Physiological functions should be considered as true end points of nutritional intervention studies

With the beginning of this millennium it has become fashionable to only follow ‘evidence-based' practices. This generally-accepted approach cruelly negates experience or intelligent interpretation of pathophysiology. Another problem is that the great ‘meta-analysts' of the present era only accept end points that they consider ‘hard'. In the metabolic and nutritional field these end points are infection-related morbidity and mortality, and all other end points are considered ‘surrogate'. The aim of this presentation is to prove that this claim greatly negates the contribution of more-fundamentally-oriented research, the fact that mortality has multifactorial causes, and that infection is a crude measure of immune function. The following problems should be considered: many populations undergoing intervention have low mortality, requiring studies with thousands of patients to demonstrate effects of intervention on mortality; nutrition is only in rare cases primary treatment, and in many populations is a prerequisite for survival rather than a therapeutic modality; once the effect of nutritional support is achieved, the extra benefit of modulation of the nutritional support regimen can only be modest; cost-benefit is not a valid end point, because the better it is done the more it will cost; morbidity and mortality are crude end points for the effect of nutritional intervention, and are influenced by many factors. In fact, it is a yes or no factor. In the literature the most important contributions include new insights into the pathogenesis of disease, the diminution of disease-related adverse events and/or functional improvement after therapy. In nutrition research the negligence of these end points has precluded the development and validation of functional end points, such as muscle, immune and cognitive functions. Disability, quality of life, morbidity and mortality are directly related to these functional variables. It is, therefore, of paramount importance to validate functional end points and to consider them as primary rather than surrogate end point

Is there an isolated arrhythmogenic right atrial myocarditis?

Two cases with drug refractory ectopic atrial tachycardia are described. A map-guided partial resection of the right atrium (RA) was done after preoperative endocardial catheter mapping hadshown well-defined areas of fractionated RA potentials. Intraoperatively, there were no aneurysmal formations present as described by other authors. Histopathologic examination of the resected tissue showed atrial myocarditis in both patients. Postoperative right ventricular myocardial biopsies revealed no inflammatory tissue. A minor elevation of antibodies against echoviruses was found in one case. Postoperative electrophysiologic studies were negative. We conclude: focal RA myocarditis without concomitant ventricular myocarditis may represent one cause of drug-resistant ectopic atrial tachycardia. Map-guided surgical intervention may cure the diseas

Mosquito nets for the elderly?

Nine-year follow-up (ending 1999) of survival of 3738 individuals in a malaria-endemic area of Papua New Guinea found that the use of mosquito nets was associated with a large reduction in mortality in people aged ⩾40 years as well as in children aged <5 years. There may be substantial benefits of malaria transmission reduction for older people, that have been overlooked in public health programmes and burden of disease calculation

Low fat-free mass as a marker of mortality in community-dwelling healthy elderly subjects†

Background: low fat-free mass has been related to high mortality in patients. This study evaluated the relationship between body composition of healthy elderly subjects and mortality. Methods: in 1999, 203 older subjects underwent measurements of body composition by bioelectrical impedance analysis, Charlson co-morbidity index and estimation of energy expenditure through physical activity by a validated questionnaire. These measurements were repeated in 2002, 2005 and 2008 in all consenting subjects. Mortality data between 1999 and 2010 were retrieved from the local death registers. The relationship between mortality and the last indexes of fat and fat-free masses was analysed by multiple Cox regression models. Results: women's and men's data at last follow-up were: age 81.1±5.9 and 80.9±5.8 years, body mass index 25.3±4.6 and 26.1±3.4kg/m2, fat-free mass index 16.4±1.8 and 19.3±1.9kg/m2 and fat mass index 9.0±3.2 and 6.8±2.0kg/m2. Fifty-eight subjects died between 1999 and 2010. The fat-free mass index (hazard ratio 0.77; 95% confidence interval 0.63-0.95) but not the fat mass index, predicted mortality in addition to sex and Charlson index. The multiple Cox regression model explained 31% of the variance of mortality. Conclusion: a low fat-free mass index is an independent risk factor of mortality in elderly subjects, healthy at the time of body composition measuremen

Predictive value of clinical and laboratory features for the main febrile diseases in children living in Tanzania: A prospective observational study.

