La dysménorrhée: un problème pour le pédiatre [Dysmenorrhea: a problem for the pediatrician?].

Dysmenorrhea is common in adolescent years, especially after the onset of ovulatory cycles, usually 2 to 3 years after menarche. Pain and symptoms are responsible for school absenteeism and interruption of sports and social activities. OBJECTIVES: This study aims to measure the prevalence of severe dysmenorrhea and its consequences on adolescent girls in Switzerland. Treatment of dysmenorrhea is discussed and recommendations for clinical practice are given. STUDY DESIGN: Cross sectional survey (SMASH 02) on a nationally representative sample of adolescents (n=7548; 3340 females), aged 16 to 20 years who attended post-mandatory education. A self-administered questionnaire was used to assess the severity of dysmenorrhea and its consequences on daily life pursuit of medical help and medications used. RESULTS: Among 3340 girls, 86.6% suffered from dysmenorrhea-related symptoms: 12.4% described having severe dysmenorrhea and 74.2% moderate dysmenorrhea. Girls with severe dysmenorrhea described heavier consequences on daily activities compared with girls without dysmenorrhea: 47.8% of girls with severe dysmenorrhea reported staying at home and 66.5% declared reducing their sportive activities. Yet, fewer than half have consulted a physician for this complaint and even fewer were treated properly. RECOMMENDATION: The pediatrician has a pivotal role in screening young patients for dysmenorrhea, as well as, educating and effectively treating adolescent girls with menstruation-associated symptoms. Non-steroidal anti-inflammatory drugs are considered the first-line of treatment for dysmenorrhea, and adolescents with symptoms that do not respond to this treatment for 3 menstrual periods should be offered combined oestroprogestative contraception and must be followed up, as non-responders may have an underlying organic pathology. CONCLUSION: Dysmenorrhea is a frequent health problem in adolescent years and adolescent care providers should be able to care for these patients in an efficient way.

Hindsight judgement on ambiguous episodes of suspected infection in critically ill children: poor consensus amongst experts?

Few episodes of suspected infection observed in paediatric intensive care are classifiable without ambiguity by a priori defined criteria. Most require additional expert judgement. Recently, we observed a high variability in antibiotic prescription rates, not explained by the patients' clinical data or underlying diseases. We hypothesised that the disagreement of experts in adjudication of episodes of suspected infection could be one of the potential causes for this variability. During a 5-month period, we included all patients of a 19-bed multidisciplinary, tertiary, neonatal and paediatric intensive care unit, in whom infection was clinically suspected and antibiotics were prescribed ( n=183). Three experts (two senior ICU physicians and a specialist in infectious diseases) were provided with all patient data, laboratory and microbiological findings. All experts classified episodes according to a priori defined criteria into: proven sepsis, probable sepsis (negative cultures), localised infection and no infection. Episodes of proven viral infection and incomplete data sets were excluded. Of the remaining 167 episodes, 48 were classifiable by a priori criteria ( n=28 proven sepsis, n= 20 no infection). The three experts only achieved limited agreement beyond chance in the remaining 119 episodes (kappa = 0.32, and kappa = 0.19 amongst the ICU physicians). The kappa is a measure of the degree of agreement beyond what would be expected by chance alone, with 0 indicating the chance result and 1 indicating perfect agreement. CONCLUSION: agreement of specialists in hindsight adjudication of episodes of suspected infection is of questionable reliability.

Heritage Sporting Event : An Old Recipe for a New Problem

In the last decades, the globalized competition among cities and regions made them develop new strategies for branding and promoting their territory to attract tourists, investors, companies and residents. Major sports events - such as the Olympic Games, the FIFA World Cup or World and Continental Championships - have played an integral part in these strategies. Believing, with or without evidence, in the capacity of those events to improve the visibility and the economy of the host destination, many cities, regions and even countries have engaged in establishing sports events hosting strategies. The problem of the globalized competition in the sports events "market" is that many cities and regions do not have the resources - either financial, human or in terms of infrastructure - to compete in hosting major sports events. Consequently, many cities or regions have to turn to second-tier sports events. To organise those smaller events means less media coverage and more difficulty in finding sponsors, while the costs - both financial and in terms of services - stay high for the community. This paper analyses how Heritage Sporting Events (HSE) might be an opportunity for cities and regions engaged in sports events hosting strategies. HSE is an emerging concept that to date has been under-researched in the academic literature. Therefore, this paper aims to define the concept of HSE through an exploratory research study. A multidisciplinary literature review reveals two major characteristics of HSEs: the sustainability in the territory and the authenticity of the event constructed through a differentiation process. These characteristics, defined through multiple variables, give us the opportunity to observe the construction process of a sports event into a heritage object. This paper argues that HSEs can be seen as territorial resources that can represent a competitive advantage for host destinations. In conclusion, academics are invited to further research HSEs to better understand their construction process and their impacts on the territory, while local authorities are invited to consider HSEs for the branding and the promotion of their territory.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Modeling the forensic two-trace problem with Bayesian networks

The forensic two-trace problem is a perplexing inference problem introduced by Evett (J Forensic Sci Soc 27:375-381, 1987). Different possible ways of wording the competing pair of propositions (i.e., one proposition advanced by the prosecution and one proposition advanced by the defence) led to different quantifications of the value of the evidence (Meester and Sjerps in Biometrics 59:727-732, 2003). Here, we re-examine this scenario with the aim of clarifying the interrelationships that exist between the different solutions, and in this way, produce a global vision of the problem. We propose to investigate the different expressions for evaluating the value of the evidence by using a graphical approach, i.e. Bayesian networks, to model the rationale behind each of the proposed solutions and the assumptions made on the unknown parameters in this problem.

Invasive candidiasis as a cause of sepsis in the critically ill patient.

Invasive fungal infections are an increasingly frequent etiology of sepsis in critically ill patients causing substantial morbidity and mortality. Candida species are by far the predominant agent of fungal sepsis accounting for 10% to 15% of health-care associated infections, about 5% of all cases of severe sepsis and septic shock and are the fourth most common bloodstream isolates in the United States. One-third of all episodes of candidemia occur in the intensive care setting. Early diagnosis of invasive candidiasis is critical in order to initiate antifungal agents promptly. Delay in the administration of appropriate therapy increases mortality. Unfortunately, risk factors, clinical and radiological manifestations are quite unspecific and conventional culture methods are suboptimal. Non-culture based methods (such as mannan, anti-mannan, β-d-glucan, and polymerase chain reaction) have emerged but remain investigational or require additional testing in the ICU setting. Few prophylactic or pre-emptive studies have been performed in critically ill patients. They tended to be underpowered and their clinical usefulness remains to be established under most circumstances. The antifungal armamentarium has expanded considerably with the advent of lipid formulations of amphotericin B, the newest triazoles and the echinocandins. Clinical trials have shown that the triazoles and echinocandins are efficacious and well tolerated antifungal therapies. Clinical practice guidelines for the management of invasive candidiasis have been published by the European Society for Clinical Microbiology and Infectious Diseases and the Infectious Diseases Society of North America.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.