990 resultados para JOINT POINT REGRESSION
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Référence bibliographique : Rol, 54890
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Référence bibliographique : Rol, 54858
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Given the significant impact the use of glucocorticoids can have on fracture risk independent of bone density, their use has been incorporated as one of the clinical risk factors for calculating the 10-year fracture risk in the World Health Organization's Fracture Risk Assessment Tool (FRAX(®)). Like the other clinical risk factors, the use of glucocorticoids is included as a dichotomous variable with use of steroids defined as past or present exposure of 3 months or more of use of a daily dose of 5 mg or more of prednisolone or equivalent. The purpose of this report is to give clinicians guidance on adjustments which should be made to the 10-year risk based on the dose, duration of use and mode of delivery of glucocorticoids preparations. A subcommittee of the International Society for Clinical Densitometry and International Osteoporosis Foundation joint Position Development Conference presented its findings to an expert panel and the following recommendations were selected. 1) There is a dose relationship between glucocorticoid use of greater than 3 months and fracture risk. The average dose exposure captured within FRAX(®) is likely to be a prednisone dose of 2.5-7.5 mg/day or its equivalent. Fracture probability is under-estimated when prednisone dose is greater than 7.5 mg/day and is over-estimated when the prednisone dose is less than 2.5 mg/day. 2) Frequent intermittent use of higher doses of glucocorticoids increases fracture risk. Because of the variability in dose and dosing schedule, quantification of this risk is not possible. 3) High dose inhaled glucocorticoids may be a risk factor for fracture. FRAX(®) may underestimate fracture probability in users of high dose inhaled glucocorticoids. 4) Appropriate glucocorticoid replacement in individuals with adrenal insufficiency has not been found to increase fracture risk. In such patients, use of glucocorticoids should not be included in FRAX(®) calculations.
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Référence bibliographique : Rol, 55021
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Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.
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Référence bibliographique : Rol, 55017
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Référence bibliographique : Rol, 55016
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Référence bibliographique : Rol, 54845
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Référence bibliographique : Rol, 55300
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Référence bibliographique : Rol, 54794
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Référence bibliographique : Rol, 55012
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Cervical cancer is a public health concern as it represents the second cause of cancer death in women worldwide. High-risk human papillomaviruses (HPV) are the etiologic agents, and HPV E6 and/or E7 oncogene-specific therapeutic vaccines are under development to treat HPV-related lesions in women. Whether the use of mucosal routes of immunization may be preferable for inducing cell-mediated immune responses able to eradicate genital tumors is still debated because of the uniqueness of the female genital mucosa (GM) and the limited experimentation. Here, we compared the protective activity resulting from immunization of mice via intranasal (i.n.), intravaginal (IVAG) or subcutaneous (s.c.) routes with an adjuvanted HPV type 16 E7 polypeptide vaccine. Our data show that s.c. and i.n. immunizations elicited similar frequencies and avidity of TetE71CD81 and E7-specific Interferon-gamma-secreting cells in the GM, whereas slightly lower immune responses were induced by IVAG immunization. In a novel orthotopic murine model, both s.c. and i.n. immunizations allowed for complete long-term protection against genital E7-expressing tumor challenge. However, only s.c. immunization induced complete regression of already established genital tumors. This suggests that the higher E7-specific systemic response observed after s.c. immunization may contribute to the regression of growing genital tumors, whereas local immune responses may be sufficient to impede genital challenges. Thus, our data show that for an efficiently adjuvanted protein-based vaccine, parenteral vaccination route is superior to mucosal vaccination route for inducing regression of established genital tumors in a murine model of HPV-associated genital cancer.
