Background: Handgrip strength (HGS) is widely recognized as a key indicator of muscle function and sarcopenia risk, but the use of hand dynamometers is often limited in community settings. This study aimed to develop and evaluate a simple two-step serial screening algorithm using the Timed Up & Go (TUG) and the Modified Dynamic Reaching Test (MDRT) to identify older women with low handgrip strength.
Methods: Sixty community-dwelling older women (age, mean±SD = 67.43±4.43 year) participated in this pilot study. Low HGS was defined as 7.57 seconds derived from receiver operating characteristic (ROC) analysis (sensitivity = 0.882). Step 2 (MDRT) focused on specificity, using a cutoff value of ≤73.5 cm (specificity = 0.882). The two-step algorithm was considered positive only when both criteria were met.
Results: Among 60 valid cases, 17 participants (28.3%) had low HGS. The two-step screening correctly identified 13 true positives and 43 true negatives, yielding a sensitivity of 0.765, specificity of 1.000, positive predictive value of 1.000, negative predictive value of 0.915, and overall accuracy of 0.933. No false positives were observed, indicating strong discriminative specificity.
Conclusions: The proposed TUG–MDRT serial algorithm demonstrated high screening accuracy and practical feasibility for detecting low handgrip strength among community-dwelling older women. This two-step approach offers a rapid, low-cost, and field-applicable alternative for identifying individuals who may benefit from further muscle strength assessment or intervention.

Authors:
Saisunee Konsanit, University of Phayao, Thailand
Weerasak Tapanya, University of Phayao, Thailand
Patchareeya Amput, University of Phayao, Thailand

About the Presenter(s)
Physical therapist at University of Phayao, Thailand. I research exercise-based rehabilitation for older adults and people with chronic diseases, developing evidence-based programs to improve function, and prevent complications.

See this presentation on the full schedule – Tuesday Schedule

Bookmark