84 resultados para rank regression


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OBJECTIVE: Anemia is a common comorbid condition in various inflammatory states and an established predictor of mortality in patients with chronic heart failure, ischemic heart disease, and end-stage renal disease. The present study of patients with abdominal aortic aneurysm (AAA) undergoing endovascular repair (EVAR) assessed the relationships between baseline hemoglobin concentration and AAA size, as well as anemia and long-term survival. METHODS: Between March 1994 and November 2006, 711 patients (65 women, mean age 75.8 +/- 7.8 years) underwent elective EVAR. Anemia was defined as a hemoglobin level <13 g/dL in men and <12 g/dL in women. Post-EVAR mean follow-up was 48.3 +/- 32.0 months. Association of hemoglobin level with AAA size was assessed with multiple linear regression. Mortality was determined with use of the internet-based Social Security Death Index and the electronic hospital record. Kaplan-Meier survival curves of anemic and nonanemic patient groups were compared by the log-rank method. Multivariable logistic regression models were used to determine the influence of anemia on vital status after EVAR. RESULTS: A total of 218/711 (30.7%) of AAA patients undergoing EVAR had anemia at baseline. After adjustment for various risk factors, hemoglobin level was inversely related to maximum AAA diameter (beta: - .144, 95%-CI: -1.482 - .322, P = .002). Post-EVAR survival was 65.5% at 5 years and 44.4% at 10 years. In long-term follow-up, survival was significantly lower in patients with anemia as compared to patients without anemia (P < .0001 by log-rank). Baseline hemoglobin levels were independently related to long-term mortality in multivariable Cox regression analysis adjusted for various risk factors (adjusted HR: 0.866, 95% CI: .783 to .958, P = .005). Within this model, statin use (adjusted HR: .517, 95% CI: .308 to .868, P = .013) was independently related to long-term survival, whereas baseline AAA diameter (adjusted HR: 1.022, 95% CI: 1.009 to 1.036, P = .001) was an independently associated with increased mortality. CONCLUSIONS: Baseline hemoglobin concentration is independently associated with AAA size and reduced long-term survival following EVAR. Thus, the presence or absence of anemia offers a potential refinement of existing risk stratification instruments.

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BACKGROUND: Purpose of this study was to compare the correlation of statin use with long-term mortality in patients with abdominal (AAA) and thoracic aortic aneurysm (TAA). PATIENTS AND METHODS: We compared long-term survival of 731 AAA and 59 TAA patients undergoing elective endovascular repair (EVAR). Kaplan-Meier survival curves were compared by the log-rank method. Propensity score-adjusted multivariable logistic regression models were used to determine independent associations of statin use on vital status after EVAR. RESULTS: Statin use was associated with decreased long-term mortality in AAA patients in bivariate and multivariable regression analysis, in which the effect of propensity to receive a statin was considered (adjusted HR: .613, 95%-CI: .379- .993, p = .047) whereas mortality of TAA patients was not associated with use of statins (adjusted HR: 1.795, 95%-CI: .147 -21.942, p = .647). CONCLUSIONS: Use of statins is an independent predictor of decreased mortality after elective EVAR in AAA, but not in TAA patients. These findings indirectly support the concept of a distinct pathogenesis of AAA and TAA.

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OBJECTIVES: This paper is concerned with checking goodness-of-fit of binary logistic regression models. For the practitioners of data analysis, the broad classes of procedures for checking goodness-of-fit available in the literature are described. The challenges of model checking in the context of binary logistic regression are reviewed. As a viable solution, a simple graphical procedure for checking goodness-of-fit is proposed. METHODS: The graphical procedure proposed relies on pieces of information available from any logistic analysis; the focus is on combining and presenting these in an informative way. RESULTS: The information gained using this approach is presented with three examples. In the discussion, the proposed method is put into context and compared with other graphical procedures for checking goodness-of-fit of binary logistic models available in the literature. CONCLUSION: A simple graphical method can significantly improve the understanding of any logistic regression analysis and help to prevent faulty conclusions.

