As more of the world population continues to live into old age, falls are becoming a global health challenge and their prevention paramount. Malaysian researchers developed a clustering algorithm to sort 1400 patients (age 55+) into low, intermediate A, intermediate B, and high risk groups which corresponded with fall occurrence of 13%, 19%, 21%, and 31%, respectively. Participants clustered in the high falls risk group possessed 50% higher odds of falls compared to the overall dataset. Participants included in the high falls risk group had slower gait, poorer balance, weaker muscle strength, presence of cardiovascular disorder, poorer cognitive performance, and advancing age. The authors concluded that this clustering algorithm represents a potential clinical decision support tool to identify high risk fallers for falls prevention initiatives, thus improving case finding and reducing burdens on the currently limited resource of clinicians trained in managing older adults.
Source: Goh C-H, Wong KK, Tan MP, Ng S-C, Chuah YD, Kwan B-H. Development of an effective clustering algorithm for older fallers. PLoS ONE. 2022;17(11):e0277966. https://doi.org/10.1371/journal.pone.0277966.
