988 resultados para Age Estimation


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A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

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The aim of the present study was to compare, under the same nursing conditions, the energy-nitrogen balance and the protein turnover in small for gestational age (SGA) and appropriate for gestational age (AGA) low birthweight infants. We compared 8 SGA's (mean +/- s.d.: gestational age 35 +/- 2 weeks, birthweight 1520 +/- 330 g) to 11 AGA premature infants (32 +/- 2 weeks, birthweight 1560 +/- 240 g). When their rate of weight gain was above 15 g/kg/d (17.6 +/- 3.0 and 18.2 +/- 2.6 g/kg/d, mean postnatal age 18 +/- 10 and 20 +/- 9 d respectively) they were studied with respect to their metabolizable energy intake, their energy expenditure, their energy and protein gain and their protein turnover. Energy balance was assessed by the difference between metabolizable energy and energy expenditure as measured by indirect calorimetry. Protein gain was calculated from the amount of retained nitrogen. Protein turnover was estimated by a stable isotope enrichment technique using repeated nasogastric administration of 15N-glycine for 72 h. Although there was no difference in their metabolizable energy intakes (110 +/- 12 versus 108 +/- 11 kcal/kg/d), SGA's had a higher rate of resting energy expenditure (64 +/- 8 versus 57 +/- 8 kcal/kg/d, P less than 0.05). Protein gain and composition of weight gain was very similar in both groups (2.0 +/- 0.4 versus 2.1 +/- 0.4 g protein/kg/d; 3.5 +/- 1.1 versus 3.3 +/- 1.4 g fat/kg/d in SGA's and AGA's respectively). However, the rate of protein synthesis was significantly lower in SGA's (7.7 +/- 1.6 g/kg/d) as compared to AGA's (9.7 +/- 2.8 g/kg/d; P less than 0.05). It is concluded that SGA's have a more efficient protein gain/protein synthesis ratio since for the same weight and protein gains, SGA's show a 20 per cent slower protein turnover. They might therefore tolerate slightly higher protein intakes. Postconceptional age seems to be an important factor in the regulation of protein turnover.

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The rat adrenal gland contains ganglion cells able to synthesize nitric oxide (NO). This messenger molecule controls and modulates adrenal secretory activity and blood flow. The present study analyzed the number, size, and distribution of NO-producing adrenal neurons in adulthood and during postnatal development by means of beta-nicotinamide adenine dinucleotide phosphate-diaphorase (NADPH-d) histochemistry. This method reliably visualizes the enzyme responsible for NO generation. The reactive neurons per adrenal gland were 350-400 in both male and female adult rats. The positive nerve cell bodies were mostly located in the medulla, few being detected within the cortex and the subcapsular region. Dual labeling with anti-microtubule-associated protein 2 antibody, specific for neuronal elements, confirmed this distribution. Anti-microtubule-associated protein 1b antibody identified a subset of NADPH-d-positive neurons, displaying different degrees of maturation according to their position within the adrenal gland. At birth, there were about 220 NADPH-d-labeled neurons per adrenal gland in both sexes. As confirmed by dual immunocytochemical labeling, their great majority was evenly distributed between the cortex and the subcapsular region, the medulla being practically devoid of stained neurons. After birth, the number of adrenal NADPH-d-positive ganglion cells displayed a strong postnatal increase and reached the adult-like distribution after 1-2 months. During the period of increase, there was a transient difference in the numbers of these cells in the two sexes. Thus we present here evidence of plasticity in the number, size, and distribution of NADPH-d-positive adrenal neurons between birth and adulthood; in addition, we describe transient sex-related differences in their number and distribution during the 2nd postnatal week, which are possibly related to the epigenetic action of gonadal hormones during this period.

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Individualized treatment regimens may reduce patient burden with satisfactory patient outcomes in neovascular age-related macular degeneration. Intravitreal anti-VEGF drugs are the current gold standard. Fixed monthly injections offer the best visual outcome but this regimen is not commonly followed outside clinical trials. A PRN regimen requires monthly visits where the patient is treated in the presence of signs of lesion activity. Therefore, an early detection of reactivation of the disease with immediate retreatment is crucial to prevent visual acuity loss. Several trials suggest that "treat and extend" and other proactive regimens provide a reasonable approach. The rationale of the proactive regimens is to perform treatment anticipating relapses or recurrences and therefore avoid drops in vision while individualizing patient followup. Treat and extend study results in significant direct medical cost savings from fewer treatments and office visits compared to monthly treatment. Current data suggest that, for one year, PRN is less expensive, but treat and extend regimen would likely be less expensive for subsequent years. Once a patient is not a candidate to continue with treatment, he/she should be sent to an outpatient unit with adequate resources to follow nAMD patients in order to reduce the burden of specialized ophthalmologist services.

