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To assess fall risk in the elderly OPD patients using conventional fall risk tool and Kinesis QTUG device: A
Vivek Aggarwal1, S Shankar2, Pradeep Behl3
1Senior Registrar & OC Tps, 153 Gen Hosp, C/O 56 APO, India.
Medical Journal, Armed Forces India
|August 18, 2025
Summary
A digital sensor device (Kinesis QTUG) and a conventional tool (FRAT) showed poor agreement in assessing fall risk in elderly Indians. This highlights potential discrepancies in identifying high-risk individuals for falls prevention.
Area of Science:
- Gerontology
- Biomechanics
- Medical Devices
Background:
- Falls are a significant health concern for the elderly, often stemming from multiple factors.
- Early identification and management of fall risk factors are crucial for prevention.
- Assessing fall risk accurately is vital for implementing effective interventions in geriatric care.
Purpose of the Study:
- To evaluate the agreement between a digital sensor-based device, Kinesis Quantitative Timed Up and Go (QTUG), and a conventional Fall Risk Assessment Tool (FRAT).
- To determine the concordance of fall-risk assessment in the elderly Indian population using these two distinct methodologies.
Main Methods:
- The study was conducted in a tertiary care hospital in Western India.
- Fall risk was assessed using both the conventional FRAT score and the digital sensor-based Kinesis QTUG device.
- Agreement between the two assessment tools was statistically analyzed using unweighted kappa.
Main Results:
- The study included 147 elderly individuals with a mean age of 68.54 years; 53.3% were female.
- The Kinesis QTUG device identified 59.56% of elderly patients as high fall risk, contrasting with FRAT's 1.36%.
- A poor agreement was observed between the Kinesis QTUG and FRAT, indicated by an unweighted kappa value of 0.634.
Conclusions:
- The prevalence of falls in the elderly population within the study year was 40%.
- There is a significant lack of agreement between the Kinesis QTUG device and the FRAT score in estimating fall risk.
- These findings suggest a need for further validation and potential recalibration of fall risk assessment tools in diverse elderly populations.

