Decision Support for Treatment of Patients with Advanced Parkinson’s Disease
Sammanfattning: The overall aim of this thesis was to develop, deploy and evaluate new IT-based methods for supporting treatment and assessment of treatment of advanced Parkinson’s disease. In this condition a number of different motor and non-motor symptoms occur in episodes of varying frequency, duration and severity. In order to determine outcome of treatment changes, repeated assessments are necessary. Hospitalization for observation is expensive and may not be representative for the situation at home. Paper home diaries have questionable reliability and storage and retrieval of results are problematic. Approaches for monitoring using wearable sensors are unable to address important non-motor symptoms.A test battery system consisting of both self-assessments of symptoms and motor function tests was constructed for a touch screen mobile phone. Tests are performed on several occasions per day during test periods of one week. Data is transmitted over the mobile net to a central server where summaries in different symptom dimensions and an overall test score per patient and test period are calculated. There is a web application that graphically presents the results to treating clinical staff. As part of this work, a novel method for assessment of spiral drawing impairment useful during event-driven sampling was developed. To date, the system has been used by over 100 patients in 10 clinics in Sweden and Italy. Evidence is growing that the test battery is useful, reliable and valid for assessment of symptoms during advanced Parkinson’s disease.Infusion of a levodopa/carbidopa gel into the small intestine has been shown to reduce variation in plasma drug levels and improve clinical response in this patient category. A pharmacokinetic-pharmacodynamic model of this intestinal gel infusion was constructed. Possibly this model can assist the process of individualization of dosage for this treatment through in numero simulations. Results from an exploratory data analysis indicate that severity measures during oral levodopa treatment may be factors to consider when deciding candidates for infusion treatment.
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