Literature DB >> 23039867

Early treatment of Parkinson's disease: opportunities for managed care.

Daniel L Murman1.   

Abstract

The diagnosis and treatment of Parkinson's disease (PD) typically occur when the disease has already progressed to a relatively advanced stage in which motor symptoms are clearly evident and substantial neurophysiological damage has already taken place. Nonmotor symptoms, which account for a large proportion of PD symptoms, usually emerge much earlier and offer both an early indication for treatment and a therapeutic target. A growing body of data from the medical literature points to several critical advantages that may be associated with early therapeutic intervention in PD. The most evident benefit of early intervention is a reduction in symptoms, particularly dyskinesia, and the delay of levodopa initiation. Clinical trials suggest but have yet to conclusively demonstrate that early treatment can slow disease progression. Both the diminishment of symptoms and the potential for slowing disease progression have large implications for improving patient quality of life. The enormous direct costs associated with PD would also likely be reduced over the long term with earlier treatment. The great majority of costs attributable to PD occur when the disease is at its most advanced stage and when symptoms are most severe. An early-treatment strategy that diminishes symptoms and that has the potential to slow disease progression could have a meaningful impact on PD expenditures. Adherence, too, must be taken into consideration, particularly since PD patients are generally poorly adherent to prescribed therapies, especially therapies with complex dosing schedules. Taking advantage of more convenient and adherencefriendly drug formulations may further help to improve outcomes and lower costs in PD.

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Year:  2012        PMID: 23039867

Source DB:  PubMed          Journal:  Am J Manag Care        ISSN: 1088-0224            Impact factor:   2.229


  9 in total

1.  Advanced-Stage Parkinson's Disease: From Identification to Characterization Using a Nationwide Database.

Authors:  Yael Barer; Tanya Gurevich; Gabriel Chodick; Nir Giladi; Ruth Gross; Raanan Cohen; Lars Bergmann; Yash J Jalundhwala; Varda Shalev; Meital Grabarnik-John; Avner Thaler
Journal:  Mov Disord Clin Pract       Date:  2022-04-29

2.  Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease.

Authors:  Dimitrios Iakovakis; Stelios Hadjidimitriou; Vasileios Charisis; Sevasti Bostantzopoulou; Zoe Katsarou; Leontios J Hadjileontiadis
Journal:  Sci Rep       Date:  2018-05-16       Impact factor: 4.379

3.  Stress-induced localization of HSPA6 (HSP70B') and HSPA1A (HSP70-1) proteins to centrioles in human neuronal cells.

Authors:  Sam Khalouei; Ari M Chow; Ian R Brown
Journal:  Cell Stress Chaperones       Date:  2013-09-06       Impact factor: 3.667

4.  metabolic profiling of Parkinson's disease and mild cognitive impairment.

Authors:  Florence Burté; David Houghton; Hannah Lowes; Angela Pyle; Sarah Nesbitt; Alison Yarnall; Patrick Yu-Wai-Man; David J Burn; Mauro Santibanez-Koref; Gavin Hudson
Journal:  Mov Disord       Date:  2017-04-10       Impact factor: 10.338

Review 5.  Gut Microbiota Dysfunction as Reliable Non-invasive Early Diagnostic Biomarkers in the Pathophysiology of Parkinson's Disease: A Critical Review.

Authors:  Arun T Nair; Vadivelan Ramachandran; Nanjan M Joghee; Shanish Antony; Gopalakrishnan Ramalingam
Journal:  J Neurogastroenterol Motil       Date:  2018-01-30       Impact factor: 4.924

6.  Parkinson patients without tremor show changed patterns of mechanical muscle oscillations during a specific bilateral motor task compared to controls.

Authors:  Laura V Schaefer; Frank N Bittmann
Journal:  Sci Rep       Date:  2020-01-24       Impact factor: 4.379

7.  Unobtrusive detection of Parkinson's disease from multi-modal and in-the-wild sensor data using deep learning techniques.

Authors:  Alexandros Papadopoulos; Dimitrios Iakovakis; Lisa Klingelhoefer; Sevasti Bostantjopoulou; K Ray Chaudhuri; Konstantinos Kyritsis; Stelios Hadjidimitriou; Vasileios Charisis; Leontios J Hadjileontiadis; Anastasios Delopoulos
Journal:  Sci Rep       Date:  2020-12-07       Impact factor: 4.379

8.  Predicting Parkinson's Disease Progression: Evaluation of Ensemble Methods in Machine Learning.

Authors:  Mehrbakhsh Nilashi; Rabab Ali Abumalloh; Behrouz Minaei-Bidgoli; Sarminah Samad; Muhammed Yousoof Ismail; Ashwaq Alhargan; Waleed Abdu Zogaan
Journal:  J Healthc Eng       Date:  2022-02-03       Impact factor: 2.682

9.  The effects of a mindfulness-based lifestyle program for adults with Parkinson's disease: a mixed methods, wait list controlled randomised control study.

Authors:  Jenny Advocat; Joanne Enticott; Brooke Vandenberg; Craig Hassed; Jennifer Hester; Grant Russell
Journal:  BMC Neurol       Date:  2016-09-08       Impact factor: 2.474

  9 in total

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