Development and validation of a clinical decision rule for the diagnosis of influenza.

INTRODUCTION: A clinical decision rule to improve the accuracy of a diagnosis of influenza could help clinicians avoid unnecessary use of diagnostic tests and treatments. Our objective was to develop and validate a simple clinical decision rule for diagnosis of influenza. METHODS: We combined data from 2 studies of influenza diagnosis in adult outpatients with suspected influenza: one set in California and one in Switzerland. Patients in both studies underwent a structured history and physical examination and had a reference standard test for influenza (polymerase chain reaction or culture). We randomly divided the dataset into derivation and validation groups and then evaluated simple heuristics and decision rules from previous studies and 3 rules based on our own multivariate analysis. Cutpoints for stratification of risk groups in each model were determined using the derivation group before evaluating them in the validation group. For each decision rule, the positive predictive value and likelihood ratio for influenza in low-, moderate-, and high-risk groups, and the percentage of patients allocated to each risk group, were reported. RESULTS: The simple heuristics (fever and cough; fever, cough, and acute onset) were helpful when positive but not when negative. The most useful and accurate clinical rule assigned 2 points for fever plus cough, 2 points for myalgias, and 1 point each for duration <48 hours and chills or sweats. The risk of influenza was 8% for 0 to 2 points, 30% for 3 points, and 59% for 4 to 6 points; the rule performed similarly in derivation and validation groups. Approximately two-thirds of patients fell into the low- or high-risk group and would not require further diagnostic testing. CONCLUSION: A simple, valid clinical rule can be used to guide point-of-care testing and empiric therapy for patients with suspected influenza.

On ignoring scientific evidence: The bumpy road to enlightenment

It is well accepted that people resist evidence that contradicts their beliefs.Moreover, despite their training, many scientists reject results that are inconsistent withtheir theories. This phenomenon is discussed in relation to the field of judgment anddecision making by describing four case studies. These concern findings that clinical judgment is less predictive than actuarial models; simple methods have proven superiorto more theoretically correct methods in times series forecasting; equal weighting ofvariables is often more accurate than using differential weights; and decisions cansometimes be improved by discarding relevant information. All findings relate to theapparently difficult-to-accept idea that simple models can predict complex phenomenabetter than complex ones. It is true that there is a scientific market place for ideas.However, like its economic counterpart, it is subject to inefficiencies (e.g., thinness,asymmetric information, and speculative bubbles). Unfortunately, the market is only correct in the long-run. The road to enlightenment is bumpy.

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

Estandarización de la captura por unidad de esfuerzo (CPUE) de la flota industrial de cerco del stock norte-centro de la anchoveta peruana (Engraulis ringens Jenyns)

Se trabajó utilizando una metodología basada en Modelos Lineales Generalizados (MLG). La CPUE fue expresada en toneladas por duración de viaje. Las variables explicativas utilizadas fueron el año, mes, capacidad de bodega, latitud, inercia espacial y distancia a la costa. El modelo tuvo un coeficiente de determinación de 0,485, explicando casi la mitad de la variabilidad de la CPUE observada. La variable con mayor influencia en el modelo fue la capacidad de bodega (49% de la varianza explicada), debido posiblemente a que la flota anchovetera posee una capacidad elevada de captura y que los recursos pelágicos tienden a hiper-agregarse, incluso cuando están siendo fuertemente explotados. La correlación entre la CPUE estandarizada y biomasa estimada por un modelo de captura a la edad (r=0,74) indica que el método basado en MLG es recomendable para la estandarización de la CPUE. Se propone a esta CPUE como una alternativa para monitorear la biomasa de la anchoveta.

Behavioral assumptions and management ability

The paper explores the consequences that relying on different behavioral assumptions intraining managers may have on their future performance. We argue that training with anemphasis on the standard assumptions used in economics (rationality and self-interest) is goodfor technical posts but may also lead future managers to rely excessively on rational and explicitsafeguarding, crowding out instinctive relational heuristics and signaling a bad human type topotential partners. In contrast, human assumptions used in management theories, because oftheir diverse, implicit and even contradictory nature, do not conflict with the innate set ofcooperative tools and may provide a good training ground for such tools. We present tentativeconfirmatory evidence by examining how the weight given to behavioral assumptions in the corecourses of the top 100 business schools influences the average salaries of their MBA graduates.Controlling for the self-selected average quality of their students and some other schools characteristics, average salaries are seen to be significantly greater for schools whose core MBAcourses contain a higher proportion of management courses as opposed to courses based oneconomics or technical disciplines.

