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For: Melin M, Hagerman I, Gonon A, Gustafsson T, Rullman E. Variability in Physical Activity Assessed with Accelerometer Is an Independent Predictor of Mortality in CHF Patients. PLoS One 2016;11:e0153036. [PMID: 27054323 DOI: 10.1371/journal.pone.0153036] [Cited by in Crossref: 10] [Cited by in F6Publishing: 11] [Article Influence: 1.7] [Reference Citation Analysis]
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3 Kolk MZ, Frodi DM, Andersen TO, Langford J, Diederichsen SZ, Svendsen JH, Tan HL, Knops RE, Tjong FV. Accelerometer-assessed physical behavior and the association with clinical outcomes in implantable cardioverter-defibrillator recipients: A systematic review. Cardiovascular Digital Health Journal 2021. [DOI: 10.1016/j.cvdhj.2021.11.006] [Reference Citation Analysis]
4 Khandwalla RM, Grant D, Birkeland K, Heywood JT, Fombu E, Owens RL, Steinhubl SR; AWAKE-H. F. Study Investigators. The AWAKE-HF Study: Sacubitril/Valsartan Impact on Daily Physical Activity and Sleep in Heart Failure. Am J Cardiovasc Drugs 2021;21:241-54. [PMID: 32978755 DOI: 10.1007/s40256-020-00440-y] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
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6 Rullman E, Melin M, Mandić M, Gonon A, Fernandez-Gonzalo R, Gustafsson T. Circulatory factors associated with function and prognosis in patients with severe heart failure. Clin Res Cardiol 2020;109:655-72. [PMID: 31562542 DOI: 10.1007/s00392-019-01554-3] [Cited by in Crossref: 8] [Cited by in F6Publishing: 12] [Article Influence: 2.7] [Reference Citation Analysis]
7 Yoshimura K, Urabe Y, Maeda N, Yoshida T. Relationship Between Energy Expenditure During Walking and Step Length in Patients With Heart Failure. Topics in Geriatric Rehabilitation 2019;35:97-103. [DOI: 10.1097/tgr.0000000000000206] [Reference Citation Analysis]
8 Tan MKH, Wong JKL, Bakrania K, Abdullahi Y, Harling L, Casula R, Rowlands AV, Athanasiou T, Jarral OA. Can activity monitors predict outcomes in patients with heart failure? A systematic review. Eur Heart J Qual Care Clin Outcomes 2019;5:11-21. [PMID: 30215706 DOI: 10.1093/ehjqcco/qcy038] [Cited by in Crossref: 8] [Cited by in F6Publishing: 12] [Article Influence: 2.7] [Reference Citation Analysis]
9 Doumouras BS, Lee DS, Levy WC, Alba AC. An Appraisal of Biomarker-Based Risk-Scoring Models in Chronic Heart Failure: Which One Is Best? Curr Heart Fail Rep 2018;15:24-36. [PMID: 29404976 DOI: 10.1007/s11897-018-0375-y] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 2.7] [Reference Citation Analysis]
10 Bergman P. The number of repeated observations needed to estimate the habitual physical activity of an individual to a given level of precision. PLoS One 2018;13:e0192117. [PMID: 29390010 DOI: 10.1371/journal.pone.0192117] [Cited by in Crossref: 14] [Cited by in F6Publishing: 13] [Article Influence: 3.5] [Reference Citation Analysis]
11 Jamé S, Kutyifa V, Polonsky B, Mcnitt S, Al-ahmad A, Moss AJ, Zareba W, Wang PJ. Predictive value of device-derived activity level for short-term outcomes in MADIT-CRT. Heart Rhythm 2017;14:1081-6. [DOI: 10.1016/j.hrthm.2017.03.032] [Cited by in Crossref: 7] [Cited by in F6Publishing: 10] [Article Influence: 1.4] [Reference Citation Analysis]