The effect of frequent hemodialysis on matrix metalloproteinases,their tissue inhibitors,and FGF23: Implications for blood pressure and left ventricular mass modification in the Frequent Hemodialysis Network trials

Background: Frequent hemodialysis modifies serum phosphorus, blood pressure, and left ventricular mass (LVM). We ascertained whether frequent hemodialysis is associated with specific changes in biomarker profile among patients enrolled in the frequent hemodialysis network (FHN) trials. Methods: This was a post hoc analysis of biomarkers among patients enrolled to the FHN trials. In particular, we hypothesized that frequent hemodialysis is associated with changes in a specific set of biomarkers which are linked with changes in blood pressure or LVM. Results: Among 332 randomized patients, 243 had biomarker data available. Of these, 124 patients were assigned to 3‐times‐a‐week hemodialysis (94 [Daily Trial] and 30 [Nocturnal Trial]) and 119 patients were assigned to 6‐times‐a‐week hemodialysis (87 [Daily Trial] and 32 [Nocturnal Trial]). Frequent hemodialysis lowered phosphate, blood pressures, LVM, log fibroblast growth factor (FGF)23, and tissue inhibitors of metalloproteinase (TIMP)—2 levels. The fall in phosphate was associated with changes in FGF23 (r = 0.48, P < 0.001) [Daily Trial] and (r = 0.55, P < 0.001) [Nocturnal Trial]) and tended to be associated with changes in systolic blood pressure (r = 0.18, P = 0.057) [Daily Trial] and (r = 0.31, P = 0.04) [Nocturnal Trial]. Within the Daily Trial, changes in MMP2 (r = 0.20, P = 0.034) were associated with changes in LVM. In the Nocturnal Trial, changes in TIMP‐1 (r = 0.37, P = 0.029) and MMP 9 (r = ?0.38, P = 0.01) were associated with LVM changes. MMP2 changes were associated with changes in systolic blood pressure. Conclusions: Reduction of serum phosphate by frequent hemodialysis may modulate FGF23 levels and systolic blood pressure. Markers of matrix turnover are associated with LVM changes. Frequent hemodialysis may affect pathological mediators of chronic kidney disease‐mineral bone‐metabolism disorder.     

Incorporating Confidence Intervals on the Decision Threshold in Logistic Regression

This paper discusses an application of confidence intervals to the threshold decision value used in logistic regres]sion and discusses its effect on changing the quantification of false positive and false negative errors. In doing this a grey area, in which observations are not classified as success (1) or failure (0), but rather ‘uncertain’ is developed. The size of this grey area is related to the level of confidence chosen to create the interval around the threshold as well as the quality of logistic regression model fit. This method shows that potential errors may be mitigated. Monte Carlo simulation and an experimental design approach are used to study the relationship between a number of responses relating to classification of observations and the following factors: threshold level, confidence level, noise in the data, and number of observations collected. Copyright © 2015 John Wiley & Sons, Ltd.     

A Note on Incorporating Simultaneous Multi‐level Failure Time Data in System Reliability Assessments

In this article, we present a method how to evaluate the likelihood for simultaneous failure time data when monitoring is stopped when the system fails. Our method is based on the reliability structure of the system, listing all possible events consistent with the simultaneous data and calculating their contributions to the likelihood. The method is simple to understand and is based on standard probabilistic calculations. We also consider the Jackson and Mosleh 5 method, and some results suggest that the two methods are equivalent. Copyright © 2015 John Wiley & Sons, Ltd.     

