957 resultados para Average Rank


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Approximate entropy (ApEn) of blood pressure (BP) can be easily measured based on software analysing 24-h ambulatory BP monitoring (ABPM), but the clinical value of this measure is unknown. In a prospective study we investigated whether ApEn of BP predicts, in addition to average and variability of BP, the risk of hypertensive crisis. In 57 patients with known hypertension we measured ApEn, average and variability of systolic and diastolic BP based on 24-h ABPM. Eight of these fifty-seven patients developed hypertensive crisis during follow-up (mean follow-up duration 726 days). In bivariate regression analysis, ApEn of systolic BP (P<0.01), average of systolic BP (P=0.02) and average of diastolic BP (P=0.03) were significant predictors of hypertensive crisis. The incidence rate ratio of hypertensive crisis was 14.0 (95% confidence interval (CI) 1.8, 631.5; P<0.01) for high ApEn of systolic BP as compared to low values. In multivariable regression analysis, ApEn of systolic (P=0.01) and average of diastolic BP (P<0.01) were independent predictors of hypertensive crisis. A combination of these two measures had a positive predictive value of 75%, and a negative predictive value of 91%, respectively. ApEn, combined with other measures of 24-h ABPM, is a potentially powerful predictor of hypertensive crisis. If confirmed in independent samples, these findings have major clinical implications since measures predicting the risk of hypertensive crisis define patients requiring intensive follow-up and intensified therapy.

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OBJECTIVE: Lateral ridge augmentations are traditionally performed using autogenous bone grafts to support membranes for guided bone regeneration (GBR). The bone-harvesting procedure, however, is accompanied by considerable patient morbidity. AIM: The aim of the present study was to test whether or not resorbable membranes and bone substitutes will lead to successful horizontal ridge augmentation allowing implant installation under standard conditions. MATERIAL AND METHODS: Twelve patients in need of implant therapy participated in this study. They revealed bone deficits in the areas intended for implant placement. Soft tissue flaps were carefully raised and blocks or particles of deproteinized bovine bone mineral (DBBM) (Bio-Oss) were placed in the defect area. A collagenous membrane (Bio-Gide) was applied to cover the DBBM and was fixed to the surrounding bone using poly-lactic acid pins. The flaps were sutured to allow for healing by primary intention. RESULTS: All sites in the 12 patients healed uneventfully. No flap dehiscences and no exposures of membranes were observed. Nine to 10 months following augmentation surgery, flaps were raised in order to visualize the outcomes of the augmentation. An integration of the DBBM particles into the newly formed bone was consistently observed. Merely on the surface of the new bone, some pieces of the grafting material were only partly integrated into bone. However, these were not encapsulated by connective tissue but rather anchored into the newly regenerated bone. In all of the cases, but one, the bone volume following regeneration was adequate to place implants in a prosthetically ideal position and according to the standard protocol with complete bone coverage of the surface intended for osseointegration. Before the regenerative procedure, the average crestal bone width was 3.2 mm and to 6.9 mm at the time of implant placement. This difference was statistically significant (P<0.05, Wilcoxon's matched pairs signed-rank test). CONCLUSION: After a healing period of 9-10 months, the combination of DBBM and a collagen membrane is an effective treatment option for horizontal bone augmentation before implant placement.

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PURPOSE: The aim of this study was to assess long-term changes in position of soft tissue landmarks following mandibular advancement and setback surgery. MATERIALS AND METHODS: Twenty-seven patients (14 women, 13 men; mean age, 36 years) who had undergone either mandibular advancement (15 patients) or setback surgery (12 patients), were available for a long-term follow-up an average of 12 years postoperatively. In all of these cases, lateral cephalometric radiographs taken immediately before operation, at 1 week, 14 months, and 12 years postoperatively, were studied. RESULTS: During the 14 months postoperatively, soft tissue chin and mentolabial fold followed its underlying hard tissue in all patients. A continuous skeletal relapse was observable 12 years after mandibular advancement, but soft tissue chin moved more in an anterior direction. After mandibular setback, soft and hard tissue landmarks remained almost unchanged. Over the entire observation period, a thickening of soft tissue at pogonion was generally seen, and particularly a thickening of the whole chin in the setback group. All patients showed a significant lengthening and thinning of the upper lip. In all except 2 males, the patient's body weight increased markedly. CONCLUSION: In contrast to the immediate postoperative stage, soft tissue changes observed an average of 12 years after the primary operation do not directly follow the movements of the underlying skeletal structure. The soft tissue profile changes observed over such a long term seem to be influenced not only by the underlying skeletal structure but also by other factors such as weight gain and aging process.

