Karen Mactier1, Sue Lord2, Alan Godfrey3, David Burn4, Lynn Rochester5. 1. Institute of Neuroscience, Newcastle University, NE4 5PL, UK. Electronic address: karen.mactier@newcastle.ac.uk. 2. Institute of Neuroscience, Newcastle University, NE4 5PL, UK. Electronic address: sue.lord@newcastle.ac.uk. 3. Institute of Neuroscience, Newcastle University, NE4 5PL, UK. Electronic address: alan.godrey@newcastle.ac.uk. 4. Institute of Neuroscience, Newcastle University, NE4 5PL, UK. Electronic address: david.burn@newcastle.ac.uk. 5. Institute of Neuroscience, Newcastle University, NE4 5PL, UK. Electronic address: lynn.rochester@newcastle.ac.uk.
Abstract
INTRODUCTION: Few studies have categorized falls in early Parkinson's disease (PD) and little is known about falls incidence and evolution. Fall incidence and frequency are reported to be 'U' shaped with respect to disease severity and may be influenced by time spent engaged in ambulatory activity. METHODS: Twelve months prospective falls in an incident PD cohort (n = 111) were reported and the relationship between falls and ambulatory activity was examined in a subgroup (n = 83). Fall events were collected using standardised protocols and were categorized by fall frequency (non-faller, single fall, recurrent falls) and also by a novel classification based on pre-fall event: (1) engaged in advanced activity; (2) ambulation; and (3) transition. Non-parametric statistics compared groups in both classifications. RESULTS: At baseline 23 (20.7%) of the cohort had fallen, increasing to 41 (36.9%) participants over 12 months. Total time spent walking was significantly lower for transition fallers compared with non-fallers and ambulation fallers (p = 0.041), who also had significantly increased disease severity. There were no significant relationships when fallers were categorized by frequency. We present an inverted U curve model depicting the relationship between falls and activity over time in PD, and propose that at this stage transition and ambulation fallers occupy different places on the curve. CONCLUSIONS: Falls are more common than recognised in newly-diagnosed PD. Daily activity is reduced even in early disease for people who fall during transitions. Classification methods that take pre-fall event into account may be useful to understand the heterogeneity of this complex problem. Crown
INTRODUCTION: Few studies have categorized falls in early Parkinson's disease (PD) and little is known about falls incidence and evolution. Fall incidence and frequency are reported to be 'U' shaped with respect to disease severity and may be influenced by time spent engaged in ambulatory activity. METHODS: Twelve months prospective falls in an incident PD cohort (n = 111) were reported and the relationship between falls and ambulatory activity was examined in a subgroup (n = 83). Fall events were collected using standardised protocols and were categorized by fall frequency (non-faller, single fall, recurrent falls) and also by a novel classification based on pre-fall event: (1) engaged in advanced activity; (2) ambulation; and (3) transition. Non-parametric statistics compared groups in both classifications. RESULTS: At baseline 23 (20.7%) of the cohort had fallen, increasing to 41 (36.9%) participants over 12 months. Total time spent walking was significantly lower for transition fallers compared with non-fallers and ambulation fallers (p = 0.041), who also had significantly increased disease severity. There were no significant relationships when fallers were categorized by frequency. We present an inverted U curve model depicting the relationship between falls and activity over time in PD, and propose that at this stage transition and ambulation fallers occupy different places on the curve. CONCLUSIONS: Falls are more common than recognised in newly-diagnosed PD. Daily activity is reduced even in early disease for people who fall during transitions. Classification methods that take pre-fall event into account may be useful to understand the heterogeneity of this complex problem. Crown
Authors: Natalie E Allen; Colleen G Canning; Lorena Rosa S Almeida; Bastiaan R Bloem; Samyra Hj Keus; Niklas Löfgren; Alice Nieuwboer; Geert Saf Verheyden; Tiê P Yamato; Catherine Sherrington Journal: Cochrane Database Syst Rev Date: 2022-06-06
Authors: Victoria A Goodwin; Ruth Pickering; Claire Ballinger; Helen Roberts; Emma McIntosh; Sarah Lamb; Alice Nieuwboer; Lynn Rochester; Ann Ashburn Journal: BMC Neurol Date: 2015-05-15 Impact factor: 2.474