To construct evidence-based guidelines for management of febrile illness, it is essential to identify clinical predictors for the main causes of fever, either to diagnose the disease when no laboratory test is available or to better target testing when a test is available. The objective was to investigate clinical predictors of several diseases in a cohort of febrile children attending outpatient clinics in Tanzania, whose diagnoses have been established after extensive clinical and laboratory workup. From April to December 2008, 1005 consecutive children aged 2 months to 10 years with temperature ≥38°C attending two outpatient clinics in Dar es Salaam were included. Demographic characteristics, symptoms and signs, comorbidities, full blood count and liver enzyme level were investigated by bi- and multi-variate analyses (Chan, et al., 2008). To evaluate accuracy of combined predictors to construct algorithms, classification and regression tree (CART) analyses were also performed. 62 variables were studied. Between 4 and 15 significant predictors to rule in (aLR+&gt;1) or rule out (aLR+&lt;1) the disease were found in the multivariate analysis for the 7 more frequent outcomes. For malaria, the strongest predictor was temperature ≥40°C (aLR+8.4, 95%CI 4.7-15), for typhoid abdominal tenderness (5.9,2.5-11), for urinary tract infection (UTI) age ≥3 years (0.20,0-0.50), for radiological pneumonia abnormal chest auscultation (4.3,2.8-6.1), for acute HHV6 infection dehydration (0.18,0-0.75), for bacterial disease (any type) chest indrawing (19,8.2-60) and for viral disease (any type) jaundice (0.28,0.16-0.41). Other clinically relevant and easy to assess predictors were also found: malaria could be ruled in by recent travel, typhoid by jaundice, radiological pneumonia by very fast breathing and UTI by fever duration of ≥4 days. The CART model for malaria included temperature, travel, jaundice and hepatomegaly (sensitivity 80%, specificity 64%); typhoid: age ≥2 years, jaundice, abdominal tenderness and adenopathy (46%,93%); UTI: age &lt;2 years, temperature ≥40°C, low weight and pale nails (20%,96%); radiological pneumonia: very fast breathing, chest indrawing and leukocytosis (38%,97%); acute HHV6 infection: less than 2 years old, (no) dehydration, (no) jaundice and (no) rash (86%,51%); bacterial disease: chest indrawing, chronic condition, temperature ≥39.7°c and fever duration &gt;3 days (45%,83%); viral disease: runny nose, cough and age &lt;2 years (68%,76%). A better understanding of the relative performance of these predictors might be of great help for clinicians to be able to better decide when to test, treat, refer or simply observe a sick child, in order to decrease morbidity and mortality, but also to avoid unnecessary antimicrobial prescription. These predictors have been used to construct a new algorithm for the management of childhood illnesses called ALMANACH

Yet another breakdown point notion: EFSBP - illustrated at scale-shape models

The breakdown point in its different variants is one of the central notions to quantify the global robustness of a procedure. We propose a simple supplementary variant which is useful in situations where we have no obvious or only partial equivariance: Extending the Donoho and Huber(1983) Finite Sample Breakdown Point, we propose the Expected Finite Sample Breakdown Point to produce less configuration-dependent values while still preserving the finite sample aspect of the former definition. We apply this notion for joint estimation of scale and shape (with only scale-equivariance available), exemplified for generalized Pareto, generalized extreme value, Weibull, and Gamma distributions. In these settings, we are interested in highly-robust, easy-to-compute initial estimators; to this end we study Pickands-type and Location-Dispersion-type estimators and compute their respective breakdown points.Comment: 21 pages, 4 figure

Communication du risque en médecine des voyages [Risk communication in travel medicine].

Les recommandations en termes de prévention contre la malaria pour les pays à risques modéré à faible diffèrent entre les pays, malgré le fait que les personnes soient exposées à un risque identique dans les pays qu'ils visitent. Pour inclure les voyageurs dans la réflexion, des outils de partage de la décision ont été développés et testés dans cette population. Leur utilisation a montré que la majorité des personnes choisissent de ne pas prendre de chimioprophylaxie en avançant des raisons valides. Le développement d'aides décisionnelles répondant à des critères reconnus est prévu et permettra d'améliorer la pertinence des recommandations. Les aides décisionnelles permettront aussi aux voyageurs de faire un choix de prévention avec les soignants au plus près de leurs valeurs et préférences, tout en respectant les règles de l'éthique médicale. Recommendations for malaria prevention for travelers planning a trip in medium to low risk countries differ between countries, despite the fact that people are exposed to the same risk in the travelled country. Decision aids have been developed and tested in a population of travelers planning a trip in such countries n order to present travelers the various prevention options and involve them in the decision. The use of the decision aid showed that he majority of people choose not to take chemoprophylaxis and that they could motivate their choice with valid reasons. The development of decision aids based on recognized quality criteria is foreseen; these will allow to improving the relevance of the recommendations and enable travelers to choose a prevention option that will be the closest to their values and preferences while following to the principles of medical ethics

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these