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For: Hung RK, Al-Mallah MH, McEvoy JW, Whelton SP, Blumenthal RS, Nasir K, Schairer JR, Brawner C, Alam M, Keteyian SJ, Blaha MJ. Prognostic value of exercise capacity in patients with coronary artery disease: the FIT (Henry Ford ExercIse Testing) project. Mayo Clin Proc 2014;89:1644-54. [PMID: 25440889 DOI: 10.1016/j.mayocp.2014.07.011] [Cited by in Crossref: 54] [Cited by in F6Publishing: 54] [Article Influence: 6.0] [Reference Citation Analysis]
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5 Drugescu A, Roca M, Zota IM, Costache AD, Gavril OI, Gavril RS, Vasilcu TF, Mitu O, Esanu IM, Roca IC, Ghiciuc CM, Mitu F. Value of the Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio in Predicting CPET Performance in Patients with Stable CAD and Recent Elective PCI. Medicina (Kaunas) 2022;58. [PMID: 35744077 DOI: 10.3390/medicina58060814] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 9.0] [Reference Citation Analysis]
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16 Al Rifai M, Blaha MJ, Ahmed A, Almasoudi F, Johansen MC, Qureshi W, Sakr S, Virani SS, Brawner CA, Ehrman JK, Keteyian SJ, Al-Mallah MH. Cardiorespiratory Fitness and Incident Stroke Types: The FIT (Henry Ford ExercIse Testing) Project. Mayo Clin Proc 2020;95:1379-89. [PMID: 32622446 DOI: 10.1016/j.mayocp.2019.11.027] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]
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19 Marcin T, Eser P, Prescott E, Mikkelsen N, Prins LF, Kolkman EK, Lado-baleato Ó, Cardaso-suaréz C, Bruins W, van der Velde AE, Peña Gil C, Iliou MC, Ardissino D, Zeymer U, Meindersma EP, Van’t Hof AW, de Kluiver EP, Wilhelm M. Predictors of pre-rehabilitation exercise capacity in elderly European cardiac patients – The EU-CaRE study. Eur J Prev Cardiolog 2020;27:1702-12. [DOI: 10.1177/2047487319894676] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 1.5] [Reference Citation Analysis]
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21 Mikkelsen N, Cadarso-suárez C, Lado-baleato O, Díaz-louzao C, Gil CP, Reeh J, Rasmusen H, Prescott E. Improvement in VO 2peak predicts readmissions for cardiovascular disease and mortality in patients undergoing cardiac rehabilitation. Eur J Prev Cardiolog 2020;27:811-9. [DOI: 10.1177/2047487319887835] [Cited by in Crossref: 28] [Cited by in F6Publishing: 28] [Article Influence: 7.0] [Reference Citation Analysis]
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23 Rifai MA, Qureshi WT, Dardari Z, Keteyian SJ, Brawner CA, Ehrman JK, Ahmed A, Sakr S, Virani SS, Blaha MJ, Al-Mallah MH. The Interplay of the Global Atherosclerotic Cardiovascular Disease Risk Scoring and Cardiorespiratory Fitness for the Prediction of All-Cause Mortality and Myocardial Infarction: The Henry Ford ExercIse Testing Project (The FIT Project). Am J Cardiol 2019;124:511-7. [PMID: 31221461 DOI: 10.1016/j.amjcard.2019.05.033] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
24 Mikkelsen N, Dall CH, Frederiksen M, Holdgaard A, Rasmusen H, Prescott E. Depression, Socioeconomic Factors, and Ethnicity as Predictors of Cardiorespiratory Fitness Before and After Cardiac Rehabilitation. Journal of Cardiopulmonary Rehabilitation and Prevention 2019;39:E1-6. [DOI: 10.1097/hcr.0000000000000367] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 2.3] [Reference Citation Analysis]
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28 Al Rifai M, Al-Mallah MH. Is pulse pressure a novel cardiovascular disease risk marker in secondary prevention? Atherosclerosis 2018;277:175-6. [PMID: 30150081 DOI: 10.1016/j.atherosclerosis.2018.07.035] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.6] [Reference Citation Analysis]
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30 Sakr S, Elshawi R, Ahmed A, Qureshi WT, Brawner C, Keteyian S, Blaha MJ, Al-Mallah MH. Using machine learning on cardiorespiratory fitness data for predicting hypertension: The Henry Ford ExercIse Testing (FIT) Project. PLoS One 2018;13:e0195344. [PMID: 29668729 DOI: 10.1371/journal.pone.0195344] [Cited by in Crossref: 55] [Cited by in F6Publishing: 59] [Article Influence: 11.0] [Reference Citation Analysis]
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36 Sakr S, Elshawi R, Ahmed AM, Qureshi WT, Brawner CA, Keteyian SJ, Blaha MJ, Al-Mallah MH. Comparison of machine learning techniques to predict all-cause mortality using fitness data: the Henry ford exercIse testing (FIT) project. BMC Med Inform Decis Mak 2017;17:174. [PMID: 29258510 DOI: 10.1186/s12911-017-0566-6] [Cited by in Crossref: 38] [Cited by in F6Publishing: 40] [Article Influence: 6.3] [Reference Citation Analysis]
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