130 resultados para Interval generalized set
em Université de Lausanne, Switzerland
International consensus conference on PFAPA syndrome: Evaluation of a new set of diagnostic criteria
Resumo:
The PFAPA syndrome is characterized by periodic fever, associated with pharyngitis, cervical adenitis and/or aphtous stomatitis and belongs to the auto-inflammatory diseases. Diagnostic criteria are based on clinical features and the exclusion of other periodic fever syndromes. An analysis of a large cohort of patients has shown weaknesses for these criteria and there is a lack of international consensus. An International Conference was held in Morges in November 2008 to propose a new set of classification criteria based on a consensus among experts in the field. We aimed to verify the applicability of the new set of classification criteria. 80 patients diagnosed with PFAPA syndrome from 3 centers (Genoa, Lausanne and Geneva) for pediatric rheumatology were included in the study. A detailed description of the clinical and laboratory features was obtained. The new classification criteria and the actual diagnostic criteria were applied to the patients. Only 43/80 patients (53.8%) fulfilled all criteria of the new classification. 31 patients were excluded because they didn't meet one of the 7 diagnostic criteria, 8 because of 2 criteria, and one because of 3 criteria. When we applied the current criteria to the same patients, 11/80 patients (13%) needed to be excluded. 8/80 patients (10%) were excluded from both sets. Exclusion was related only to some of the criteria. Number of patients for each not fulfilled criterion (new set of criteria/actual criteria): age (1/6), symptoms between episodes (2/2), delayed growth (3/3), main symptoms (21/0), periodicity, length of fever, interval between episodes, and length of disease (19/0). The application of some of the new criteria was not easy, as they were both very restrictive and needed precise information from the patients. Our work has shown that the new set of classification criteria can be applied to patients suspected for PFAPA syndrome, but it seems to be more restrictive than the actual diagnostic criteria. A further work of validation needs to be done for this new set of classification criteria in order to determine if these criteria allow a good discrimination between PFAPA patients and other causes of recurrent fever syndromes.
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INTRODUCTION: PFAPA syndrome is characterized by periodic fever, associated with pharyngitis, cervical adenitis and/or aphthous stomatitis and belongs to the auto-inflammatory diseases. Diagnostic criteria are based on clinical features and the exclusion of other periodic fever syndromes. An analysis of a large cohort of patients has shown weaknesses for these criteria and there is a lack of international consensus. An International Conference was held in Morges in November 2008 to propose a new set of classification criteria based on a consensus among experts in the field.OBJECTIVE: We aimed to verify the applicability of the new set of classification criteria.PATIENTS & METHODS: 80 patients diagnosed with PFAPA syndrome from 3 centers (Genoa, Lausanne and Geneva) for pediatric rheumatology were included in the study. A detailed description of the clinical and laboratory features was obtained. The new classification criteria and the actual diagnostic criteria were applied to the patients.RESULTS: Only 40/80 patients (50%) fulfilled all criteria of the new classification. 31 patients were excluded because they didn't meet one of the 7 diagnostic criteria, 7 because of 2 criteria, and one because of 3 criteria. When we applied the current criteria to the same patients, 11/80 patients (13.7%) needed to be excluded. 8/80 patients (10%) were excluded from both sets. Exclusion was related only to some of the criteria. Number of patients for each not fulfilled criterion (new set of criteria/actual criteria): age (1/6), symptoms between episodes (2/2), delayed growth (4/1), main symptoms (21/0), periodicity, length of fever, interval between episodes, and length of disease (20/0). The application of some of the new criteria was not easy, as they were both very restrictive and needed precise information from the patients.CONCLUSION: Our work has shown that the new set of classification criteria can be applied to patients suspected for PFAPA syndrome, but it seems to be more restrictive than the actual diagnostic criteria. A further work of validation needs to be done in order to determine if this new set of classification criteria allow a good discrimination between PFAPA patients and other causes of recurrent fever syndromes.
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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.
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OBJECTIVE: To compare interval breast cancer rates (ICR) between a biennial organized screening programme in Norway and annual opportunistic screening in North Carolina (NC) for different conceptualizations of interval cancer. SETTING: Two regions with different screening practices and performance. METHODS: 620,145 subsequent screens (1996-2002) performed in women aged 50-69 and 1280 interval cancers were analysed. Various definitions and quantification methods for interval cancers were compared. RESULTS: ICR for one year follow-up were lower in Norway compared with NC both when the rate was based on all screens (0.54 versus 1.29 per 1000 screens), negative final assessments (0.54 versus 1.29 per 1000 screens), and negative screening assessments (0.53 versus 1.28 per 1000 screens). The rate of ductal carcinoma in situ was significantly lower in Norway than in NC for cases diagnosed in both the first and second year after screening. The distributions of histopathological tumour size and lymph node involvement in invasive cases did not differ between the two regions for interval cancers diagnosed during the first year after screening. In contrast, in the second year after screening, tumour characteristics remained stable in Norway but became prognostically more favorable in NC. CONCLUSION: Even when applying a common set of definitions of interval cancer, the ICR was lower in Norway than in NC. Different definitions of interval cancer did not influence the ICR within Norway or NC. Organization of screening and screening performance might be major contributors to the differences in ICR between Norway and NC.
