117 research outputs found

    Feasibility of diffusion tensor imaging (DTI) with fibre tractography of the normal female pelvic floor

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    To prospectively determine the feasibility of diffusion tensor imaging (DTI) with fibre tractography as a tool for the three-dimensional (3D) visualisation of normal pelvic floor anatomy. Five young female nulliparous subjects (mean age 28 ± 3 years) underwent DTI at 3.0T. Two-dimensional diffusion-weighted axial spin-echo echo-planar (SP-EPI) pulse sequence of the pelvic floor was performed, with additional T2-TSE multiplanar sequences for anatomical reference. Fibre tractography for visualisation of predefined pelvic floor and pelvic wall muscles was performed offline by two observers, applying a consensus method. Three eigenvalues (λ1, λ2, λ3), fractional anisotropy (FA) and mean diffusivity (MD) were calculated from the fibre trajectories. In all subjects fibre tractography resulted in a satisfactory anatomical representation of the pubovisceral muscle, perineal body, anal - and urethral sphincter complex and internal obturator muscle. Mean FA values ranged from 0.23 ± 0.02 to 0.30 ± 0.04, MD values from 1.30 ± 0.08 to 1.73 ± 0.12 × 10(-)³ mm²/s. Muscular structures in the superficial layer of the pelvic floor could not be satisfactorily identified. This study demonstrates the feasibility of visualising the complex three-dimensional pelvic floor architecture using 3T-DTI with fibre tractography. DTI of the deep female pelvic floor may provide new insights into pelvic floor disorder

    Research methods for subgrouping low back pain

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    <p>Abstract</p> <p>Background</p> <p>There is considerable clinician and researcher interest in whether the outcomes for patients with low back pain, and the efficiency of the health systems that treat them, can be improved by 'subgrouping research'. Subgrouping research seeks to identify subgroups of people who have clinically important distinctions in their treatment needs or prognoses. Due to a proliferation of research methods and variability in how subgrouping results are interpreted, it is timely to open discussion regarding a conceptual framework for the research designs and statistical methods available for subgrouping studies (a method framework). The aims of this debate article are: (1) to present a method framework to inform the design and evaluation of subgrouping research in low back pain, (2) to describe method options when investigating prognostic effects or subgroup treatment effects, and (3) to discuss the strengths and limitations of research methods suitable for the hypothesis-setting phase of subgroup studies.</p> <p>Discussion</p> <p>The proposed method framework proposes six phases for studies of subgroups: studies of assessment methods, hypothesis-setting studies, hypothesis-testing studies, narrow validation studies, broad validation studies, and impact analysis studies. This framework extends and relabels a classification system previously proposed by McGinn et al (2000) as suitable for studies of clinical prediction rules. This extended classification, and its descriptive terms, explicitly anchor research findings to the type of evidence each provides. The inclusive nature of the framework invites appropriate consideration of the results of diverse research designs. Method pathways are described for studies designed to test and quantify prognostic effects or subgroup treatment effects, and examples are discussed. The proposed method framework is presented as a roadmap for conversation amongst researchers and clinicians who plan, stage and perform subgrouping research.</p> <p>Summary</p> <p>This article proposes a research method framework for studies of subgroups in low back pain. Research designs and statistical methods appropriate for sequential phases in this research are discussed, with an emphasis on those suitable for hypothesis-setting studies of subgroups of people seeking care.</p

    Predictive factors for overactive bladder symptoms after pelvic organ prolapse surgery

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    Contains fulltext : 89696.pdf (publisher's version ) (Closed access)INTRODUCTION AND HYPOTHESIS: This study focussed on the factors which predict the presence of symptoms of overactive bladder (OAB) after surgery for pelvic organ prolapse (POP). METHODS: Consecutive women who underwent POP surgery with or without the use of vaginal mesh materials in the years 2004-2007 were included. Assessments were made preoperatively and at follow-up, including physical examination (POP-Q) and standardised questionnaires (IIQ, UDI and DDI). RESULTS: Five hundred and five patients were included with a median follow-up of 12.7 (6-35) months. Bothersome OAB symptoms decreased after POP surgery. De novo bothersome OAB symptoms appeared in 5-6% of the women. Frequency and urgency were more likely to improve as compared with urge incontinence and nocturia. The best predictor for the absence of postoperative symptoms was the absence of preoperative bothersome OAB symptoms. CONCLUSION: The absence of bothersome OAB symptoms preoperatively was the best predictor for the absence of postoperative symptoms.1 september 201

    A comparative analysis of Patient-Reported Expanded Disability Status Scale tools.

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    BACKGROUND: Patient-Reported Expanded Disability Status Scale (PREDSS) tools are an attractive alternative to the Expanded Disability Status Scale (EDSS) during long term or geographically challenging studies, or in pressured clinical service environments. OBJECTIVES: Because the studies reporting these tools have used different metrics to compare the PREDSS and EDSS, we undertook an individual patient data level analysis of all available tools. METHODS: Spearman's rho and the Bland-Altman method were used to assess correlation and agreement respectively. RESULTS: A systematic search for validated PREDSS tools covering the full EDSS range identified eight such tools. Individual patient data were available for five PREDSS tools. Excellent correlation was observed between EDSS and PREDSS with all tools. A higher level of agreement was observed with increasing levels of disability. In all tools, the 95% limits of agreement were greater than the minimum EDSS difference considered to be clinically significant. However, the intra-class coefficient was greater than that reported for EDSS raters of mixed seniority. The visual functional system was identified as the most significant predictor of the PREDSS-EDSS difference. CONCLUSION: This analysis will (1) enable researchers and service providers to make an informed choice of PREDSS tool, depending on their individual requirements, and (2) facilitate improvement of current PREDSS tools.University of Southampton and National Institute of Health Research (NIHR)

    Mixture of latent trait analyzers for model-based clustering of categorical data

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    Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone

    Visual inspection with acetic acid as a cervical cancer test: accuracy validated using latent class analysis

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    <p>Abstract</p> <p>Background</p> <p>The purpose of this study was to validate the accuracy of an alternative cervical cancer test – visual inspection with acetic acid (VIA) – by addressing possible imperfections in the gold standard through latent class analysis (LCA). The data were originally collected at peri-urban health clinics in Zimbabwe.</p> <p>Methods</p> <p>Conventional accuracy (sensitivity/specificity) estimates for VIA and two other screening tests using colposcopy/biopsy as the reference standard were compared to LCA estimates based on results from all four tests. For conventional analysis, negative colposcopy was accepted as a negative outcome when biopsy was not available as the reference standard. With LCA, local dependencies between tests were handled through adding direct effect parameters or additional latent classes to the model.</p> <p>Results</p> <p>Two models yielded good fit to the data, a 2-class model with two adjustments and a 3-class model with one adjustment. The definition of latent disease associated with the latter was more stringent, backed by three of the four tests. Under that model, sensitivity for VIA (abnormal+) was 0.74 compared to 0.78 with conventional analyses. Specificity was 0.639 versus 0.568, respectively. By contrast, the LCA-derived sensitivity for colposcopy/biopsy was 0.63.</p> <p>Conclusion</p> <p>VIA sensitivity and specificity with the 3-class LCA model were within the range of published data and relatively consistent with conventional analyses, thus validating the original assessment of test accuracy. LCA probably yielded more likely estimates of the true accuracy than did conventional analysis with in-country colposcopy/biopsy as the reference standard. Colpscopy with biopsy can be problematic as a study reference standard and LCA offers the possibility of obtaining estimates adjusted for referent imperfections.</p
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