Pilot therapeutic education program in multiple system atrophy: Safety, quality of life and satisfaction from a national registry based longitudinal study.

BACKGROUND: Therapeutic education programs are effective in several chronic conditions. However, evidence is lacking in multiple system atrophy (MSA). We aimed to assess efficacy and safety of a comprehensive therapeutic education program in people with MSA (PwMSA) and their caregivers. METHODS: In this prospective longitudinal study we included 16 PwMSA and their main caregivers in 4 groups of 4 dyads each. The program consisted of eight 60-min interdisciplinary sessions: introduction, orthostatic hypotension, speech therapy, gait and respiratory physiotherapy, psychological support, urinary dysfunction, occupational therapy/social work. UMSARS, NMSS, PDQ39, EQ5 and Zarit scales were administered at baseline and 6 months later. After each session participants filled-out a modified EduPark satisfaction questionnaire and a Likert scale. Educational material was generated for each session after suggestions by participants. RESULTS: At baseline PwMSA and caregivers were comparable in age and sex, with significant correlation between UMSARS-IV (disability) and PDQ39 (quality of life). Adherence to sessions was of 94,92 %. Total modified EduPark scores and Likert scales did not differ in PwMSA vs. caregivers, mild-moderate vs. severe-advanced cases or between genders. The significant difference in satisfaction across sessions (p = 0.03) was driven by higher scores in speech, respiratory and occupational therapy sessions. Longitudinally there was no significant worsening in any scale, nor a significant increase post-vs. pre-program in the number of consultations. CONCLUSIONS: The healthcare education program in MSA was feasible, satisfactory, and safe for patients and caregivers. The educational material of the program is being forwarded to incident MSA cases attending our clinic.

Bilevel Parameter Learning for Higher-Order Total Variation Regularisation Models.

We consider a bilevel optimisation approach for parameter learning in higher-order total variation image reconstruction models. Apart from the least squares cost functional, naturally used in bilevel learning, we propose and analyse an alternative cost based on a Huber-regularised TV seminorm. Differentiability properties of the solution operator are verified and a first-order optimality system is derived. Based on the adjoint information, a combined quasi-Newton/semismooth Newton algorithm is proposed for the numerical solution of the bilevel problems. Numerical experiments are carried out to show the suitability of our approach and the improved performance of the new cost functional. Thanks to the bilevel optimisation framework, also a detailed comparison between TGV 2 and ICTV is carried out, showing the advantages and shortcomings of both regularisers, depending on the structure of the processed images and their noise level.