On heuristic and linear models of judgment: Mapping the demand for knowledge

Research on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from as if linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of lens model research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human andheuristic performance in the same tasks. Our results highlight the trade-off betweenlinear models and heuristics. Whereas the former are cognitively demanding, the latterare simple to use. However, they require knowledge and thus maps of when andwhich heuristic to employ.

A simple optimised search heuristic for the job-shop scheduling problem

This paper presents a simple Optimised Search Heuristic for the Job Shop Scheduling problem that combines a GRASP heuristic with a branch-and-bound algorithm. The proposed method is compared with similar approaches and leads to better results in terms of solution quality and computing times.

Metaheuristics for the bus-driver scheduling problem

We present new metaheuristics for solving real crew scheduling problemsin a public transportation bus company. Since the crews of thesecompanies are drivers, we will designate the problem by the bus-driverscheduling problem. Crew scheduling problems are well known and severalmathematical programming based techniques have been proposed to solvethem, in particular using the set-covering formulation. However, inpractice, there exists the need for improvement in terms of computationalefficiency and capacity of solving large-scale instances. Moreover, thereal bus-driver scheduling problems that we consider can present variantaspects of the set covering, as for example a different objectivefunction, implying that alternative solutions methods have to bedeveloped. We propose metaheuristics based on the following approaches:GRASP (greedy randomized adaptive search procedure), tabu search andgenetic algorithms. These metaheuristics also present some innovationfeatures based on and genetic algorithms. These metaheuristics alsopresent some innovation features based on the structure of the crewscheduling problem, that guide the search efficiently and able them tofind good solutions. Some of these new features can also be applied inthe development of heuristics to other combinatorial optimizationproblems. A summary of computational results with real-data problems ispresented.

Parametric imaging for characterizing focal liver lesions in contrast-enhanced ultrasound.

The differentiation between benign and malignant focal liver lesions plays an important role in diagnosis of liver disease and therapeutic planning of local or general disease. This differentiation, based on characterization, relies on the observation of the dynamic vascular patterns (DVP) of lesions with respect to adjacent parenchyma, and may be assessed during contrast-enhanced ultrasound imaging after a bolus injection. For instance, hemangiomas (i.e., benign lesions) exhibit hyper-enhanced signatures over time, whereas metastases (i.e., malignant lesions) frequently present hyperenhanced foci during the arterial phase and always become hypo-enhanced afterwards. The objective of this work was to develop a new parametric imaging technique, aimed at mapping the DVP signatures into a single image called a DVP parametric image, conceived as a diagnostic aid tool for characterizing lesion types. The methodology consisted in processing a time sequence of images (DICOM video data) using four consecutive steps: (1) pre-processing combining image motion correction and linearization to derive an echo-power signal, in each pixel, proportional to local contrast agent concentration over time; (2) signal modeling, by means of a curve-fitting optimization, to compute a difference signal in each pixel, as the subtraction of adjacent parenchyma kinetic from the echopower signal; (3) classification of difference signals; and (4) parametric image rendering to represent classified pixels as a support for diagnosis. DVP parametric imaging was the object of a clinical assessment on a total of 146 lesions, imaged using different medical ultrasound systems. The resulting sensitivity and specificity were 97% and 91%, respectively, which compare favorably with scores of 81 to 95% and 80 to 95% reported in medical literature for sensitivity and specificity, respectively.

Lung microbiota promotes tolerance to allergens in neonates via PD-L1.

Epidemiological data point toward a critical period in early life during which environmental cues can set an individual on a trajectory toward respiratory health or disease. The neonatal immune system matures during this period, although little is known about the signals that lead to its maturation. Here we report that the formation of the lung microbiota is a key parameter in this process. Immediately following birth, neonatal mice were prone to develop exaggerated airway eosinophilia, release type 2 helper T cell cytokines and exhibit airway hyper-responsiveness following exposure to house dust mite allergens, even though their lungs harbored high numbers of natural CD4(+)Foxp3(+)CD25(+)Helios(+) regulatory T (Treg) cells. During the first 2 weeks after birth, the bacterial load in the lungs increased, and representation of the bacterial phyla shifts from a predominance of Gammaproteobacteria and Firmicutes towards Bacteroidetes. The changes in the microbiota were associated with decreased aeroallergen responsiveness and the emergence of a Helios(-) Treg cell subset that required interaction with programmed death ligand 1 (PD-L1) for development. Absence of microbial colonization(10) or blockade of PD-L1 during the first 2 weeks postpartum maintained exaggerated responsiveness to allergens through to adulthood. Adoptive transfer of Treg cells from adult mice to neonates before aeroallergen exposure ameliorated disease. Thus, formation of the airway microbiota induces regulatory cells early in life, which, when dysregulated, can lead to sustained susceptibility to allergic airway inflammation in adulthood.

