Markov Model

For wideband Cognitive Radio (CR) devices, the availability of primary user (PU) activity prediction model can save sensing energy and time, track spectrum variations, reduce switching overhead, improve spectrum usage and lower interference to PU. Using Universal Software Radio Peripheral (USRP) generated data, this paper has verified the superiority of Hidden Semi-Markov model (HSMM) over the conventional HMM in learning and predicting temporal correlations in PU spectral activity under non-geometric distribution of state durations. Numerical simulations further show that in a coordinated multi-SU/PU scenario, compared to the traditional random Carrier Sense Multiple Access (CSMA), the proposed HSMM-dynamic spectrum allocation (DSA) protocol significantly reduces aggregate interference to PU. Depending on the number of SU, there exists a trade-off between “interference-free coexistence with PU” and “self-existence of a large number of SU”. This problem is addressed further by statistically modeling probability of free channels and using it to optimize the number of SU that can be allocated. The proposed scheme outperforms the conventional sensing based dynamic spectrum allocation (DSA) in terms of reduced PU interference, lower spectrum handoff requirements and higher spectrum utilization efficiency. The predictive optimized HSMM-DSA can be used as an additional layer of intelligence for any CR device for efficient spectrum sharing.

BENEFICIAL EFFECTS OF MAGNETIC FIELDS ON THE HUMAN HEART A REVIEW OF CURRENT ADVANCES AND PROPOSED MECHANISMS

The main purpose of this manuscript is to introduce the reader to the present “state of the art” in experimental Low Level Magnetic Fields nerve stimulation approaches to improve chaotic cardiac arrhythmias and muscle contractions. The area addressed in this paper is the transcutaneous application of Low Level Magnetic Fields to a branch of the vagus nerve. Cardiac Arrhythmias such as Atrial Fibrillation, as well as and muscle contractility were reversed by Low Level Transcutaneous Stimulation (LL-TS) of the Auricular Branch of the Vagus Nerve (ABVN). This treatment has been successfully reported in humans as well as in awaken and anesthetized animals such as rodents and dogs. The functional improvement has been attributed to a reversal of cardiac myocytes remodeling (reversal of fibrosis) resulting from experimentally provoking induced rapid heartbeats. The prolonged duration of a tachycardia state induces intracellular accumulation of glycogen leading into fibrosis, this in turn is hypothesized to impede the intercellular electrical communications of the specialized cardiac cells. It also reduces the functional ability of the main pumping chamber (Left Ventricle).

A Spectral and Timing Study of MAXI J1535–571, Based on Swift/XRT, XMM-Newton, and NICER Observations Obtained in Fall 2017

Abstract We present a spectral-timing analysis of observations taken in fall 2017 of the newly detected X-ray transient MAXI J1535–571. We included 38 Swift/XRT window timing mode observations, 3 XMM-Newton observations, and 31 Neutron star Interior Composition Explorer observations in our study. We computed the fundamental diagrams commonly used to study black hole transients, and fitted power density and energy spectra to study the evolution of spectral and timing parameters. The observed properties are consistent with a bright black hole X-ray binary ( erg cm−2 s−1) that evolves from the low-hard-state to the high-soft state and back to the low-hard-state. In some observations the power density spectra showed type-C quasiperiodic oscillations, giving additional evidence that MAXI J1535–571 is in a hard state during these observations. The duration of the soft state with less than 10 days is unusually short and observations taken in spring 2018 show that MAXI J1535–571 entered a second (and longer) soft state.

Change-Driven M100 Component in the Bilateral Secondary Somatosensory Cortex: A Magnetoencephalographic Study.