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The MDRD (Modification of diet in renal disease) equation enables glomerular filtration rate (GFR) estimation from serum creatinine only. Thus, the laboratory can report an estimated GFR (eGFR) with each serum creatinine assessment, increasing therefore the recognition of renal failure. Predictive performance of MDRD equation is better for GFR < 60 ml/min/1,73 m2. A normal or near-normal renal function is often underestimated by this equation. Overall, MDRD provides more reliable estimations of renal function than the Cockcroft-Gault (C-G) formula, but both lack precision. MDRD is not superior to C-G for drug dosing. Being adjusted to 1,73 m2, MDRD eGFR has to be back adjusted to the patient's body surface area for drug dosing. Besides, C-G has the advantage of a greater simplicity and a longer use.

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Age and sex have been identified as predictors of outcome in malignant melanoma (MM). This aim of this multicentre, cross-sectional study was to analyse the role of age and sex as explanatory variables for the diagnosis of thin MM. A total of 2430 patients with MM were recruited. Cases of in situ-T1 MM were more frequent than T2-T4 MM (56.26% vs. 43.74%). Breslow thickness increased throughout decades of life (analysis of variance (ANOVA) p < 0.001), with a weak correlation between Breslow thickness and patient's age (r   = 0.202, p < 0.001). Breslow thickness was significantly less in women (1.79 vs. 2.38 mm, p = 0.0001). Binary logistic regression showed a significant (p < 0.001) odds ratio for age 0-29 years (1.18), and 30-59 years (1.16), and for women (1.09). Age and sex explained 3.64% of the variation observed in Tis-T1 frequency (R2 = 0.0364). Age and sex appear to explain a low percentage of the variation in the early detection of MM.

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In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

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Aim: Duration of untreated psychosis (DUP) refers to the time elapsing between psychosis onset and treatment initiation. Despite a certain degree of consensus regarding the definition of psychosis onset, the definition of treatment commencement varies greatly between studies and DUP may be underestimated due to lack of agreement. In the present study, three sets of criteria to define the end of the untreated period were applied in a first-episode psychosis cohort to assess the impact of the choice of definition on DUP estimation. Methods: The DUP of 117 patients admitted in the Treatment and Early Intervention in Psychosis Program Psychosis in Lausanne was measured using the following sets of criteria to define treatment onset: (i) initiation of antipsychotic medication; (ii) entry into a specialized programme; and (iii) entry into a specialized programme and adequate medication with a good compliance. Results: DUP varied greatly according to definitions, the most restrictive criteria leading to the longest DUP (median DUP1 = 2.2 months, DUP2 = 7.4 months and DUP3 = 13.6 months). A percentage of 19.7 of the patients who did not meet these restrictive criteria had poorer premorbid functioning and were more likely to use cannabis. Longer DUP3 was associated with poorer premorbid functioning and with younger age at onset of psychosis. Conclusion: These results underline the need for a unique and standardized definition of the end of DUP. We suggest that the most restrictive definition of treatment should be used when using the DUP concept in future research.

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SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

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BACKGROUND: Guidelines for the prevention of coronary heart disease (CHD) recommend use of Framingham-based risk scores that were developed in white middle-aged populations. It remains unclear whether and how CHD risk prediction might be improved among older adults. We aimed to compare the prognostic performance of the Framingham risk score (FRS), directly and after recalibration, with refit functions derived from the present cohort, as well as to assess the utility of adding other routinely available risk parameters to FRS.¦METHODS: Among 2193 black and white older adults (mean age, 73.5 years) without pre-existing cardiovascular disease from the Health ABC cohort, we examined adjudicated CHD events, defined as incident myocardial infarction, CHD death, and hospitalization for angina or coronary revascularization.¦RESULTS: During 8-year follow-up, 351 participants experienced CHD events. The FRS poorly discriminated between persons who experienced CHD events vs. not (C-index: 0.577 in women; 0.583 in men) and underestimated absolute risk prediction by 51% in women and 8% in men. Recalibration of the FRS improved absolute risk prediction, particulary for women. For both genders, refitting these functions substantially improved absolute risk prediction, with similar discrimination to the FRS. Results did not differ between whites and blacks. The addition of lifestyle variables, waist circumference and creatinine did not improve risk prediction beyond risk factors of the FRS.¦CONCLUSIONS: The FRS underestimates CHD risk in older adults, particularly in women, although traditional risk factors remain the best predictors of CHD. Re-estimated risk functions using these factors improve accurate estimation of absolute risk.