The article reviewed here is ‘Incidence and Prediction of Falls in Dementia: A Prospective Study in Older People’ by Allan and colleagues and freely available here. The authors identify the aim of the study as follows
‘to identify modifiable risk factors for falling in older people with mild to moderate dementia‘
The authors note in their introduction that a number of risk factors in the general population have been identified:-
‘In multivariate studies significant risk factors include fall history, gait, balance and mobility impairments, visual impairment, cognitive impairment, fear of falling, environmental hazards, muscle weakness and incontinence‘
The question here however is what kind of risk factors are there for falls in dementia? In order to answer this question, the researchers include healthy controls as well as subjects with Alzheimer’s Disease (AD), Vascular Dementia (VaD), Lewy Body Dementia (LBD) (who are oversampled in order to ensure comparisons can be made with the other groups) and Parkinson’s Disease with Dementia (PDD). The researchers note that a random sampling from the community would have been preferable to the inclusion of consecutive patients from community clinics. However it can also be argued that such participants are representative of the patients seen in clinical practice. They list the inclusion and exclusion criteria which I thought seemed entirely reasonable and again reflected pragmatic issues in clinical practice.
The authors include several helpful definitions of terms that they use to avoid ambiguity. They use a prospective (12-month) design for the study and include a number of baseline characteristics such as body mass index and ratings such as Unified Parkinson’s Disease rating scale motor component, depression (Cornell scale), Bristol activities of daily living scale and Neuropsychological inventory. They also look at blood pressure using a photoplethysmograph (see below)
The primary outcome measures are prevalence and incidence of falls with secondary outcomes of ‘proportional hazard ratios for time to first fall in dementia according to diagnosis and status of putative clinical predictors’. The statistical methods used for the different types of data are clearly described.
In terms of the results, the survival curve (describing the time to the first fall) follows the trend for the prevalence data with a lower end-point in the order lowest first: PDD, DLB, VaD, AD and controls. The incidence of falls shows a similar sequence although the VaD and AD groups are not statistically significantly different from each other.
Univariate and multivariate analyses of predictors for falls in people with dementia were undertaken and in the univariate analysis the researchers found the following variables significantly predicted falls
History of falls/Recurrent falls over last 12 months
‘Use of cardioactive medication’
Abnormal gait/balance score
Cornell depression score >= 10
Autonomic symptom scale > 7
Symptomatic Orthostatic Hypotension
‘Time taken for blood pressure to return to baseline on standing’
The multivariate analysis included one model in which ‘Cornell depression score, total autonomic symptom score and symptomatic orthostatic hypotension’ were retained, while the other model stratified subjects according to diagnosis when
‘predictors retained were symptomatic orthostatic hypotension, use of cardiovascular medication and physical activity score, which was protective‘
The authors note that some of the univariate predictors may have been proxy markers for dementia diagnoses explaining why they weren’t included in the final model which was stratified according to diagnosis.
I thought this was quite a nice paper, written concisely with a clear organisation, definitions of relevant terms, a prospective design with relevant groupings for comparison and asking an important clinical question while providing in the results some valuable information which has the potential to impact on patient’s lives.
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