Our previous demonstration that the M100 somatosensory evoked magnetic field (SEF) has a similar temporal profile, dipole orientation and source location whether induced by activation (ON-M100) or deactivation (OFF-M100) of electrical stimulation suggests a common cortical system to detect sensory change. While we have not recorded such change-driven components earlier than M100 using electrical stimulation, clear M50 responses were reported using both ON and OFF mechanical stimulation (Onishi et al. in Clin Neurophysiol 121:588-593, 2010). To examine the significance of M50 and M100 in reflecting the detection of somatosensory changes, we recorded these waveforms in 12 healthy subjects (9 males and 3 females) by magnetoencephalography in response to mechanical stimulation from a piezoelectric actuator. Onset and offset (ON and OFF) stimuli were randomly presented with three preceding steady state (PSS) durations (0.5, 1.5 and 3s) in one consecutive session. Results revealed that (i) onset and offset somatosensory events elicited clear M50 and M100 components; (ii) M50 and M100 components had distinct origins, with M50 localised to the contralateral primary somatosensory cortex (cS1) and M100 to the bilateral secondary somatosensory cortex (iS2, cS2); and (iii) the amplitude of M50 in cS1 was independent of the PSS durations, whereas that of M100 in S2 was dependent on the PSS durations for both ON and OFF events. These findings suggest that the M50 amplitude in cS1 reflects the number of activated mechanoreceptors during Onset and Offset, whereas the M100 amplitude in S2 reflects change detection based on sensory memory for Onset and Offset stimuli at least in part. We demonstrated that the M50 in cS1 and M100 in S2 plays different roles in the change detection system in somatosensory modality.

Risk Factors Associated with the Outcome of Post-Traumatic Hydrocephalus.

Post-traumatic hydrocephalus is a common complication that arises after head injury. However, risk factors associated with the outcome of post-traumatic hydrocephalus have seldom been addressed. Therefore, we performed this clinical study to analyze the risk factors affecting the outcome of post-traumatic hydrocephalus in patients with head injuries. A total of 116 post-traumatic hydrocephalus patients, admitted in our hospital between March 2012 and October 2017 were reviewed. The related factors assessed were age, gender, Glasgow Coma Score on admission, platelet count, plasma fibrinogen levels, D-dimer concentration, subarachnoid hemorrhage, subdural hygroma, cerebral hernia, cisterna ambiens, decompressive craniectomy, cranioplasty, ventriculoperitoneal shunt implantation, intracranial infection, and duration of comatous state. The patient outcomes after 6 months of treatment were evaluated by the Glasgow Outcome Scale. Risk factors for the outcome of post-traumatic hydrocephalus were evaluated by applying logistic regression analysis. Poor outcome was observed in 66.4% of the patients (77/116). Univariate and multivariate analyses revealed that the disappearance of cisterna ambiens, the long duration of comatous state (>2 months), the high levels of plasma fibrinogen, and the ventriculoperitoneal shunt implantation were related to adverse outcomes (p < 0.05). The disappearance of cisterna ambiens, the prolonged duration of comatous state (>2 months), the high plasma fibrinogen levels are the most important factors affecting the outcome of post-traumatic hydrocephalus, and the ventriculoperitoneal shunt implantation is the most critical predictor of the outcome of post-traumatic hydrocephalus.

Rapid estimation of PID minimum variance

PID controllers are the most common type of controllers used in industry. However, to find the best PID performance is a challenging task. Assessment of the best PID performance leads to the minimization of the deviation from set point as indicated by closed loop transfer function. This is a non-convex optimization problem and there is no direct solution for finding this benchmark. Solving this problem iteratively as proposed in literature requires long calculation times. Furthermore, iterative methods are not guaranteed to find the minimum value. Using as many as possible infinite impulse response coefficients, or increasing the number of finite impulse coefficients gradually, causes undesirably large calculation times. We propose a fast method to evaluate the minimum variance by a fixed number of finite impulse response coefficients. This finite impulse model is double the size of the stable system impulse response (it contains the transient response and the same duration of steady state). Thus it avoids undesired iteration, and consequently, the PID minimum variance is quickly evaluated. Time is a critical factor as the purpose to assess this index is for use in online monitoring. The proposed method is tested on benchmark simulation examples from literature.

