McMaster University

About: McMaster University is a education organization based out in Hamilton, Ontario, Canada. It is known for research contribution in the topics: Population & Health care. The organization has 41361 authors who have published 101269 publications receiving 4251422 citations.

The Lower Extremity Functional Scale (LEFS): Scale Development, Measurement Properties, and Clinical Application

Abstract: Background and Purpose. The purpose of this study was to assess the reliability, construct validity, and sensitivity to change of the Lower Extremity Functional Scale (LEFS). Subjects and Methods. The LEFS was administered to 107 patients with lower-extremity musculoskeletal dysfunction referred to 12 outpatient physical therapy clinics. Methods. The LEFS was administered during the initial assessment, 24 to 48 hours following the initial assessment, and then at weekly intervals for 4 weeks. The SF-36 (acute version) was administered during the initial assessment and at weekly intervals. A type 2,1 intraclass correlation coefficient was used to estimate test-retest reliability. Pearson correlations and one-way analyses of variance were used to examine construct validity. Spearman rank-order correlation coefficients were used to examine the relationship between an independent prognostic rating of change for each patient and change in the LEFS and SF-36 scores. Results. Test-retest reliability of the LEFS scores was excellent ( R =.94 [95% lower limit confidence interval (CI)=.89]). Correlations between the LEFS and the SF-36 physical function subscale and physical component score were r =.80 (95% lower limit CI=.73) and r =.64 (95% lower limit CI=.54), respectively. There was a higher correlation between the prognostic rating of change and the LEFS than between the prognostic rating of change and the SF-36 physical function score. The potential error associated with a score on the LEFS at a given point in time is ±5.3 scale points (90% CI), the minimal detectable change is 9 scale points (90% CI), and the minimal clinically important difference is 9 scale points (90% CI). Conclusion and Discussion. The LEFS is reliable, and construct validity was supported by comparison with the SF-36. The sensitivity to change of the LEFS was superior to that of the SF-36 in this population. The LEFS is efficient to administer and score and is applicable for research purposes and clinical decision making for individual patients.

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

Abstract: Adaptive beamforming methods are known to degrade if some of underlying assumptions on the environment, sources, or sensor array become violated. In particular, if the desired signal is present in training snapshots, the adaptive array performance may be quite sensitive even to slight mismatches between the presumed and actual signal steering vectors (spatial signatures). Such mismatches can occur as a result of environmental nonstationarities, look direction errors, imperfect array calibration, distorted antenna shape, as well as distortions caused by medium inhomogeneities, near-far mismatch, source spreading, and local scattering. The similar type of performance degradation can occur when the signal steering vector is known exactly but the training sample size is small. In this paper, we develop a new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch. Our approach is based on the optimization of worst-case performance. It turns out that the natural formulation of this adaptive beamforming problem involves minimization of a quadratic function subject to infinitely many nonconvex quadratic constraints. We show that this (originally intractable) problem can be reformulated in a convex form as the so-called second-order cone (SOC) program and solved efficiently (in polynomial time) using the well-established interior point method. It is also shown that the proposed technique can be interpreted in terms of diagonal loading where the optimal value of the diagonal loading factor is computed based on the known level of uncertainty of the signal steering vector. Computer simulations with several frequently encountered types of signal steering vector mismatches show better performance of our robust beamformer as compared with existing adaptive beamforming algorithms.

Transmit beamforming for physical-layer multicasting

Abstract: This paper considers the problem of downlink transmit beamforming for wireless transmission and downstream precoding for digital subscriber wireline transmission, in the context of common information broadcasting or multicasting applications wherein channel state information (CSI) is available at the transmitter. Unlike the usual "blind" isotropic broadcasting scenario, the availability of CSI allows transmit optimization. A minimum transmission power criterion is adopted, subject to prescribed minimum received signal-to-noise ratios (SNRs) at each of the intended receivers. A related max-min SNR "fair" problem formulation is also considered subject to a transmitted power constraint. It is proven that both problems are NP-hard; however, suitable reformulation allows the successful application of semidefinite relaxation (SDR) techniques. SDR yields an approximate solution plus a bound on the optimum value of the associated cost/reward. SDR is motivated from a Lagrangian duality perspective, and its performance is assessed via pertinent simulations for the case of Rayleigh fading wireless channels. We find that SDR typically yields solutions that are within 3-4 dB of the optimum, which is often good enough in practice. In several scenarios, SDR generates exact solutions that meet the associated bound on the optimum value. This is illustrated using measured very-high-bit-rate Digital Subscriber line (VDSL) channel data, and far-field beamforming for a uniform linear transmit antenna array.

Methods to explain the clinical significance of health status measures.

Abstract: One can classify ways to establish the interpretability of quality-of-life measures as anchor based or distribution based. Anchor-based measures require an independent standard or anchor that is itself interpretable and at least moderately correlated with the instrument being explored. One can further classify anchor-based approaches into population-focused and individual-focused measures. Population-focused approaches are analogous to construct validation and rely on multiple anchors that frame an individual's response in terms of the entire population (eg, a group of patients with a score of 40 has a mortality of 20%). Anchors for population-based approaches include status on a single item, diagnosis, symptoms, disease severity, and response to treatment. Individual-focused approaches are analogous to criterion validation. These methods, which rely on a single anchor and establish a minimum important difference in change in score, require 2 steps. The first step establishes the smallest change in score that patients consider, on average, to be important (the minimum important difference). The second step estimates the proportion of patients who have achieved that minimum important difference. Anchors for the individual-focused approach include global ratings of change within patients and global ratings of differences between patients. Distribution-based methods rely on expressing an effect in terms of the underlying distribution of results. Investigators may express effects in terms of between-person standard deviation units, within-person standard deviation units, and the standard error of measurement. No single approach to interpretability is perfect. Use of multiple strategies is likely to enhance the interpretability of any particular instrument.

Mapping autism risk loci using genetic linkage and chromosomal rearrangements

Abstract: Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.