{Reference Type}: Journal Article
{Title}: Utility of wearable physical activity monitors in cardiovascular disease: a systematic review of 11 464 patients and recommendations for optimal use.
{Author}: Hammond-Haley M;Allen C;Han J;Patterson T;Marber M;Redwood S;
{Journal}: Eur Heart J Digit Health
{Volume}: 2
{Issue}: 2
{Year}: Jun 2021
暂无{DOI}: 10.1093/ehjdh/ztab035
{Abstract}: <B>UNASSIGNED: </B>Physical activity (PA) plays an important role in primary and secondary prevention of cardiovascular disease (CVD), functioning as a marker of disease progression and response to therapy. Real-world measurement of habitual PA is now possible through wearable activity monitors, however, their use in cardiovascular patients is not well described.<BR><B>UNASSIGNED: </B>We performed a systematic review to summarize how wearable activity monitors have been used to measure PA in patients with CVD, with 11 464 patients included across 108 studies. Activity monitors were primarily used in the setting of cardiac rehabilitation (46, 43%). Most often, triaxial accelerometers (70, 65%) were instructed to be worn at the hip (58, 54%) for 7 days (n = 54, 50%). Thirty-nine different activity monitors were used, with a range of accelerometer specific settings for collection and reporting of activity data. Activity was reported most commonly as time spent in metabolic equivalent-defined activity levels (49, 45%), while non-wear time was defined in just 16 (15%) studies.<BR><B>UNASSIGNED: </B>The collecting, processing, and reporting of accelerometer-related outcomes were highly heterogeneous. Most validation studies are limited to healthy young adults, while the paucity of methodological information disclosed renders interpretation of results and cross-study comparison challenging. While accelerometers are promising tools to measure real-world PA, we highlight current challenges facing their use in elderly multimorbid cardiology patients. We suggest recommendations to guide investigators using these devices in cardiovascular research. Future work is required to determine optimal methodology and consensus-based development of meaningful outcomes using raw acceleration data.