Intermittent Operation of Fixed-Bed Methanation Reactors: A Simple Relation Between Start-Up Time and Idle State Duration

Power to gas is a way to convert surplus electricity available on the grid (that might come from renewable sources like solar or wind) and store it as methane. It is also a way to valorize carbon dioxide and reduce CO2 emissions into the atmosphere. At the heart of the process, the methanation reaction has to achieve high-performance conversion in a completely dynamic mode of operation. This mode of operation—linked to the fluctuations of available power on the grid, and the possible thermal runaway of the reactor due to the exothermic nature of the methanation reaction—means that special care is needed in the design of the reactor as well as its control. The reactor, which might be catalytic fixed-bed, should also restart quickly after an idle period. Start-up requires the reactor temperature to be sufficiently high to ignite the reaction. In this paper, the intermittent operation of a fixed-bed methanation reactor is studied. A mathematical model is developed in order to simulate successive gas shutdowns and reinjections. It is examined as well if the reactor is able to restart spontaneously (i.e. with no external heating, but utilizing thermal inertia and the exothermicity of the reaction), when reactants are reinjected after an idle phase. A relation is found between the respective durations of spontaneous restart and idle phase, which can be used to evaluate whether using an external heat source is preferable to relying on spontaneous restart.

Multi-centroid diastolic duration distribution based HSMM for heart sound segmentation

Abstract This paper presents a multi-centroid diastolic duration model for the hidden semi-Markov model (HSMM) based heart sound segmentation. The centroids are calculated by hierarchical agglomerative clustering of the neighboring diastolic duration values using Ward's method until center of clusters are found at least a systolic duration apart. The multiple peak distribution yields a sharper gradient of likelihood around the expected centroids and improves the discriminability of similar observations. The peak density at each centroid acts as a reference point for the HSMM to determine the origin of the hidden-state and adjust the corresponding state duration based on the maximum likelihood criterion. This model overcomes the limitation of the single peak mean value model that may overfit the duration distribution when the heart rate variation is relatively large. An extended logistic regression-HSMM algorithm using the proposed duration model is presented for the heart sound segmentation. In addition, the total variation filter is used to attenuate the effect of noises and emphasize the fundamental heart sounds, S1 and S2. The proposed method is evaluated on the training-set-a of 2016 Physionet/Computing in Cardiology Challenge and yields an average F1 score of 98.36 ± 0.43.

Abstract 190: Hybrid Strategy of Damage Control IR (DCIR) and REBOA Would be Feasible for Traumatic Hemorrhagic Shock Patients Suffering From Severe Pelvic Injuries

Introduction: Massive hemorrhage with pelvic injury is sometimes lethal. So, success or failure of hemostatic intervention in the hyperacute phase leads to survival of patients directly. Recently, a hybrid strategy with Operative Management (OM) and Interventional Radiology (IR) and/or Resuscitative Endovascular Balloon Occlusion of the Aorta (REBOA) for torso or pelvic severe trauma has been recognized world-widely. But, awareness of Damage control IR (DCIR) which is conscious of time and coagulopathy as Damage control surgery (DCS) is still not enough. So, we studied the possibility of the hybrid strategy with DCIR and REBOA for traumatic hemorrhagic shock patients with pelvic fracture. Methods: This study included patients who underwent traditional IR or DCIR with REBOA, if it were needed, for a traumatic shock state mainly due to pelvic fracture, at our emergency and trauma center. They were sorted into traditional IR group (group IR) and DCIR group (group DCIR). The primary endpoint was a survival rate in the first 30 days after injured. Secondary endpoints were fluid factors such as total amount of crystalloid infusion and blood transfusion within the first 24 hours, and for the duration of the recovery from shock state. Results: 64 trauma shock patients were sorted into group IR (n=38) and group DCIR (n=26). All REBOA patients (n=18) were in group DCIR. Initial systolic BP (group IR vs DCIR; 75mmHg vs. 54), RTS (5.66 vs. 4.12) and Ps (0.61 vs. 0.39) were significantly lower in group DCIR. ISS (32.8 vs. 41.5) and initial Shock Index (1.9 vs. 2.4) were higher in group DCIR significantly. There were no significant differences in the amount of total crystalloid infusion (7353+/-3152ml vs. 7140+/-5342ml) and blood transfusion (4183+/-3485ml vs. 3972+/-3188ml), and the survival rate (30/38 (79%) vs. 16/28 (62%)). But the required time to recovery from shock state was significantly shorter in group DCIR (65min vs. 43min). Conclusion: The hybrid strategy with DCIR and REBOA did not increase any amount of blood transfusion or crystalloid infusion or the mortality rate. But it could shorten the duration of shock state compared with traditional IR treatment. Thus, this hybrid strategy would be feasible for hemorrhage shock patients suffering from pelvic severe trauma.