Thyroid function in end stage renal disease and effects of frequent hemodialysis

Introduction: End‐stage renal disease (ESRD) is associated with perturbations in thyroid hormone concentrations and an increased prevalence of hypothyroidism. Few studies have examined the effects of hemodialysis dose or frequency on endogenous thyroid function. Methods: Within the Frequent Hemodialysis Network (FHN) trials, we examined the prevalence of hypothyroidism in patients with ESRD. Among those with endogenous thyroid function (without overt hyper/hypothyroidism or thyroid hormone supplementation), we examined the association of thyroid hormone concentration with multiple parameters of self‐reported health status, and physical and cognitive performance, and the effects of hemodialysis frequency on serum thyroid stimulating hormone (TSH), free thyroxine (FT4), and free tri‐iodothyronine (FT3) levels. Conventional thrice‐weekly hemodialysis was compared to in‐center (6 d/wk) hemodialysis (Daily Trial) and Nocturnal (6 nights/wk) home hemodialysis (Nocturnal Trial) over 12 months. Findings: Among 226 FHN Trial participants, the prevalence of hypothyroidism was 11% based on thyroid hormone treatment and/or serum TSH ≥8 mIU/mL. Among the remaining 195 participants (147 Daily, 48 Nocturnal) with endogenous thyroid function, TSH concentrations were modestly (directly) correlated with age (r = 0.16, P = 0.03) but not dialysis vintage. Circulating thyroid hormone levels were not associated with parameters of health status or physical and cognitive performance. Furthermore, frequent in‐center and nocturnal hemodialysis did not significantly change (baseline to month 12) TSH, FT4, or FT3 concentrations in patients with endogenous thyroid function. Discussion: Among patients receiving hemodialysis without overt hyper/hypothyroidism or thyroid hormone treatment, thyroid indices were not associated with multiple measures of health status and were not significantly altered with increased dialysis frequency.     

Factors affecting air sparging remediation systems using field data and numerical simulations

Field data from five air sparging sites were used to assess the effect of several soil, contaminant, and air sparging system factors on the removal time and associated costs required to reach specified clean-up criteria. Numerical simulations were also performed to better assess the field data and to expand the data sets beyond the five field sites. Ten factors were selected and evaluated individually over a range of values based on information from practitioners and the literature. Trends in removal time and removal cost to reach a specified clean-up criterion were analyzed to ascertain the conditions controlling contaminant removal with variations in each factors' value. A linear sensitivity equation was used to quantify system dynamics controlling the observed contaminant removal trends for each factor. Factors found most critical across all field sites in terms of removal time and/or cost were contaminant type, sparge pulsing schedule, number of wells, maximum biodecay rate, total soil porosity, and aquifer organic carbon content. Factors showing moderate to low effect included the depth of the sparge point below the water table, air injection rate/pressure, horizontal air conductivity, and anisotropy ratio. At each field site, subsurface coverage of sparged air, sparged air residence time, contaminant equilibrium in the system, contaminant phase distribution, oxygen availability to microbes, and contaminant volatility seem to control the system responses and were affected by one or more of the 10 factors evaluated.     

Deriving land surface temperature from Landsat 5 and 7 during SMEX02/SMACEX

A sequence of five high-resolution satellite-based land surface temperature (T_s) images over a watershed area in Iowa were analyzed. As a part of the SMEX02 field experiment, these land surface temperature images were extracted from Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM) thermal bands. The radiative transfer model MODTRAN 4.1 was used with atmospheric profile data to atmospherically correct the Landsat data. NDVI derived from Landsat visible and near-infrared bands was used to estimate fractional vegetation cover, which in turn was used to estimate emissivity for Landsat thermal bands. The estimated brightness temperature was compared with concurrent tower based measurements. The mean absolute difference (MAD) between the satellite-based brightness temperature estimates and the tower based brightness temperature was 0.98 °C for Landsat 7 and 1.47 °C for Landsat 5, respectively. Based on these images, the land surface temperature spatial variation and its change with scale are addressed. The scaling properties of the surface temperature are important as they have significant implications for changes in land surface flux estimation between higher-resolution Landsat and regional to global sensors such as MODIS.     

A Database and Evaluation Methodology for Optical Flow

The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex natural scenes, including nonrigid motion, real sensor noise, and motion discontinuities. We propose a new set of benchmarks and evaluation methods for the next generation of optical flow algorithms. To that end, we contribute four types of data to test different aspects of optical flow algorithms: (1) sequences with nonrigid motion where the ground-truth flow is determined by tracking hidden fluorescent texture, (2) realistic synthetic sequences, (3) high frame-rate video used to study interpolation error, and (4) modified stereo sequences of static scenes. In addition to the average angular error used by Barron et al., we compute the absolute flow endpoint error, measures for frame interpolation error, improved statistics, and results at motion discontinuities and in textureless regions. In October 2007, we published the performance of several well-known methods on a preliminary version of our data to establish the current state of the art. We also made the data freely available on the web at . Subsequently a number of researchers have uploaded their results to our website and published papers using the data. A significant improvement in performance has already been achieved. In this paper we analyze the results obtained to date and draw a large number of conclusions from them.