Details

Autor(en) / Beteiligte

• Schink, Kristin
• Gaßner, Heiko
• Reljic, Dejan
• Herrmann, Hans J.
• Kemmler, Wolfgang
• Schwappacher, Raphaela
• Meyer, Julia
• Eskofier, Björn M.
• Winkler, Jürgen
• Neurath, Markus F.
• Klucken, Jochen
• Zopf, Yurdagül

Titel

Assessment of gait parameters and physical function in patients with advanced cancer participating in a 12‐week exercise and nutrition programme: A controlled clinical trial

Ist Teil von

• European journal of cancer care, 2020-03, Vol.29 (2), p.e13199-n/a

Ort / Verlag

England: Hindawi Limited

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• Objective Gait is a sensitive marker for functional declines commonly seen in patients treated for advanced cancer. We tested the effect of a combined exercise and nutrition programme on gait parameters of advanced‐stage cancer patients using a novel wearable gait analysis system. Methods Eighty patients were allocated to a control group with nutritional support or to an intervention group additionally receiving whole‐body electromyostimulation (WB‐EMS) training (2×/week). At baseline and after 12 weeks, physical function was assessed by a biosensor‐based gait analysis during a six‐minute walk test, a 30‐s sit‐to‐stand test, a hand grip strength test, the Karnofsky Index and EORTC QLQ–C30 questionnaire. Body composition was measured by bioelectrical impedance analysis and inflammation by blood analysis. Results Final analysis included 41 patients (56.1% male; 60.0 ± 13.0 years). After 12 weeks, the WB‐EMS group showed higher stride length, gait velocity (p < .05), six‐minute walking distance (p < .01), bodyweight and skeletal muscle mass, and emotional functioning (p < .05) compared with controls. Correlations between changes in gait and in body composition, physical function and inflammation were detected. Conclusion Whole‐body electromyostimulation combined with nutrition may help to improve gait and functional status of cancer patients. Sensor‐based mobile gait analysis objectively reflects patients’ physical status and could support treatment decisions.