Automated monitoring and assessment of productivity in earthmoving projects

Continuous monitoring of productivity and assessment of its variations are crucial processes that significantly contribute to success of earthmoving projects. Numerous factors may lead to productivity variations. However, these factors are subjectively identified using manual knowledge-based expert judgment. Such manual recognition process is not only subject to errors but also time-consuming. There is a lack of research work that focuses on near real-time assessment of productivity variation and its effect on cost, schedule and effective utilization of resources in earthmoving projects. This paper presents a customized multi-source automated data acquisition model that acquires data from a variety of wireless sensing technologies. The acquired multi-sensor data are transmitted to a central MySQL database. Then a newly developed data fusion algorithm is applied for truck state recognition, and hence the duration of each earthmoving state. Multi-sensor data fusion facilitates measurement of actual productivity, and consequently the assessment of productivity ratios that support continuous monitoring of productivity variation in earthmoving operations. The developed tracking and monitoring model generates an early warning that supports proactive decisions to avoid schedule delays, cost overruns, and inefficient depletion of resources. A case study is used to reveal the applicability of the proposed model in monitoring and assessing actual productivity and its deviations from planned productivity. Finally, results are discussed and conclusions are drawn highlighting the features of the proposed model.

Capturing and Understanding Workers’ Activities in Far‐Field Surveillance Videos with Deep Action Recognition and Bayesian Nonparametric Learning

AbstractRecording workers’ activities is an important, but burdensome, management task for site supervisors. The last decade has seen a growing trend toward vision‐based activity recognition. However, recognizing workers’ activities in far‐field surveillance videos is understudied. This study proposes a hierarchical statistical method for recognizing workers’ activities in far‐field surveillance videos. The method consists of two steps. First, a deep action recognition method was used to recognize workers’ actions, and a new fusion strategy was proposed to consider the characteristics of far‐field surveillance videos. The deep action recognition method with the new fusion strategy has achieved the comparable performance (0.84 average accuracy) on the far‐field surveillance data set in contrast to the original method on the public data sets. Second, a Bayesian nonparametric hidden semi‐Markov model was innovatively used to model and infer workers’ activities based on action sequences. The latent states of the fitted Bayesian model captured workers’ activities in terms of state duration distributions and state transition distributions, which are indispensable for understanding workers’ time allocation. It has been preliminarily illustrated that the activity information learned by the Bayesian model possesses the potential to implement objective work sampling, personal physical fatigue monitoring, trade‐level health risk assessment, and process‐based quality control. Also, the limitations of this study are discussed.

On Achieving Asynchronous Energy-Efficient Neighbor Discovery for Mobile Sensor Networks

Recent advances in mobile sensor networks (MSNs) lead to a wide demand of wireless communication based applications. However, due to the battery technology constraint, many MSNs-based applications are confined by the limited power resource capacity. Thus, discovering neighbors with minimal power consumption and latency becomes an indispensable characteristic to guarantee the feasibility of above applications. Most of previously proposed time-slotted-based neighbor discovery protocols excessively idealize the power consumption model, which ignores the power consumption and time duration of the transient state. In this paper, we propose a more practical model named enhanced power consumption model that considers the power consumption and time duration of the transient state. We then propose the asynchronous energy-efficient neighbor discovery protocols called Quick-Connect ( $Q-Connect$ ) including $Q-Connect_A$ , $Q-Connect_U$ and $Q-Connect_{UI}$ protocols, each of which can provide a strict upper bound on the discovery latency. We consider both the slot-aligned and slot-unaligned cases. For slot-aligned case, we propose the $Q-Connect_A$ protocol, which can greatly reduce the worst-case discovery latency. For slot-unaligned case, we first propose the $Q-Connect_U$ protocol, based on which we further propose an improved protocol called $Q-Connect_{UI}$ . Finally, we conduct state-based simulations to illustrate the effectiveness of the proposed $Q-Connect$ protocols.

