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For: Alba AC, Agoritsas T, Jankowski M, Courvoisier D, Walter SD, Guyatt GH, Ross HJ. Risk Prediction Models for Mortality in Ambulatory Patients With Heart Failure: A Systematic Review. Circ: Heart Failure 2013;6:881-9. [DOI: 10.1161/circheartfailure.112.000043] [Cited by in Crossref: 104] [Cited by in F6Publishing: 50] [Article Influence: 11.6] [Reference Citation Analysis]
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4 Yang H, Tian J, Meng B, Wang K, Zheng C, Liu Y, Yan J, Han Q, Zhang Y. Application of Extreme Learning Machine in the Survival Analysis of Chronic Heart Failure Patients With High Percentage of Censored Survival Time. Front Cardiovasc Med 2021;8:726516. [PMID: 34778396 DOI: 10.3389/fcvm.2021.726516] [Reference Citation Analysis]
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6 Naruse H, Ishii J, Takahashi H, Kitagawa F, Sakaguchi E, Nishimura H, Kawai H, Muramatsu T, Harada M, Yamada A, Fujiwara W, Hayashi M, Motoyama S, Sarai M, Watanabe E, Ito H, Ozaki Y, Izawa H. Combined Assessment of D-Dimer with the Get with the Guidelines-Heart Failure Risk Score and N-Terminal Pro-B-Type Natriuretic Peptide in Patients with Acute Decompensated Heart Failure with Preserved and Reduced Ejection Fraction. J Clin Med 2021;10:3564. [PMID: 34441860 DOI: 10.3390/jcm10163564] [Reference Citation Analysis]
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10 Simpson J, Jhund PS, Lund LH, Padmanabhan S, Claggett BL, Shen L, Petrie MC, Abraham WT, Desai AS, Dickstein K, Køber L, Packer M, Rouleau JL, Mueller-Velten G, Solomon SD, Swedberg K, Zile MR, McMurray JJV. Prognostic Models Derived in PARADIGM-HF and Validated in ATMOSPHERE and the Swedish Heart Failure Registry to Predict Mortality and Morbidity in Chronic Heart Failure. JAMA Cardiol 2020;5:432-41. [PMID: 31995119 DOI: 10.1001/jamacardio.2019.5850] [Cited by in Crossref: 14] [Cited by in F6Publishing: 13] [Article Influence: 14.0] [Reference Citation Analysis]
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12 Moyehodie YA, Muluneh MW, Belay AT, Fenta SM. Time to Death and Its Determinant Factors Among Patients With Chronic Heart Failure in Northwest Ethiopia: A Retrospective Study at Selected Referral Hospitals. Front Cardiovasc Med 2022;9:817074. [DOI: 10.3389/fcvm.2022.817074] [Reference Citation Analysis]
13 Vazquez-Montes MDLA, Debray TPA, Taylor KS, Speich B, Jones N, Collins GS, Hobbs FDRR, Magriplis E, Maruri-Aguilar H, Moons KGM, Parissis J, Perera R, Roberts N, Taylor CJ, Kadoglou NPE, Trivella M; proBHF group. UMBRELLA protocol: systematic reviews of multivariable biomarker prognostic models developed to predict clinical outcomes in patients with heart failure. Diagn Progn Res 2020;4:13. [PMID: 32864468 DOI: 10.1186/s41512-020-00081-4] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
14 Habal MV, Garan AR. Long-term management of end-stage heart failure. Best Pract Res Clin Anaesthesiol 2017;31:153-66. [PMID: 29110789 DOI: 10.1016/j.bpa.2017.07.003] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 1.6] [Reference Citation Analysis]
15 Damen JAAG, Debray TPA, Pajouheshnia R, Reitsma JB, Scholten RJPM, Moons KGM, Hooft L. Empirical evidence of the impact of study characteristics on the performance of prediction models: a meta-epidemiological study. BMJ Open 2019;9:e026160. [PMID: 30940759 DOI: 10.1136/bmjopen-2018-026160] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 2.7] [Reference Citation Analysis]
