Browsing by Subject "validation"

Now showing 1 - 3 of 3
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    Clinical Diagnosis and Functional Implications of Shoulder Multidirectional Instability
    (2017-12) Staker, Justin
    Background: Shoulder injuries are a common musculoskeletal complaint. Shoulder multidirectional instability (MDI) is thought to be a common cause of symptoms especially in athletes such as competitive swimmers. Clinical laxity tests such as the anterior/posterior drawer and sulcus tests are commonly used to identify excessive glenohumeral translations commonly associated with the diagnosis of MDI. However, the ability of these tests to identify individuals with MDI and to determine if excessive glenohumeral translations are present compared to controls without MDI has not been established. Therefore, the overall purpose of this study was to determine how laxity test findings relate to glenohumeral translations and if differences in joint stability exist dynamically during scapular plane abduction for swimmers diagnosed with MDI and matched controls. Methods: Direct tracking of glenohumeral motion was performed with bone-fixed pins or single plane fluoroscopic imaging. The kinematic inter-examiner repeatability of the laxity tests was determined by ICC calculations in individuals diagnosed with shoulder impingement (n=11). The relationship of the average laxity test score (composite laxity score) from the anterior/posterior drawer and sulcus tests to the root-mean-square average (composite translation) of the laxity test translations was performed with a regression analysis. The differences in joint translations during laxity tests and joint stability during dynamic movement between swimmers diagnosed with MDI and healthy controls without MDI were examined arthrokinematically and osteokinematiclly (n=44). Results: Good inter-examiner kinematic repeatability was demonstrated between examiner for two of three laxity tests. A strong and moderate linear relationship was demonstrated between the composite laxity score and composite translations for the laxity tests. No differences were observed between groups for contact path length or helical parameter descriptions of joint stability during scapular plane abduction. Conclusions: Clinical laxity tests demonstrate good repeatability between examiners. Combining laxity tests in a single score has capability to identify subtle differences in overall joint translations. Composite laxity scores of joint laxity tests may be able to identify differences individuals with overall joint laxity consistent with the diagnosis of MDI. To detect dynamic joint instability between groups, test movements must be sufficiently challenging to elicit signs of joint instability.
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    Large-scale Clustering using Random Sketching and Validation
    (2015-08) Traganitis, Panagiotis
    The advent of high-speed Internet, modern devices and global connectivity has introduced the world to massive amounts of data, that are being generated, communicated and processed daily. Extracting meaningful information from this humongous volume of data is becoming increasingly challenging even for high-performance and cloud computing platforms. While critically important in a gamut of applications, clustering is computationally expensive when tasked with high-volume high-dimensional data. To render such a critical task affordable for data-intensive settings, this thesis introduces a clustering framework, named random sketching and validation (SkeVa). This framework builds upon and markedly broadens the scope of random sample and consensus RANSAC ideas that have been used successfully for robust regression. Four main algorithms are introduced, which enable clustering of high-dimensional data, as well as subspace clustering for data generated by unions of subspaces and clustering of large-scale networks. Extensive numerical tests compare the SkeVa algorithms to their state-of-the-art counterparts and showcase the potential of the SkeVa frameworks.
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    Validation and use of a multiplex assay for the measurement of cytokine concentrations in non-human primate serum
    (2014-11) Gresch, Sarah
    Because of the complexity of the cytokine network, an individual cytokine measurement may be difficult to interpret or may provide insufficient information to inform conclusions. Multiplexing technology, which allows for the simultaneous measurement of multiple analytes, has advanced the study of cytokine secretion patterns. However, if cytokines are to be measured and used to make conclusions on research studies, we must understand the variability around the measurement and the potential for errors associated with testing. Method validation procedures generate data that reflect assay performance and identify the inherent measurement uncertainty, allowing data to be accurately interpreted. This study included the design and performance of a multiplex assay validation assessment for the simultaneous measurement of 23 cytokines in non-human primate (NHP) serum. The validation included analysis of serum samples from 36 healthy cynomolgus macaques in order to determine if the method could be used to detect cytokine concentrations in healthy NHP. Although sensitivity and precision data were generally acceptable, recovery and linearity data were highly variable. Of the 23 cytokines tested, 11 met acceptance criteria, 5 were marginal and 7 were rejected. The ability of the method to detect cytokine concentrations was demonstrated and cytokine concentration ranges were presented for 15 cytokines as measured in serum from healthy cynomolgus macaques. If the validation studies had not been performed, false conclusions could be made (overestimated or underestimated cytokine values) contributing to errors within the Total Testing Process. It would be appropriate to continue to evaluate the impact of pre-analytical error (e.g. storage time and temperature, blood collection steps) on the measurement of cytokines in serum from cynomolgus macaques. Because this work demonstrates significant variability among measurements within and between animals, other important next steps include the description of typical variation levels within and between animals, followed by the generation of appropriate (population- or subject-based) reference intervals for healthy animals. It is clear after performing this validation study, that clinical and research investment in multi-analyte methods is not warranted without demonstration of method validity for each analyte of interest.