Active learning methods for remote sensing image classification

In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

PTH and 1.25 vitamin D response to a low-calcium diet is associated with bone mineral density in renal stone formers.

BACKGROUND: Renal calcium stones and hypercalciuria are associated with a reduced bone mineral density (BMD). Therefore, the effect of changes in calcium homeostasis is of interest for both stones and bones. We hypothesized that the response of calciuria, parathyroid hormone (PTH) and 1.25 vitamin D to changes in dietary calcium might be related to BMD. METHODS: A single-centre prospective interventional study of 94 hyper- and non-hypercalciuric calcium stone formers consecutively retrieved from our stone clinic. The patients were investigated on a free-choice diet, a low-calcium diet, while fasting and after an oral calcium load. Patient groups were defined according to lumbar BMD (z-score) obtained by dual X-ray absorptiometry (group 1: z-score <-0.5, n = 30; group 2: z-score -0.5-0.5, n = 36; group 3: z-score >0.5, n = 28). The effect of the dietary interventions on calciuria, 1.25 vitamin D and PTH in relation to BMD was measured. RESULTS: An inverse relationship between BMD and calciuria was observed on all four calcium intakes (P = 0.009). On a free-choice diet, 1.25 vitamin D and PTH levels were identical in the three patient groups. However, the relative responses of 1.25 vitamin D and PTH to the low-calcium diet were opposite in the three groups with the highest increase of 1.25 vitamin D in group 1 and the lowest in group 3, whereas PTH increase was most pronounced in group 3 and least in group 1. CONCLUSION: Calcium stone formers with a low lumbar BMD exhibit a blunted response of PTH release and an apparently overshooting production of 1.25 vitamin D following a low-calcium diet.

Dorsal fractures of the Triquetrum : MRI findings with an emphasis on dorsal carpal ligament injuries

Contexte et but de l'étude: Les fractures du triquetrum sont les deuxièmes fractures des os du carpe en fréquence, après celles du scaphoïde. Elles représentent environ 3.5% de toutes les lésions traumatiques du poignet, et résultent le plus souvent d'une chute de sa hauteur avec réception sur le poignet en hyper-extension. Leur mécanisme physiopathologique reste débattu. La première théorie fut celle de l'avulsion ligamentaire d'un fragment osseux dorsal. Puis, Levy et coll. ainsi que Garcia-Elias ont successivement suggéré que ces fractures résultaient plutôt d'une impaction ulno-carpienne. De nombreux ligaments (intrinsèques et extrinsèques du carpe) s'insèrent sur les versants palmaires et dorsaux du triquetrum. Ces ligaments jouent un rôle essentiel dans le maintien de la stabilité du carpe. Bien que l'arthro-IRM du poignet soit l'examen de référence pour évaluer ces ligaments, Shahabpour et coll. ont récemment démontré leur visibilité en IRM tridimensionnelle (volumique) après injection iv. de produit de contraste (Gadolinium). L'atteinte ligamentaire associée aux fractures dorsales du triquetrum n'a jusqu'à présent jamais été évalué. Ces lésions pourraient avoir un impact sur l'évolution et la prise en charge de ces fractures. Les objectifs de l'étude étaient donc les suivants: premièrement, déterminer l'ensemble des caractéristiques des fractures dorsales du triquetrum en IRM, en mettant l'accent sur les lésions ligamentaires extrinsèques associées; secondairement, discuter les différents mécanismes physiopathologiques (i.e. avulsion ligamentaire ou impaction ulno-carpienne) de ces fractures d'après nos résultats en IRM. Patients et méthodes: Ceci est une étude rétrospective multicentrique (CHUV, Lausanne; Hôpital Cochin, AP-HP, Paris) d'examens IRM et radiographies conventionnelles du poignet. A partir de janvier 2008, nous avons recherché dans les bases de données institutionnelles les patients présentant une fracture du triquetrum et ayant bénéficié d'une IRM volumique du poignet dans un délai de six semaines entre le traumatisme et l'IRM. Les examens IRM ont été effectués sur deux machines à haut champ magnétique (3 Tesla) avec une antenne dédiée et un protocole d'acquisition incluant une séquence tridimensionnelle isotropique (« 3D VIBE ») après injection iv. de produit de contraste (Gadolinium). Ces examens ont été analysés par deux radiologues ostéo-articulaires expérimentés. Les mesures ont été effectuées par un troisième radiologue ostéo-articulaire. En ce qui concerne l'analyse qualitative, le type de fracture du triquetrum (selon la classification de Garcia-Elias), la distribution de l'oedème osseux post- traumatique, ainsi que le nombre et la distribution des lésions ligamentaires extrinsèques associées ont été évalués. Pour l'analyse quantitative, l'index du processus de la styloïde ulnaire (selon la formule de Garcia-Elias), le volume du fragment osseux détaché du triquetrum, et la distance séparant ce fragment osseux du triquetrum ont été mesurés.

