Evaluation of quality improvement for cesarean sections caesarean section programmes through mixed methods.

BACKGROUND The rate of avoidable caesarean sections (CS) could be reduced through multifaceted strategies focusing on the involvement of health professionals and compliance with clinical practice guidelines (CPGs). Quality improvements for CS (QICS) programmes (QICS) based on this approach, have been implemented in Canada and Spain. OBJECTIVES Their objectives are as follows: 1) Toto identify clusters in each setting with similar results in terms of cost-consequences, 2) Toto investigate whether demographic, clinical or context characteristics can distinguish these clusters, and 3) Toto explore the implementation of QICS in the 2 regions, in order to identify factors that have been facilitators in changing practices and reducing the use of obstetric intervention, as well as the challenges faced by hospitals in implementing the recommendations. METHODS Descriptive study with a quantitative and qualitative approach. 1) Cluster analysis at patient level with data from 16 hospitals in Quebec (Canada) (n = 105,348) and 15 hospitals in Andalusia (Spain) (n = 64,760). The outcome measures are CS and costs. For the cost, we will consider the intervention, delivery and complications in mother and baby, from the hospital perspective. Cluster analysis will be used to identify participants with similar patterns of CS and costs based, and t tests will be used to evaluate if the clusters differed in terms of characteristics: Hospital level (academic status of hospital, level of care, supply and demand factors), patient level (mother age, parity, gestational age, previous CS, previous pathology, presentation of the baby, baby birth weight). 2) Analysis of in-depth interviews with obstetricians and midwives in hospitals where the QICS were implemented, to explore the differences in delivery-related practices, and the importance of the different constructs for positive or negative adherence to CPGs. Dimensions: political/management level, hospital level, health professionals, mothers and their birth partner. DISCUSSION This work sets out a new approach for programme evaluation, using different techniques to make it possible to take into account the specific context where the programmes were implemented.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Rank estimation of trajectory matrix in motion segmentation

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

Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

Estimation de la fonction rénale par l'equation MDRD: intérêt et limites pour l'adaptation des doses de médicaments [Renal function estimation by MDRD equation: interest and limitations for drug dosing].

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.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

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.

Adaptively weighted maximum likelihood estimation of discrete distributions

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.

Detailed 3D seismic imaging of a fault zone beneath Lake Geneva, Switzerland

An efficient high-resolution (HR) three-dimensional (3D) seismic reflection system for small-scale targets in lacustrine settings was developed. In Lake Geneva, near the city of Lausanne, Switzerland, the offshore extension of a complex fault zone well mapped on land was chosen for testing our system. A preliminary two-dimensional seismic survey indicated structures that include a thin (<40 m) layer of subhorizontal Quaternary sediments that unconformably overlie south-east-dipping Tertiary Molasse beds and a major fault zone (Paudeze Fault Zone) that separates Plateau and Subalpine Molasse (SM) units. A 3D survey was conducted over this test site using a newly developed three-streamer system. It provided high-quality data with a penetration to depths of 300 m below the water bottom of non-aliased signal for dips up to 30degrees and with a maximum vertical resolution of 1.1 m. The data were subjected to a conventional 3D processing sequence that included post-stack time migration. Tests with 3D pre-stack depth migration showed that such techniques can be applied to HR seismic surveys. Delineation of several horizons and fault surfaces reveals the potential for small-scale geologic and tectonic interpretation in three dimensions. Five major seismic facies and their detailed 3D geometries can be distinguished. Three fault surfaces and the top of a molasse surface were mapped in 3D. Analysis of the geometry of these surfaces and their relative orientation suggests that pre-existing structures within the Plateau Molasse (PM) unit influenced later faulting between the Plateau and SM. In particular, a change in strike of the PM bed dip may indicate a fold formed by a regional stress regime, the orientation of which was different from the one responsible for the creation of the Paudeze Fault Zone. This structure might have later influenced the local stress regime and caused the curved shape of the Paudeze Fault in our surveyed area.

4/1/1920, stade Bergeyre, équipe Section Paloise : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57492

Pédiatrie 1. Formule Quadratique: une nouveauté pédiatrique et pratique pour estimer le taux de filtration glomérulaire [Quadratic formula: a new pediatric advance for glomerular filtration rate estimation].

A new formula for glomerular filtration rate estimation in pediatric population from 2 to 18 years has been developed by the University Unit of Pediatric Nephrology. This Quadratic formula, accessible online, allows pediatricians to adjust drug dosage and/or follow-up renal function more precisely and in an easy manner.