PCN107 - BURDEN AND COSTS OF ACUTE MYELOID LEUKAEMIA IN PORTUGAL

To estimate the burden and costs of disease attributable to acute myeloid leukaemia (AML). The analysis considers the impact of the disease in adult patients in Portugal during 2015, according to the societal perspective. The burden of disease is measured using disability adjusted life years (DALY), based on myeloid leukaemia’s data from Portuguese oncology registries and epidemiologic information from the United Kingdom. A cumulative incidence model was developed to estimate the incidence, prevalence and duration of each health state, based on a long-term clinical trial in adults with AML. Disability weights were based on the Global Burden of Disease Study. Direct costs included inpatient and outpatient services costs as well as transportation costs. Indirect costs due to productivity decrease were also included. In 2015, 207 deaths were attributable to AML, resulting in the loss of 1,340 life years due to premature death. Years lost due to disability are estimated at 51. The total burden of disease attributable to AML is estimated at 1,391 DALY, with a burden per patient of 1.96 DALY. The estimated direct costs due to AML in 2015 are about 16 million euros, with 99% of total direct costs driven by inpatient costs. Indirect costs accounted for 1.9 million euros. Overall costs are estimated at 18 million euros, with a cost per patient of 25,389 €. During 2015, AML was responsible for a burden of 1.391 DALY and a total cost of 18 million euros in mainland Portugal. Despite the low prevalence of AML, the burden of disease and cost per patient are high. This reflects the seriousness of the disease and it is a reason why it should be a focus of attention for healthcare decision makers.

Anti retroviral therapy adherence and its determinants among patients attending ART centre, Bhopal

Background: Antiretroviral drugs delay progression of HIV disease and improve the quality of life in the HIV infected people. A very high levels of adherence is required for ART to be effective long term and to prevent the emergence of resistant viral strains. The objectives were to assess the adherence of anti-retro viral treatment and its determinants and to estimate the status of CD4 count before and after ART in HIV patients.Methods: The study was a cross sectional study conducted in ART center Hamidia hospital at Bhopal, Madhya Pradesh. 256 participants with HIV who had registered in the center and receiving ART for the past 6 months were included in the study. A predesigned questionnaire was used for the study. Data was analysed using Epi Info. The significance of proportion were calculated using chi square test (p&lt;0.05).Results: All the respondents knew that unprotected sexual contact, contaminated Blood transfusion and infected syringes were the major modes of transmission of HIV. About 60 (41.96%) in 143 patient with CD4 count &lt;200 improved to &gt;350. Majority of respondents 195 (76.17%) missed the dose often and 61 (23.83%) did not miss the dose at all. The major reasons for missing dose of ART regimen were forgot to take medicines (57.95%), alcoholic state (26.15%) and long duration of treatment (47.17%).Conclusions: The majority of patient missed the doses due to socio demographic and treatment related factors. A good treatment adherence is linked with the good quality drug and better environment in the clinics throughout the treatment period.

Economic Evaluation of Lupus Nephritis in the Systemic Lupus International Collaborating Clinics Inception Cohort Using a Multistate Model Approach.

Little is known about the long-term costs of lupus nephritis (LN). The costs were compared between patients with and without LN using multistate modeling. Patients from 32 centers in 11 countries were enrolled in the Systemic Lupus International Collaborating Clinics inception cohort within 15 months of diagnosis and provided annual data on renal function, hospitalizations, medications, dialysis, and selected procedures. LN was diagnosed by renal biopsy or the American College of Rheumatology classification criteria. Renal function was assessed annually using the estimated glomerular filtration rate (GFR) or estimated proteinuria. A multistate model was used to predict 10-year cumulative costs by multiplying annual costs associated with each renal state by the expected state duration. A total of 1,545 patients participated; 89.3% were women, the mean ± age at diagnosis was 35.2 ± 13.4 years, 49% were white, and the mean followup duration was 6.3 ± 3.3 years. LN developed in 39.4% of these patients by the end of followup. Ten-year cumulative costs were greater in those with LN and an estimated glomerular filtration rate (GFR) <30 ml/minute ($310,579 2015 Canadian dollars versus $19,987 if no LN and estimated GFR >60 ml/minute) or with LN and estimated proteinuria >3 gm/day ($84,040 versus $20,499 if no LN and estimated proteinuria <0.25 gm/day). Patients with estimated GFR <30 ml/minute incurred 10-year costs 15-fold higher than those with normal estimated GFR. By estimating the expected duration in each renal state and incorporating associated annual costs, disease severity at presentation can be used to anticipate future health care costs. This is critical knowledge for cost-effectiveness evaluations of novel therapies.

