Why the study?
Although frailty is associated with an impaired autonomic nervous system, the direct effect of frailty on heart rate behavior during physical activity remains unclear.
Does a multimodal model combining kinematics and heart rate dynamics during an upper-extremity function task accurately predict frailty in older adults?
Does a multimodal model combining kinematics and heart rate dynamics during an upper-extremity function task accurately predict frailty in older adults?
Combining kinematics and heart rate dynamics during a brief upper-extremity task provides a promising objective tool for assessing frailty in older adults.
May aid objective frailty screening via brief upper-extremity tasks; hypothesis-generating and requires prospective validation before practice change.
Background : Previous research showed association between frailty and an impaired autonomic nervous system; however, the direct effect of frailty on heart rate (HR) behavior during physical activity is unclear. The purpose of the current study was to determine the association between HR increase and decrease with frailty during a localized upper-extremity function (UEF) task to establish a multimodal frailty test. Methods : Older adults aged 65 or older were recruited and performed the UEF task of rapid elbow flexion for 20 seconds with the right arm. Wearable gyroscopes were used to measure forearm and upper-arm motion, and electrocardiography were recorded using leads on the left chest. Using this setup, HR dynamics were measured, including time to peak HR, recovery time, percentage increase in HR during UEF, and percentage decrease in HR during recovery after UEF. Results : Fifty-six eligible participants were recruited, including 12 non-frail (age=76.92±7.32 years), and 44 pre-frail/frail (age=81.23±8.14 years). Analysis of variance models showed that the percentage increase in HR during UEF and percentage decrease in HR during recovery were both 47% smaller in pre-frail/frail older adults compared to non-frails ( p <0.01, effect size = 1.42 and 1.17 for increase and decrease percentages). Using logistic models with both UEF kinematics and HR parameters as independent variables, frailty was predicted with a sensitivity of 0.82 and specificity of 0.83. Conclusion : Current findings showed evidence of strong association between HR dynamics and frailty. It is suggested that combining kinematics and HR data in a multimodal model may provide a promising objective tool for frailty assessment.
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Toosizadeh et al. (2021) studied this question.
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