Abstract

PurposeThe study evaluates the use of heart rate variability (HRV), a measure of autonomic nervous system (ANS) modulation via wearable smart bands, to objectively assess cancer-related fatigue (CRF) levels. It aims to enhance understanding of fatigue by distinguishing between LF/HF ratios and LF/HF disorder ratios through HRV and photoplethysmography (PPG), identifying them as potential biomarkers. MethodsSeventy-one lung cancer patients and 75 non-cancer controls wore smart bands for one week. Fatigue was assessed using Brief Fatigue Inventory, alongside sleep quality and daily interference. HRV parameters were analyzed to compare groups. ResultsCancer patients showed higher fatigue and interference levels than controls (64.8% vs. 54.7%). Those with mild fatigue had elevated LF/HF disorder ratios during sleep (40% vs. 20%, P = 0.01), similar to those with moderate to severe fatigue (50% vs. 20%, P = 0.01), indicating more significant autonomic dysregulation. Notably, mild fatigue patients had higher mean LF/HF ratios than controls (1.9 ± 1.34 vs. 1.2 ± 0.6, P = 0.01), underscoring the potential of disorder ratios in signaling fatigue severity. ConclusionsUtilizing wearable smart bands for HRV-based analysis is feasible for objectively assess CRF levels in cancer patients, especially during sleep. By distinguishing between LF/HF ratios and LF/HF disorder ratios, our findings suggest that wearable technology and detailed HRV analysis offer promising avenues for real-time fatigue monitoring. This approach has the potential to significantly improve cancer care by providing new methods for managing and intervening in CRF, particularly with a focus on autonomic dysregulation as a crucial factor.

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