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The effect of continuous levodopa treatment during the afternoon hours
Dalarna University, School of Technology and Business Studies, Microdata Analysis.
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0003-0403-338X
2019 (English)In: Acta Neurologica Scandinavica, ISSN 0001-6314, E-ISSN 1600-0404, Vol. 139, no 1, p. 70-75Article in journal (Refereed) Published
Abstract [en]

OBJECTIVE: The aim of this retrospective study was to investigate if patients with PD, who are treated with levodopa-carbidopa intestinal gel (LCIG), clinically worsen during the afternoon hours and if so, to evaluate whether this occurs in all LCIG-treated patients or in a sub-group of patients.

METHODS: Three published studies were identified and included in the analysis. All studies provided individual response data assessed on the treatment response scale (TRS) and patients were treated with continuous LCIG. Ninety-eight patients from the three studies fulfilled the criteria. T-tests were performed to find differences on the TRS values between the morning and the afternoon hours, linear mixed effect models were fitted on the afternoon hours' evaluations to find trends of wearing-off, and patients were classified into three TRS categories (meaningful increase in TRS, meaningful decrease in TRS, non -meaningful increase or decrease).

RESULTS: In all three studies significant statistical differences were found between the morning TRS values and the afternoon TRS values (p-value <= 0.001 in all studies). The linear mixed effect models had significant negative coefficients for time in two studies, and 48 out of 98 patients (49%) showed a meaningful decrease of TRS during the afternoon hours.

CONCLUSION: The results from all studies were consistent, both in the proportion of patients in the three groups and the value of TRS decrease in the afternoon hours. Based on these findings there seems to be a group of patients with predictable "off" behavior in the later parts of the day. This article is protected by copyright. All rights reserved.

Place, publisher, year, edition, pages
2019. Vol. 139, no 1, p. 70-75
Keywords [en]
diurnal motor fluctuation; infusion pumps; levodopa; Parkinson disease
National Category
Medical Engineering Probability Theory and Statistics
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-28478DOI: 10.1111/ane.13020ISI: 000452067700007PubMedID: 30180267Scopus ID: 2-s2.0-85053714059OAI: oai:DiVA.org:du-28478DiVA, id: diva2:1247179
Available from: 2018-09-11 Created: 2018-09-11 Last updated: 2019-02-06Bibliographically approved
In thesis
1. Automating levodopa dosing schedules for Parkinson’s disease
Open this publication in new window or tab >>Automating levodopa dosing schedules for Parkinson’s disease
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Parkinson’s disease (PD) is the second most common neurodegenerative disease. Levodopa is mainly used to manage the motor symptoms of PD. However, disease progression and long-term use of levodopa cause reduced medication efficacy and side effects. When that happens, precise individualized dosing schedules are required.

This doctoral thesis in the field of Micro-data analysis introduces an end-to-end solution for the automation of the pharmacological management of PD with levodopa, and offers some insight on levodopa pharmacodynamics. For that purpose, an algorithm that derives objective ratings for the patients’ motor function through wearable sensors is introduced, a method to construct individual patient profiles is developed, and two dosing algorithms for oral and intestinal administration of levodopa are presented. Data from five different sources were used to develop the methods and evaluate the performance of the proposed algorithms.

The dose automation algorithms can work both with clinical and objective ratings (through wearable devices), and their application was evaluated against dosing adjustments from movement disorders experts. Both dosing algorithms showed promise and their dosing suggestions were similar to those of the clinicians.

The objective ratings algorithm had good test-retest reliability and its application during a clinical study was successful. Furthermore, the method of fitting individual patient models was robust and worked well with the objective ratings algorithm. Finally, a study was carried out that showed that about half the patients on levodopa treatment show reduced response during the afternoon hours, pointing to the need for more precise modelling of levodopa pharmacodynamics.

Place, publisher, year, edition, pages
Borlänge: Dalarna University, 2019
Series
Dalarna Doctoral Dissertations in Microdata Analysis ; 9
Keywords
Parkinson’s disease, levodopa, symptom assessment, symptom management, dosing algorithms, wearable sensors, microtablets, continuous infusion
National Category
Computer Sciences Computer Systems Information Systems
Research subject
Complex Systems – Microdata Analysis, FLOAT - Flexible Levodopa Optimizing Assistive Technology
Identifiers
urn:nbn:se:du-29435 (URN)978-91-85941-80-3 (ISBN)
Public defence
2019-04-05, sal Clas Ohlson, Borlänge, 13:00 (English)
Opponent
Supervisors
Available from: 2019-03-11 Created: 2019-02-06 Last updated: 2019-06-17Bibliographically approved

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Thomas, IliasWestin, Jerker

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