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As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.
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OBJECTIVE: To identify the clinical determinants of occurrence of postictal generalized EEG suppression (PGES) after generalized convulsive seizures (GCS). METHODS: We reviewed the video-EEG recordings of 417 patients included in the REPO2MSE study, a multicenter prospective cohort study of patients with drug-resistant focal epilepsy. According to ictal semiology, we classified GCS into 3 types: tonic-clonic GCS with bilateral and symmetric tonic arm extension (type 1), clonic GCS without tonic arm extension or flexion (type 2), and GCS with unilateral or asymmetric tonic arm extension or flexion (type 3). Association between PGES and person-specific or seizure-specific variables was analyzed after correction for individual effects and the varying number of seizures. RESULTS: A total of 99 GCS in 69 patients were included. Occurrence of PGES was independently associated with GCS type (p < 0.001) and lack of early administration of oxygen (p < 0.001). Odds ratio (OR) for GCS type 1 in comparison with GCS type 2 was 66.0 (95% confidence interval [CI 5.4-801.6]). In GCS type 1, risk of PGES was significantly increased when the seizure occurred during sleep (OR 5.0, 95% CI 1.2-20.9) and when oxygen was not administered early (OR 13.4, 95% CI 3.2-55.9). CONCLUSION: The risk of PGES dramatically varied as a function of GCS semiologic characteristics. Whatever the type of GCS, occurrence of PGES was prevented by early administration of oxygen.
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A nationwide survey was launched to investigate the use of fluoroscopy and establish national reference levels (RL) for dose-intensive procedures. The 2-year investigation covered five radiology and nine cardiology departments in public hospitals and private clinics, and focused on 12 examination types: 6 diagnostic and 6 interventional. A total of 1,000 examinations was registered. Information including the fluoroscopy time (T), the number of frames (N) and the dose-area product (DAP) was provided. The data set was used to establish the distributions of T, N and the DAP and the associated RL values. The examinations were pooled to improve the statistics. A wide variation in dose and image quality in fixed geometry was observed. As an example, the skin dose rate for abdominal examinations varied in the range of 10 to 45 mGy/min for comparable image quality. A wide variability was found for several types of examinations, mainly complex ones. DAP RLs of 210, 125, 80, 240, 440 and 110 Gy cm2 were established for lower limb and iliac angiography, cerebral angiography, coronary angiography, biliary drainage and stenting, cerebral embolization and PTCA, respectively. The RL values established are compared to the data published in the literature.
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Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.
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In many fields, the spatial clustering of sampled data points has many consequences. Therefore, several indices have been proposed to assess the level of clustering affecting datasets (e.g. the Morisita index, Ripley's Kfunction and Rényi's generalized entropy). The classical Morisita index measures how many times it is more likely to select two measurement points from the same quadrats (the data set is covered by a regular grid of changing size) than it would be in the case of a random distribution generated from a Poisson process. The multipoint version (k-Morisita) takes into account k points with k >= 2. The present research deals with a new development of the k-Morisita index for (1) monitoring network characterization and for (2) detection of patterns in monitored phenomena. From a theoretical perspective, a connection between the k-Morisita index and multifractality has also been found and highlighted on a mathematical multifractal set.
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BACKGROUND: QT interval prolongation carries an increased risk of torsade de pointes and death. AIM: We sought to determine the prevalence of QT prolongation in medical inpatients and to identify determinants of this condition. METHODS: We enrolled consecutive patients who were admitted to the internal medicine ward and who had an electrocardiogram performed within 24 h of admission. We collected information on baseline patient characteristics and the use of QT-prolonging drugs. Two blinded readers manually measured the QT intervals. QT intervals were corrected for heart rate using the traditional Bazett formula and the linear regression-based Framingham formula. We used logistic regression to identify patient characteristics and drugs that were independently associated with QTc prolongation. RESULTS: Of 537 inpatients, 22.3% had a prolonged QTc based on the Bazett formula. The adjusted odds for QTc prolongation based on the Bazett correction were significantly higher in patients who had liver disease (OR 2.9, 95% CI: 1.5-5.6), hypokalaemia (OR 3.3, 95% CI: 1.9-5.6) and who were taking ≥1 QT-prolonging drug at admission (OR 1.7, 95% CI: 1.1-2.6). Overall, 50.8% of patients with QTc prolongation received additional QT-prolonging drugs during hospitalisation. CONCLUSIONS: The prevalence of QTc prolongation was high among medical inpatients but depended on the method used to correct for heart rate. The use of QT-prolonging drugs, hypokalaemia and liver disease increased the risk of QTc prolongation. Many patients with QTc prolongation received additional QT-prolonging drugs during hospitalisation, further increasing the risk of torsade de pointes and death.