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OBJECTIVE: To determine if the receptor activator of nuclear factor-kappaB-receptor activator of nuclear factor-kappaB ligand-osteoprotegerin (RANK-RANKL-OPG) system is active in bone remodeling in dogs and, if so, whether differences in expression of these mediators occur in healthy and arthritic joints. STUDY DESIGN: Experimental study. SAMPLE POPULATION: Fragmented processus coronoidei (n=20) were surgically removed from dogs with elbow arthritis and 5 corresponding healthy samples from dogs euthanatized for reasons other than elbow joint disease. METHODS: Bright-field immunohistochemistry and high-resolution fluorescence microscopy were used to investigate the distribution of RANK, RANKL, and OPG in healthy and arthritic joints. RESULTS: All 3 molecules were identified by immunostaining of canine bone tissue. In elbow dysplasia, the number of RANK-positive osteoclasts was increased. In their vicinity, cells expressing RANKL, a mediator of osteoclast activation, were abundant whereas the number of osteoblasts having the potential to limit osteoclastogenesis and bone resorption via OPG was few. CONCLUSIONS: The RANK-RANKL-OPG system is active in bone remodeling in dogs. In elbow dysplasia, a surplus of molecules promoting osteoclastogenesis was evident and is indicative of an imbalance between the mediators regulating bone resorption and bone formation. Both OPG and neutralizing antibodies against RANKL have the potential to counterbalance bone resorption. CLINICAL RELEVANCE: Therapeutic use of neutralizing antibodies against RANKL to inhibit osteoclast activation warrants further investigation.

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In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

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INTRODUCTION The objective of this trial was to compare the survival rates of mandibular lingual retainers bonded with either chemically cured or light-cured adhesive after orthodontic treatment. METHODS Patients having undergone orthodontic treatment at a private orthodontic office were randomly allocated to fixed retainers placed with chemically cured composite or light-cured composite. Eligibility criteria included no active caries, restorations, or fractures on the mandibular anterior teeth, and adequate oral hygiene. The main outcome was any type of first-time lingual retainer breakage; pattern of failure (adapted adhesive remnant index scores) was a secondary outcome. Randomization was accomplished with random permuted blocks of 20 patients with allocation concealed in sequentially numbered, opaque, sealed envelopes. Blinding was applicable for outcome assessment only. Patients were reviewed at 1, 3, and 6 months and then every 6 months after placement of the retainer until completion of the study. Data were analyzed using survival analysis including Cox regression; sensitivity analysis was carried out after data imputation for subjects lost to follow-up. RESULTS Two hundred twenty patients (median age, 16 years; interquartile range, 2; range, 12-47 years) were randomized in a 1:1 ratio to either chemical or light curing. Baseline characteristics were similar between groups, the median follow-up period was 2.19 years (range, 0.003-3.64 years), and 16 patients were lost to follow-up. At a minimum follow-up of 2 years, 47 of 110 (42.7%) and 55 of 110 (50.0%) retainers had some type of failure with chemically cured and light-cured adhesive, respectively (log-rank test, P = 0.35). Data were analyzed on an intention-to-treat basis, and the hazard ratio (HR) was 1.15 (95% confidence interval [CI], 0.88-1.70; P = 0.47). There was weak evidence that age is a significant predictor for lingual retainer failures (HR, 0.96; 95% CI, 0.93-1.00; P = 0.08). Adhesive remnant index scoring was possible for only 66 of the 102 (64.7%) failures and did not differ between composites (Fisher exact test, P = 0.16). No serious harm was observed other than gingivitis associated with plaque accumulation. CONCLUSIONS The results of this study indicated no evidence that survival of mandibular lingual retainers differs between chemically and light-cured adhesives. The overall failure rate was 46.4%; however, this included any type of failure, which may have exaggerated the overall failure rate.

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The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA)accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias = −14 ± 22 counts) but not for horizontal counts (−17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.

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This paper introduces and analyzes a stochastic search method for parameter estimation in linear regression models in the spirit of Beran and Millar [Ann. Statist. 15(3) (1987) 1131–1154]. The idea is to generate a random finite subset of a parameter space which will automatically contain points which are very close to an unknown true parameter. The motivation for this procedure comes from recent work of Dümbgen et al. [Ann. Statist. 39(2) (2011) 702–730] on regression models with log-concave error distributions.