Progression of subclinical atherosclerosis in systemic lupus erythematosus versus rheumatoid arthritis: the impact of low disease activity.

The progression of subclinical atherosclerosis in SLE and RA has not been comparatively assessed. We sought to investigate the impact of low disease activity and other disease-related factors on atherosclerosis progression in SLE vs RA. We performed a 3-year follow-up carotid and femoral artery ultrasound in 101 patients with SLE, 85 with RA and 85 controls after a baseline examination in 115 SLE and 1:1 age- and gender-matched RA patients and controls. We used logistic regression to compare atherosclerosis progression (new plaque development) between SLE and RA vs controls, and assess determinants of progression in SLE patients with different lupus low disease activity state (LLDAS) durations, adjusting for disease-related factors, antihypertensives, antiplatelets, statins and the Systemic Coronary Risk Evaluation 10-year cardiovascular risk. The odds ratio (OR) of plaque progression vs controls was significantly higher in SLE (OR = 2.81, P = 0.043), but not in RA (OR = 2.22, P = 0.109). Results were similar in patients with low disease activity (88% of SLE, 74% of RA). Multivariate determinants of progression in SLE included antiphospholipid antibodies (OR = 2.00, P = 0.043) and Systemic Coronary Risk Evaluation (OR = 2.87, P = 0.019) for all patients, and additionally cumulative corticosteroid dose during follow-up (OR = 1.38, P = 0.013) and disease duration (OR = 1.20, P = 0.022) for patients in LLDAS over entire follow-up. Results were similar for patients with shorter LLDAS durations (>75% or >50% of follow-up). Plaque progression is accelerated in SLE regardless of disease activity, and is associated with antiphospholipid antibodies and the Systemic Coronary Risk Evaluation. In LLDAS, cumulative corticosteroid dose and disease duration are additional determinants of progression.

Lack of Transmission of Foot-and-Mouth Disease Virus From Persistently Infected Cattle to Naïve Cattle Under Field Conditions in Vietnam.

Foot-and-mouth disease (FMD), caused by FMD virus (FMDV; Aphthovirus, Picornaviridae), is a highly contagious and economically important disease of cloven-hoofed domestic livestock and wildlife species worldwide. Subsequent to the clinical phase of FMD, a large proportion of FMDV-infected ruminants become persistently infected carriers, defined by detection of FMDV in oropharyngeal fluid (OPF) samples 28 days or more post-infection. The goal of this prospective study was to characterize the FMD carrier state in cattle subsequent to natural infection under typical husbandry practices in Vietnam. Ten persistently infected cattle on eight farms in the Long An province in southern Vietnam were monitored by monthly screening of serum and oropharyngeal fluid samples for 12 months. To assess transmission from FMDV carriers, 16 naïve cattle were intentionally brought into direct contact with the persistently infected animals for 6 months, and were monitored by clinical and laboratory methods. The restricted mean duration of the FMD carrier state was 27.7 months, and the rate of decrease of the proportion of carrier animals was 0.03 per month. There was no evidence of transmission to naïve animals throughout the study period. Additionally, there was no detection of FMDV infection or seroconversion in three calves born to carrier animals during the study. The force of infection for carrier-to-contact transmission was 0 per month, with upper 95% confidence limit of 0.064 per month. Phylogenetic analysis of viral protein 1 (VP1) coding sequences obtained from carriers indicated that all viruses recovered in this study belonged to the O/ME-SA/PanAsia lineage, and grouped phylogenetically with temporally and geographically related viruses. Analysis of within-host evolution of FMDV, based upon full-length open reading frame sequences recovered from consecutive samples from one animal, indicated that most of the non-synonymous changes occurred in Lpro, VP2, and VP3 protein coding regions. This study suggests that the duration of FMDV persistent infection in cattle may be longer than previously recognized, but the risk of transmission is low. Additional novel insights are provided into within-host viral evolution under natural conditions in an endemic setting.