November 2024
Proposed World Falls Guidelines modifications may better identify older people at risk
By Melanie Hinze
Australian researchers have proposed two simple modifications to the World Falls Guidelines algorithm to better identify older people at intermediate risk of falls.
Published in Age and Ageing, the researchers conducted a secondary analysis of the World Falls Guidelines algorithm’s ability to stratify older people into sizeable fall-risk groups, or whether minor modifications were necessary to achieve this.
Overall, 693 community-living adults aged 70 to 90 years (52.4% women) were stratified into low-, intermediate- and high-fall-risk groups using both the original algorithm and a modified algorithm.The modified algorithm involved using a cutoff point of greater than 10 seconds for the Timed Up and Go (TUG) test screening, rather than the original greater than 15 seconds. It also required all participants not classified as high risk (that is, without a positive fall-severity factor) to undertake a TUG test, with slower participants (greater than 10 seconds) classified as being at intermediate risk of falls.
The researchers found that the original algorithm was not able to identify three sizeable groups, with only five participants (0.7%) classified as intermediate risk. In contrast, the modified algorithm classified 349 participants (50.3%) as low risk, 127 (18.3%) as intermediate risk and 217 (31.3%) as high risk.
The researchers reported that the intermediate-risk group had similar physical and neuropsychological characteristics to the high-risk group, but a fall rate that was similar to the low-risk group.
Professor Stephen Lord, coauthor of the paper and Senior Principal Research Fellow in the Falls Balance and Injury Research Centre at Neuroscience Research Australia, Sydney, said that this research was important due to the rapid uptake of the World Falls Guidelines globally.
‘However, they have one limitation in that although the algorithm used for categorising older people into low, moderate and high risk of falls was made with expert consensus, it was not validated in a research study.’
Professor Lord noted that being better able to identify older people at moderate risk of falls was important as interventions such as balance training exercises might prevent this intermediate-risk group transitioning to being at a high risk of falls and frailty.
‘The modified algorithm does not need any equipment, as it relies on a medical history, a few questions and a simple timed mobility test (the TUG test), so it can be used in a doctor’s surgery,’ he said.
‘With this information, more tailored interventions can be targeted to those at low, moderate and high risk of falls,’ he added.