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X-ray is a technology that is used for numerous applications in the medical field. The process of X-ray projection gives a 2-dimension (2D) grey-level texture from a 3- dimension (3D) object. Until now no clear demonstration or correlation has positioned the 2D texture analysis as a valid indirect evaluation of the 3D microarchitecture. TBS is a new texture parameter based on the measure of the experimental variogram. TBS evaluates the variation between 2D image grey-levels. The aim of this study was to evaluate existing correlations between 3D bone microarchitecture parameters - evaluated from μCT reconstructions - and the TBS value, calculated on 2D projected images. 30 dried human cadaveric vertebrae were acquired on a micro-scanner (eXplorer Locus, GE) at isotropic resolution of 93 μm. 3D vertebral body models were used. The following 3D microarchitecture parameters were used: Bone volume fraction (BV/TV), Trabecular thickness (TbTh), trabecular space (TbSp), trabecular number (TbN) and connectivity density (ConnD). 3D/2D projections has been done by taking into account the Beer-Lambert Law at X-ray energy of 50, 100, 150 KeV. TBS was assessed on 2D projected images. Correlations between TBS and the 3D microarchitecture parameters were evaluated using a linear regression analysis. Paired T-test is used to assess the X-ray energy effects on TBS. Multiple linear regressions (backward) were used to evaluate relationships between TBS and 3D microarchitecture parameters using a bootstrap process. BV/TV of the sample ranged from 18.5 to 37.6% with an average value at 28.8%. Correlations' analysis showedthat TBSwere strongly correlatedwith ConnD(0.856≤r≤0.862; p<0.001),with TbN (0.805≤r≤0.810; p<0.001) and negatively with TbSp (−0.714≤r≤−0.726; p<0.001), regardless X-ray energy. Results show that lower TBS values are related to "degraded" microarchitecture, with low ConnD, low TbN and a high TbSp. The opposite is also true. X-ray energy has no effect onTBS neither on the correlations betweenTBS and the 3Dmicroarchitecture parameters. In this study, we demonstrated that TBS was significantly correlated with 3D microarchitecture parameters ConnD and TbN, and negatively with TbSp, no matter what X-ray energy has been used. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: None declared.
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Introduction: The Charlson index (Charlson, 1987) is a commonly used comorbidity index in outcome studies. Still, the use of different weights makes its calculation cumbersome, while the sum of its components (comorbidities) is easier to compute. In this study, we assessed the effects of 1) the Charlson index adapted for the Swiss population and 2) the sum of its components (number of comorbidities, maximum 15) on a) in-hospital deaths and b) cost of hospitalization. Methods: Anonymous data was obtained from the administrative database of the department of internal medicine of the Lausanne University Hospital (CHUV). All hospitalizations of adult (>=18 years) patients occurring between 2003 and 2011 were included. For each hospitalization, the Charlson index and the number of comorbidities were calculated. Analyses were conducted using Stata. Results: Data from 32,741 hospitalizations occurring between 2003 and 2011 was analyzed. On bivariate analysis, both the Charlson index and the number of comorbidities were significantly and positively associated with in hospital death. Conversely, multivariate adjustment for age, gender and calendar year using Cox regression showed that the association was no longer significant for the number of comorbidities (table). On bivariate analysis, hospitalization costs increased both with Charlson index and with number of comorbidities, but the increase was much steeper for the number of comorbidities (figure). Robust regression after adjusting for age, gender, calendar year and duration of hospital stay showed that the increase in one comorbidity led to an average increase in hospital costs of 321 CHF (95% CI: 272 to 370), while the increase in one score point of the Charlson index led to a decrease in hospital costs of 49 CHF (95% CI: 31 to 67). Conclusion: Charlson index is better than the number of comorbidities in predicting in-hospital death. Conversely, the number of comorbidities significantly increases hospital costs.
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We carried out a descriptive, retrospective study with a sample side of 121 patients with Legión® prosthesis replacement in our Vírgen del Rocío hospital area, in the city of Seville, from May of 2008 until March of 2011. This study included epidemiological data as well as technical information about the process performed, including post-operative pain, mobility and functional results using a functional assessment scale and series of radiological studies. Average follow-up was 19 months, with a mean age of 71 years and 87% women. We obtained an average of 20.41º for articular balance obtained, correction of prior deformities by restoring the tibia-femoral axis to the anatomic e balance articular angle; we resolved bone loss prior to replacement and carried out an adequate balance of the inter-lineal joint. 66% of the patients continued with no post-operative pain, with the other 33% reporting slight to moderate pain. With regards to pain at the point of the stem, we have found no significant relationship with the incidence angle of the stem on the cortical or with the type of cement. We observed a 74% rate of intervention without complications, with complications being rupture of the patellar tendon in one patient, one case of peri-prosthesis fracture, two iatrogenic avulsion fractures of the anterior tibial tuberosity and seven infections (4 were diagnosed previously).