16 Rich JD, Burns J, Freed BH, Maurer MS, Burkhoff D, Shah SJ. Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score: Validation of a Simple Tool for the Prediction of Morbidity and Mortality in Heart Failure With Preserved Ejection Fraction. J Am Heart Assoc 2018;7:e009594. [PMID: 30371285 DOI: 10.1161/JAHA.118.009594] [Cited by in Crossref: 23] [Cited by in F6Publishing: 15] [Article Influence: 7.7] [Reference Citation Analysis]
17 Kasthurirathne SN, Grannis S, Halverson PK, Morea J, Menachemi N, Vest JR. Precision Health-Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation. JMIR Med Inform 2020;8:e16129. [PMID: 32479414 DOI: 10.2196/16129] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
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20 Kadoglou NPE, Parissis J, Karavidas A, Kanonidis I, Trivella M. Assessment of acute heart failure prognosis: the promising role of prognostic models and biomarkers. Heart Fail Rev 2021. [PMID: 34036472 DOI: 10.1007/s10741-021-10122-9] [Reference Citation Analysis]
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22 McGuinty C, Leong D, Weiss A, MacIver J, Kaya E, Hurlburt L, Billia F, Ross H, Wentlandt K. Heart Failure: A Palliative Medicine Review of Disease, Therapies, and Medications With a Focus on Symptoms, Function, and Quality of Life. J Pain Symptom Manage 2020;59:1127-1146.e1. [PMID: 31866489 DOI: 10.1016/j.jpainsymman.2019.12.357] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
23 Chicco D, Jurman G. Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone. BMC Med Inform Decis Mak 2020;20:16. [PMID: 32013925 DOI: 10.1186/s12911-020-1023-5] [Cited by in Crossref: 49] [Cited by in F6Publishing: 19] [Article Influence: 24.5] [Reference Citation Analysis]
24 Hearn J, Ross HJ, Mueller B, Fan CP, Crowdy E, Duhamel J, Walker M, Alba AC, Manlhiot C. Neural Networks for Prognostication of Patients With Heart Failure. Circ Heart Fail 2018;11:e005193. [PMID: 30354561 DOI: 10.1161/CIRCHEARTFAILURE.118.005193] [Cited by in Crossref: 9] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
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26 Koller L, Kleber ME, Brandenburg VM, Goliasch G, Richter B, Sulzgruber P, Scharnagl H, Silbernagel G, Grammer TB, Delgado G, Tomaschitz A, Pilz S, Berger R, Mörtl D, Hülsmann M, Pacher R, März W, Niessner A. Fibroblast Growth Factor 23 Is an Independent and Specific Predictor of Mortality in Patients With Heart Failure and Reduced Ejection Fraction. Circ Heart Fail 2015;8:1059-67. [PMID: 26273098 DOI: 10.1161/CIRCHEARTFAILURE.115.002341] [Cited by in Crossref: 30] [Cited by in F6Publishing: 18] [Article Influence: 4.3] [Reference Citation Analysis]
27 Campbell RT, Jackson CE, Wright A, Gardner RS, Ford I, Davidson PM, Denvir MA, Hogg KJ, Johnson MJ, Petrie MC, McMurray JJ. Palliative care needs in patients hospitalized with heart failure (PCHF) study: rationale and design. ESC Heart Fail 2015;2:25-36. [PMID: 27347426 DOI: 10.1002/ehf2.12027] [Cited by in Crossref: 16] [Cited by in F6Publishing: 15] [Article Influence: 2.3] [Reference Citation Analysis]
28 Vakil KP, Roukoz H, Tung R, Levy WC, Anand IS, Shivkumar K, Rector TS, Vaseghi M, Tholakanahalli V. Mortality prediction using a modified Seattle Heart Failure Model may improve patient selection for ventricular tachycardia ablation. Am Heart J 2015;170:1099-104. [PMID: 26678631 DOI: 10.1016/j.ahj.2015.09.008] [Cited by in Crossref: 17] [Cited by in F6Publishing: 12] [Article Influence: 2.4] [Reference Citation Analysis]
29 Berezin AE, Kremzer AA, Martovitskaya YV, Samura TA, Berezina TA. The predictive role of circulating microparticles in patients with chronic heart failure. BBA Clin 2015;3:18-24. [PMID: 26672475 DOI: 10.1016/j.bbacli.2014.11.006] [Cited by in Crossref: 19] [Cited by in F6Publishing: 16] [Article Influence: 2.4] [Reference Citation Analysis]
