Les méthodes d'ajustement dans les modèles d'évaluation de la mortalité hospitalière. Partie 1, Etude descriptive : document de travail

Suite à la demande du Président de la République de disposer d'indicateurs de mortalité en établissements de santé » (discours du 18 septembre 2008 sur le thème de la politique de la santé et de la réforme du système de soins), la Direction de la recherche, des études, de l'évaluation et des statistiques (DREES) a piloté en 2009, en lien avec la Direction générale de l'offre de soins (DGOS) et la Haute autorité de santé (HAS), l'instruction des aspects méthodologiques relatifs à la construction de ces indicateurs de mortalité. Cette revue de littérature portant sur les différentes méthodes d'ajustement a été réalisée dans ce cadre, à la demande conjointe de la DREES et de la HAS.Ce rapport décrit les méthodes et modèles d'estimation et d'ajustement de la mortalité hospitalière identifiées dans la littérature.Il ressort de cette revue, que d'une manière générale, trois questions méthodologiques majeures préoccupent les épidémiologistes, les chercheurs et les décideurs s'intéressant à l'indicateur de la mortalité hospitalière : i) premièrement, sur l'opportunité d'établir l'indicateur de mortalité hospitalière à partir de groupes de population de patients homogènes définis par des pathologies et/ou des procédures médicales/chirurgicales cibles ; ii) deuxièmement, sur le type d'approche analytique et de l'intérêt de prendre en compte plusieurs niveaux dans l'analyse statistique ; iii) enfin troisièmement, sur le choix des variables d'ajustement permettant de contrôler les différences de case-mix entre plusieurs établissements ou groupes de patients pour réaliser des comparaisons. [Ed.]

Scale decisions can reverse conclusions on community assembly processes.

AIM: Phylogenetic diversity patterns are increasingly being used to better understand the role of ecological and evolutionary processes in community assembly. Here, we quantify how these patterns are influenced by scale choices in terms of spatial and environmental extent and organismic scales. LOCATION: European Alps. METHODS: We applied 42 sampling strategies differing in their combination of focal scales. For each resulting sub-dataset, we estimated the phylogenetic diversity of the species pools, phylogenetic α-diversities of local communities, and statistics commonly used together with null models in order to infer non-random diversity patterns (i.e. phylogenetic clustering versus over-dispersion). Finally, we studied the effects of scale choices on these measures using regression analyses. RESULTS: Scale choices were decisive for revealing signals in diversity patterns. Notably, changes in focal scales sometimes reversed a pattern of over-dispersion into clustering. Organismic scale had a stronger effect than spatial and environmental extent. However, we did not find general rules for the direction of change from over-dispersion to clustering with changing scales. Importantly, these scale issues had only a weak influence when focusing on regional diversity patterns that change along abiotic gradients. MAIN CONCLUSIONS: Our results call for caution when combining phylogenetic data with distributional data to study how and why communities differ from random expectations of phylogenetic relatedness. These analyses seem to be robust when the focus is on relating community diversity patterns to variation in habitat conditions, such as abiotic gradients. However, if the focus is on identifying relevant assembly rules for local communities, the uncertainty arising from a certain scale choice can be immense. In the latter case, it becomes necessary to test whether emerging patterns are robust to alternative scale choices.

Una nova estimació retrospectiva del VAB regional industrial. Espanya, 1860-1930

[cat] En aquest treball, es realitza una nova estimació del VAB industrial espanyol a un nivell de desagregació territorial corresponent a les províncies (NUTSIII) i les Comunitats Autònomes (NUTS II). Per assolir aquest objectiu es planteja una nova metodologia d’estimació de les xifres històriques de VAB industrial regional. Front a les aproximacions tradicionals, basades en la utilització de fonts fiscals com a forma d’aproximar la capacitat productiva industrial, en aquest treball s’ofereix una estimació que també es basa en les rendes generades per la producció industrial de les regions. Amb aquest objectiu, es fa servir la metodologia proposada per Geary i Stark (2002) i les millores proposades per Crafts (2005). La utilització d’aquesta metodologia permet elaborar una nova estimació retrospectiva del VAB industrial de les regions espanyoles a diversos talls temporals corresponents al període 1860-1930.

Bio-electrical impedance analysis for estimation of fat-free mass and muscle mass in cystic fibrosis patients.

The nutritional status of cystic fibrosis (CF) patients has to be regularly evaluated and alimentary support instituted when indicated. Bio-electrical impedance analysis (BIA) is a recent method for determining body composition. The present study evaluates its use in CF patients without any clinical sign of malnutrition. Thirty-nine patients with CF and 39 healthy subjects aged 6-24 years were studied. Body density and mid-arm muscle circumference were determined by anthropometry and skinfold measurements. Fat-free mass was calculated taking into account the body density. Muscle mass was obtained from the urinary creatinine excretion rate. The resistance index was calculated by dividing the square of the subject's height by the body impedance. We show that fat-free mass, mid-arm muscle circumference and muscle mass are each linearly correlated to the resistance index and that the regression equations are similar for both CF patients and healthy subjects.

