[Arterial-ischaemic stroke in childhood]

The risk to have a stroke during childhood is at least as frequent as to suffer from a brain tumour. Unlike adults, in whom ischaemic strokes overweigh haemorrhagic strokes, ischaemic and haemorrhagic strokes are equally frequent in children, occurring with an incidence of 2 - 3/100'000 children/year. Even though the clinical presentation of arterial-ischaemic stroke in children (pedAIS) is similar to adults, time to diagnosis is longer. The delay to diagnosis is mainly explained by the low index of suspicion of both the general population and the medical personnel, a broad range of differential diagnoses, and the fact that diagnostic imaging in children often requires sedation, which is not always readily available. PedAIS is a multiple risk problem, usually occurring due to a combination of risk factors, such as infectious diseases, dehydration, trauma or an underlying condition such as congenital heart disease. Still little is known about the appropriate management of pedAIS. Supportive measures are considered to be the mainstay of therapy. The use of antithrombotic medication depends on pedAIS aetiology. In an ongoing multicenter trial, the safety and effectiveness of thrombolysis are currently being investigated. PedAIS carries an important mortality and morbidity, with neurological and neuropsychological deficits persisting in two thirds of the affected children.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.

Assessing the Potential of Multiple Imputation in Sequence Analysis

Sequence analysis and optimal matching are useful heuristic tools for the descriptive analysis of heterogeneous individual pathways such as educational careers, job sequences or patterns of family formation. However, to date it remains unclear how to handle the inevitable problems caused by missing values with regard to such analysis. Multiple Imputation (MI) offers a possible solution for this problem but it has not been tested in the context of sequence analysis. Against this background, we contribute to the literature by assessing the potential of MI in the context of sequence analyses using an empirical example. Methodologically, we draw upon the work of Brendan Halpin and extend it to additional types of missing value patterns. Our empirical case is a sequence analysis of panel data with substantial attrition that examines the typical patterns and the persistence of sex segregation in school-to-work transitions in Switzerland. The preliminary results indicate that MI is a valuable methodology for handling missing values due to panel mortality in the context of sequence analysis. MI is especially useful in facilitating a sound interpretation of the resulting sequence types.