30 Coles AH, Tisminetzky M, Yarzebski J, Lessard D, Gore JM, Darling CE, Goldberg RJ. Magnitude of and Prognostic Factors Associated With 1-Year Mortality After Hospital Discharge for Acute Decompensated Heart Failure Based on Ejection Fraction Findings. J Am Heart Assoc 2015;4:e002303. [PMID: 26702084 DOI: 10.1161/JAHA.115.002303] [Cited by in Crossref: 21] [Cited by in F6Publishing: 15] [Article Influence: 3.0] [Reference Citation Analysis]
31 Razaghizad A, Oulousian E, Randhawa VK, Ferreira JP, Brophy JM, Greene SJ, Guida J, Felker GM, Fudim M, Tsoukas M, Peters TM, Mavrakanas TA, Giannetti N, Ezekowitz J, Sharma A. Clinical Prediction Models for Heart Failure Hospitalization in Type 2 Diabetes: A Systematic Review and Meta‐Analysis. JAHA. [DOI: 10.1161/jaha.121.024833] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
32 Manlucu J, Sharma V, Koehler J, Warman EN, Wells GA, Gula LJ, Yee R, Tang AS. Incremental Value of Implantable Cardiac Device Diagnostic Variables Over Clinical Parameters to Predict Mortality in Patients With Mild to Moderate Heart Failure. J Am Heart Assoc 2019;8:e010998. [PMID: 31291801 DOI: 10.1161/JAHA.118.010998] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]
33 Salah K, Stienen S, Moons AHM, Bakx ALM, van Pol PE, Kortz RAM, Ferreira JP, Marques I, Schroeder-Tanka JM, Keijer JT, Bayes-Genis A, Pinto YM, Tijssen JG, Kok WE. External Validation of the ELAN-HF Score, Predicting 6-Month All-Cause Mortality in Patients Hospitalized for Acute Decompensated Heart Failure. J Am Heart Assoc 2019;8:e010309. [PMID: 31296084 DOI: 10.1161/JAHA.118.010309] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
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36 Borisenko O, Müller-Ehmsen J, Lindenfeld J, Rafflenbeul E, Hamm C. An early analysis of cost-utility of baroreflex activation therapy in advanced chronic heart failure in Germany. BMC Cardiovasc Disord 2018;18:163. [PMID: 30092774 DOI: 10.1186/s12872-018-0898-x] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
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38 Corrà U, Magini A, Paolillo S, Frigerio M. Comparison among different multiparametric scores for risk stratification in heart failure patients with reduced ejection fraction. Eur J Prev Cardiol 2020;27:12-8. [PMID: 33238734 DOI: 10.1177/2047487320962990] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
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40 Lanfear DE, Gibbs JJ, Li J, She R, Petucci C, Culver JA, Tang WHW, Pinto YM, Williams LK, Sabbah HN, Gardell SJ. Targeted Metabolomic Profiling of Plasma and Survival in Heart Failure Patients. JACC Heart Fail 2017;5:823-32. [PMID: 29096792 DOI: 10.1016/j.jchf.2017.07.009] [Cited by in Crossref: 34] [Cited by in F6Publishing: 26] [Article Influence: 8.5] [Reference Citation Analysis]
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42 Upshaw JN, Konstam MA, Klaveren Dv, Noubary F, Huggins GS, Kent DM. Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation. Circ Heart Fail 2016;9:e003146. [PMID: 27514751 DOI: 10.1161/CIRCHEARTFAILURE.116.003146] [Cited by in Crossref: 13] [Cited by in F6Publishing: 5] [Article Influence: 2.6] [Reference Citation Analysis]
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56 Ambardekar AV, Thibodeau JT, DeVore AD, Kittleson MM, Forde-McLean RC, Palardy M, Mountis MM, Cadaret L, Teuteberg JJ, Pamboukian SV, Xie R, Stevenson LW, Stewart GC. Discordant Perceptions of Prognosis and Treatment Options Between Physicians and Patients With Advanced Heart Failure. JACC Heart Fail 2017;5:663-71. [PMID: 28822745 DOI: 10.1016/j.jchf.2017.04.009] [Cited by in Crossref: 19] [Cited by in F6Publishing: 21] [Article Influence: 3.8] [Reference Citation Analysis]
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