Linear least squares estimation of the first order moving average parameter

We propose an iterative procedure to minimize the sum of squares function which avoids the nonlinear nature of estimating the first order moving average parameter and provides a closed form of the estimator. The asymptotic properties of the method are discussed and the consistency of the linear least squares estimator is proved for the invertible case. We perform various Monte Carlo experiments in order to compare the sample properties of the linear least squares estimator with its nonlinear counterpart for the conditional and unconditional cases. Some examples are also discussed

Analysis of an iterative deconvolution approach for estimating the source wavelet during waveform inversion of crosshole ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.

Osteoporotic fracture risk in elderly women: estimation with quantitative heel US and clinical risk factors

PURPOSE: To derive a prediction rule by using prospectively obtained clinical and bone ultrasonographic (US) data to identify elderly women at risk for osteoporotic fractures. MATERIALS AND METHODS: The study was approved by the Swiss Ethics Committee. A prediction rule was computed by using data from a 3-year prospective multicenter study to assess the predictive value of heel-bone quantitative US in 6174 Swiss women aged 70-85 years. A quantitative US device to calculate the stiffness index at the heel was used. Baseline characteristics, known risk factors for osteoporosis and fall, and the quantitative US stiffness index were used to elaborate a predictive rule for osteoporotic fracture. Predictive values were determined by using a univariate Cox model and were adjusted with multivariate analysis. RESULTS: There were five risk factors for the incidence of osteoporotic fracture: older age (>75 years) (P < .001), low heel quantitative US stiffness index (<78%) (P < .001), history of fracture (P = .001), recent fall (P = .001), and a failed chair test (P = .029). The score points assigned to these risk factors were as follows: age, 2 (3 if age > 80 years); low quantitative US stiffness index, 5 (7.5 if stiffness index < 60%); history of fracture, 1; recent fall, 1.5; and failed chair test, 1. The cutoff value to obtain a high sensitivity (90%) was 4.5. With this cutoff, 1464 women were at lower risk (score, <4.5) and 4710 were at higher risk (score, >or=4.5) for fracture. Among the higher-risk women, 6.1% had an osteoporotic fracture, versus 1.8% of women at lower risk. Among the women who had a hip fracture, 90% were in the higher-risk group. CONCLUSION: A prediction rule obtained by using quantitative US stiffness index and four clinical risk factors helped discriminate, with high sensitivity, women at higher versus those at lower risk for osteoporotic fracture.

Validation of a wrist monitor for accurate estimation of RR intervals during sleep.

While the incidence of sleep disorders is continuously increasing in western societies, there is a clear demand for technologies to asses sleep-related parameters in ambulatory scenarios. The present study introduces a novel concept of accurate sensor to measure RR intervals via the analysis of photo-plethysmographic signals recorded at the wrist. In a cohort of 26 subjects undergoing full night polysomnography, the wrist device provided RR interval estimates in agreement with RR intervals as measured from standard electrocardiographic time series. The study showed an overall agreement between both approaches of 0.05 ± 18 ms. The novel wrist sensor opens the door towards a new generation of comfortable and easy-to-use sleep monitors.

Whole-rat protein content estimation: applicability of the Nx6.25 factor

The amino acid composition of the protein from three strains of rat (Wistar, Zucker lean and Zucker obese), subjected to reference and high-fat diets has been used to determine the mean empirical formula, molecular weight and N content of whole-rat protein. The combined whole protein of the rat was uniform for the six experimental groups, containing an estimate of 17.3% N and a mean aminoacyl residue molecular weight of 103.7. This suggests that the appropriate protein factor for the calculation of rat protein from its N content should be 5.77 instead of the classical 6.25. In addition, an estimate of the size of the non-protein N mass in the whole rat gave a figure in the range of 5.5 % of all N. The combination of the two calculations gives a protein factor of 5.5 for the conversion of total N into rat protein.

Dynamics of sweeping through an instability: Passage-time statistics for colored noise

A calculation of passage-time statistics is reported for the laser switch-on problem, under the influence of colored noise, when the net gain is continuously swept from below to above threshold. Cases of fast and slow sweeping are considered. In the weak-noise limit, asymptotic results are given for small and large correlation times of the noise. The mean first passage time increases with the correlation time of the noise. This effect is more important for fast sweeping than for slow sweeping.

Proof of concept for microarray-based detection of DNA-binding oncogenes in cell extracts.

The function of DNA-binding proteins is controlled not just by their abundance, but mainly at the level of their activity in terms of their interactions with DNA and protein targets. Moreover, the affinity of such transcription factors to their target sequences is often controlled by co-factors and/or modifications that are not easily assessed from biological samples. Here, we describe a scalable method for monitoring protein-DNA interactions on a microarray surface. This approach was designed to determine the DNA-binding activity of proteins in crude cell extracts, complementing conventional expression profiling arrays. Enzymatic labeling of DNA enables direct normalization of the protein binding to the microarray, allowing the estimation of relative binding affinities. Using DNA sequences covering a range of affinities, we show that the new microarray-based method yields binding strength estimates similar to low-throughput gel mobility-shift assays. The microarray is also of high sensitivity, as it allows the detection of a rare DNA-binding protein from breast cancer cells, the human tumor suppressor AP-2. This approach thus mediates precise and robust assessment of the activity of DNA-binding proteins and takes present DNA-binding assays to a high throughput level.