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PURPOSE: To prospectively determine quantitatively and qualitatively the timing of maximal enhancement of the normal small-bowel wall by using contrast material-enhanced multi-detector row computed tomography (CT). MATERIALS AND METHODS: This HIPAA-compliant study was approved by the institutional review board. After information on radiation risk was given, written informed consent was obtained from 25 participants with no history of small-bowel disease (mean age, 58 years; 19 men) who had undergone single-level dynamic CT. Thirty seconds after the intravenous administration of contrast material, a serial dynamic acquisition, consisting of 10 images obtained 5 seconds apart, was performed. Enhancement measurements were obtained over time from the small-bowel wall and the aorta. Three independent readers qualitatively assessed small-bowel conspicuity. Quantitative and qualitative data were analyzed during the arterial phase, the enteric phase (which represented peak small-bowel mural enhancement), and the venous phase. Statistical analysis included paired Student t test and Wilcoxon signed rank test with Bonferroni correction. A P value less than .05 was used to indicate a significant difference. RESULTS: The mean time to peak enhancement of the small-bowel wall was 49.3 seconds +/- 7.7 (standard deviation) and 13.5 seconds +/- 7.6 after peak aortic enhancement. Enhancement values were highest during the enteric phase (P < .05). Regarding small-bowel conspicuity, images obtained during the enteric phase were most preferred qualitatively; there was a significant difference between the enteric and arterial phases (P < .001) but not between the enteric and venous phases (P = .18). CONCLUSION: At multi-detector row CT, peak mural enhancement of the normal small bowel occurs on average about 50 seconds after intravenous administration of contrast material or 14 seconds after peak aortic enhancement.

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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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The estimation of the average travel distance in a low-level picker-to-part order picking system can be done by analytical methods in most cases. Often a uniform distribution of the access frequency over all bin locations is assumed in the storage system. This only applies if the bin location assignment is done randomly. If the access frequency of the articles is considered in the bin location assignment to reduce the average total travel distance of the picker, the access frequency over the bin locations of one aisle can be approximated by an exponential density function or any similar density function. All known calculation methods assume that the average number of orderlines per order is greater than the number of aisles of the storage system. In case of small orders this assumption is often invalid. This paper shows a new approach for calculating the average total travel distance taking into account that the average number of orderlines per order is lower than the total number of aisles in the storage system and the access frequency over the bin locations of an aisle can be approximated by any density function.

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This article presents a new response time measure of evaluations, the Evaluative Movement Assessment (EMA). Two properties are verified for the first time in a response time measure: (a) mapping of multiple attitude objects to a single scale, and (b) centering that scale around a neutral point. Property (a) has implications when self-report and response time measures of attitudes have a low correlation. A study using EMA as an indirect measure revealed a low correlation with self-reported attitudes when the correlation reflected between-subjects differences in preferences for one attitude object to a second. Previously this result may have been interpreted as dissociation between two measures. However, when correlations from the same data reflected within-subject preference rank orders between multiple attitude objects, they were substantial (average r = .64). This result suggests that the presence of low correlations between self-report and response time measures in previous studies may be a reflection of methodological aspects of the response time measurement techniques. Property (b) has implications for exploring theoretical questions that require assessment of whether an evaluation is positive or negative (e.g., prejudice), because it allows such classifications in response time measurement to be made for the first time.

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We consider the problem of fitting a union of subspaces to a collection of data points drawn from one or more subspaces and corrupted by noise and/or gross errors. We pose this problem as a non-convex optimization problem, where the goal is to decompose the corrupted data matrix as the sum of a clean and self-expressive dictionary plus a matrix of noise and/or gross errors. By self-expressive we mean a dictionary whose atoms can be expressed as linear combinations of themselves with low-rank coefficients. In the case of noisy data, our key contribution is to show that this non-convex matrix decomposition problem can be solved in closed form from the SVD of the noisy data matrix. The solution involves a novel polynomial thresholding operator on the singular values of the data matrix, which requires minimal shrinkage. For one subspace, a particular case of our framework leads to classical PCA, which requires no shrinkage. For multiple subspaces, the low-rank coefficients obtained by our framework can be used to construct a data affinity matrix from which the clustering of the data according to the subspaces can be obtained by spectral clustering. In the case of data corrupted by gross errors, we solve the problem using an alternating minimization approach, which combines our polynomial thresholding operator with the more traditional shrinkage-thresholding operator. Experiments on motion segmentation and face clustering show that our framework performs on par with state-of-the-art techniques at a reduced computational cost.

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OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.