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RésuméIntroduction : Le travail de thèse est un article publié dans le journal « Fertility & Sterility » s'intitulant « Birth records from Swiss married couples analyzed over the past 35 years reveal an aging of first-time mothers by 5.1 years while the interpregnancy interval has shortened ».Méthodes : Les données concernant l'âge auquel les femmes mariées donnaient naissance ont été obtenues de l'Office fédéral de la statistique. Nous avons examiné la période allant de 1969 à 2006. Cet intervalle de temps choisi nous a permis de prendre en considération un total de 2'716'370 naissances. L'âge moyen des parturientes à la naissance de leur 1er, 2ème et 3ème enfant a été calculé pour chaque année à l'aide du logiciel Excel. Grâce à ces données on a pu obtenir les intervalles inter-gestationnels théoriques entre le 1er et 2ème enfant, ainsi qu'entre le 2ème et 3ème enfant.Résultats : Nous pouvons constater que l'intervalle inter-gestationnel théorique entre la première et la deuxième grossesse était de 23.2 mois en 1969 et passait à 13.0 mois en 2006. L'intervalle compris entre la deuxième et la troisième grossesse passait de 22.4 mois en 1969 à 7.9 mois en 2006. Notre analyse suggère donc que c'est le facteur social qui exerce un effet plus important que le facteur biologique sur les intervalles inter-gestationnels, car ces intervalles diminuaient malgré l'augmentation de l'âge des mères à la naissance.
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An ab initio structure prediction approach adapted to the peptide-major histocompatibility complex (MHC) class I system is presented. Based on structure comparisons of a large set of peptide-MHC class I complexes, a molecular dynamics protocol is proposed using simulated annealing (SA) cycles to sample the conformational space of the peptide in its fixed MHC environment. A set of 14 peptide-human leukocyte antigen (HLA) A0201 and 27 peptide-non-HLA A0201 complexes for which X-ray structures are available is used to test the accuracy of the prediction method. For each complex, 1000 peptide conformers are obtained from the SA sampling. A graph theory clustering algorithm based on heavy atom root-mean-square deviation (RMSD) values is applied to the sampled conformers. The clusters are ranked using cluster size, mean effective or conformational free energies, with solvation free energies computed using Generalized Born MV 2 (GB-MV2) and Poisson-Boltzmann (PB) continuum models. The final conformation is chosen as the center of the best-ranked cluster. With conformational free energies, the overall prediction success is 83% using a 1.00 Angstroms crystal RMSD criterion for main-chain atoms, and 76% using a 1.50 Angstroms RMSD criterion for heavy atoms. The prediction success is even higher for the set of 14 peptide-HLA A0201 complexes: 100% of the peptides have main-chain RMSD values < or =1.00 Angstroms and 93% of the peptides have heavy atom RMSD values < or =1.50 Angstroms. This structure prediction method can be applied to complexes of natural or modified antigenic peptides in their MHC environment with the aim to perform rational structure-based optimizations of tumor vaccines.
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Plant membrane compartments and trafficking pathways are highly complex, and are often distinct from those of animals and fungi. Progress has been made in defining trafficking in plants using transient expression systems. However, many processes require a precise understanding of plant membrane trafficking in a developmental context, and in diverse, specialized cell types. These include defense responses to pathogens, regulation of transporter accumulation in plant nutrition or polar auxin transport in development. In all of these cases a central role is played by the endosomal membrane system, which, however, is the most divergent and ill-defined aspect of plant cell compartmentation. We have designed a new vector series, and have generated a large number of stably transformed plants expressing membrane protein fusions to spectrally distinct, fluorescent tags. We selected lines with distinct subcellular localization patterns, and stable, non-toxic expression. We demonstrate the power of this multicolor 'Wave' marker set for rapid, combinatorial analysis of plant cell membrane compartments, both in live-imaging and immunoelectron microscopy. Among other findings, our systematic co-localization analysis revealed that a class of plant Rab1-homologs has a much more extended localization than was previously assumed, and also localizes to trans-Golgi/endosomal compartments. Constructs that can be transformed into any genetic background or species, as well as seeds from transgenic Arabidopsis plants, will be freely available, and will promote rapid progress in diverse areas of plant cell biology.