Leishmania RNA virus: when the host pays the toll.

The presence of an RNA virus in a South American subgenus of the Leishmania parasite, L. (Viannia), was detected several decades ago but its role in leishmanial virulence and metastasis was only recently described. In Leishmania guyanensis, the nucleic acid of Leishmania RNA virus (LRV1) acts as a potent innate immunogen, eliciting a hyper-inflammatory immune response through toll-like receptor 3 (TLR3). The resultant inflammatory cascade has been shown to increase disease severity, parasite persistence, and perhaps even resistance to anti-leishmanial drugs. Curiously, LRVs were found mostly in clinical isolates prone to infectious metastasis in both their human source and experimental animal model, suggesting an association between the viral hyperpathogen and metastatic complications such as mucocutaneous leishmaniasis (MCL). MCL presents as chronic secondary lesions in the mucosa of the mouth and nose, debilitatingly inflamed and notoriously refractory to treatment. Immunologically, this outcome has many of the same hallmarks associated with the reaction to LRV: production of type 1 interferons, bias toward a chronic Th1 inflammatory state and an impaired ability of host cells to eliminate parasites through oxidative stress. More intriguing, is that the risk of developing MCL is found almost exclusively in infections of the L. (Viannia) subtype, further indication that leishmanial metastasis is caused, at least in part, by a parasitic component. LRV present in this subgenus may contribute to the destructive inflammation of metastatic disease either by acting in concert with other intrinsic "metastatic factors" or by independently preying on host TLR3 hypersensitivity. Because LRV amplifies parasite virulence, its presence may provide a unique target for diagnostic and clinical intervention of metastatic leishmaniasis. Taking examples from other members of the Totiviridae virus family, this paper reviews the benefits and costs of endosymbiosis, specifically for the maintenance of LRV infection in Leishmania parasites, which is often at the expense of its human host.

Comparison of fundus autofluorescence between fundus camera (Topcon) and confocal scanning laser ophthalmoscope (HRA) in various pathologies

Purpose: To investigate the differences between Fundus Camera (Topcon TRC-50X) and Confocal Scanning Laser Ophthalmoscope (Heidelberg retina angiogram (HRA)) on the fundus autofluorescence (FAF) imaging (resolution and FAF characteristics). Methods: 105 eyes of 56 patients with various retinal diseases underwent FAF imaging with HRA (488nm exciter/500nm barrier filter) before fluorescein angiography (FFA) and Topcon Fundus Camera (580nm exciter/695nm barrier filter) before and after FFA. The quality of the FAF images was compared for their resolution and analysed for the influence of fixation stability and cataracts. Hypo-and hyper-FAF behaviour was analysed for the healthy disc, healthy fovea, and a variety of pathological features. Results: HRA images were found to be of superior resolution in 18, while Topcon images were estimated superior in 29 eyes. No difference was found in 58 eyes. Both poor fixation (p=0.009) and more advanced cataract (p=0.013) were found associated with better image quality by Topcon. Images acquired by Topcon before and after FFA were identical (100%). The healthy disc was usually dark on HRA (72%), but showed mild autofluorescence on Topcon (85%). The healthy fovea showed in 100% Hypo-FAF on HRA, while Topcon showed in 53% Iso-FAF, in 43% mild Hypo-FAF, and in 4% Hypo-FAF as on HRA. No difference of FAF was found for geographic atrophy, pigment changes, and drusen, although Topcon images were often more detailed. Hyper-FAF due to serous exudation showed better on HRA. Cystic edema was visible only on HRA in a petaloid hyper-FAF pattern in 83%, while only two eyes (17%) showed similar behavior in both HRA- and Topcon images. Hard exudates caused Hypo-FAF only on HRA, hardly visible on Topcon. Blockage phenomenon by blood however was identical. Conclusions: The filter set of Topcon and the single image acquisition appear to be an advantage for patients with cataract and poor fixation respectively. Preceding FFA does not alter the Topcon FAF image. Regarding the FAF behavior, there are differences between the 2 systems which need to be taken into account when interpreting the images.