Polysomnographic record and successful management of augmentation in restless legs syndrome/Willis-Ekbom disease

BACKGROUND: Dopamine agonists (DAs) represent the first-line treatment in restless legs syndrome (RLS); however, in the long term, a substantial proportion of patients will develop augmentation, which is a severe drug-related exacerbation of symptoms and the main reason for late DA withdrawal. Polysomnographic features and mechanisms underlining augmentation are unknown. No practice guidelines for management of augmentation are available. METHODS: A clinical case series of 24 consecutive outpatients affected by RLS with clinically significant augmentation during treatment with immediate-release DA was performed. All patients underwent a full-night polysomnographic recording during augmentation. A switchover from immediate-release DAs (l-dopa, pramipexole, ropinirole, rotigotine) to the long-acting, extended-release formula of pramipexole was performed. RESULTS: Fifty percent of patients presented more than 15 periodic limb movements per hour of sleep during augmentation, showing longer sleep latency and shorter total sleep time than subjects without periodic limb movements. In all patients, resolution of augmentation was observed within two to four weeks during which immediate-release dopamine agonists could be completely withdrawn. Treatment efficacy of extended-release pramipexole has persisted, thus far, over a mean follow-up interval of 13 months. CONCLUSIONS: Pramipexole extended release could be an easy, safe, and fast pharmacological option to treat augmentation in patients with restless legs syndrome. As such it warrants further prospective and controlled investigations. This observation supports the hypothesis that the duration of action of the drug plays a key role in the mechanism of augmentation.

On degeneracy and invariances of random fields paths with applications in Gaussian process modelling

We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy properties under well-chosen linear operators. We first show in a second order set-up that almost sure degeneracy of random field paths under some class of linear operators defined in terms of signed measures can be controlled through the two first moments. A special focus is then put on the Gaussian case, where these results are revisited and extended to further linear operators thanks to state-of-the-art representations. Several degeneracy properties are tackled, including random fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process modelling. In a first numerical experiment, it is shown that dedicated kernels can be used to infer an axis of symmetry. Our second numerical experiment deals with conditional simulations of a solution to the heat equation, and it is found that adapted kernels notably enable improved predictions of non-linear functionals of the field such as its maximum.