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Current Pharmaceutical Design

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ISSN (Print): 1381-6128
ISSN (Online): 1873-4286

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Review Article

Risk Scores and Prediction Models in Chronic Heart Failure: A Comprehensive Review

Author(s): Maria Toumpourleka, Dimitrios Patoulias, Alexandra Katsimardou, Michael Doumas* and Christodoulos Papadopoulos

Volume 27, Issue 10, 2021

Published on: 21 May, 2020

Page: [1289 - 1297] Pages: 9

DOI: 10.2174/1381612826666200521141249

Price: $65

Abstract

Background: Heart failure affects a substantial proportion of the adult population, with an estimated prevalence of 1-2% in developed countries. Over the previous decades, many prediction models have been introduced for this specific population in an attempt to better stratify and manage heart failure patients.

Objective: The aim of this study is the systematic review of recent, relevant literature regarding risk scores or prediction models in ambulatory patients with an established diagnosis of chronic heart failure.

Methods: We conducted a systematic search of the literature in PubMed and CENTRAL from their inception up till December 2019 for studies assessing the performance of risk scores and prediction models and original research studies. Grey literature was searched as well. This review is reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement.

Results: We included 16 eligible studies in this systematic review. Major heart failure risk scores derived from large heart failure populations were among the included studies. Due to significant heterogeneity regarding the main endpoints, a direct comparison of the included prediction scores was inevitable. The majority referred to patients with heart failure with reduced ejection fraction, while only two out of 16 prediction scores have been developed exclusively for heart failure patients with preserved ejection fraction. Ischemic heart disease was the most common aetiology of heart failure in the included studies. Finally, more than half of the prediction scores have not been externally validated.

Conclusion: Prediction models aiming at heart failure patients with a preserved or mid-range ejection fraction are lacking. Prediction scores incorporating recent advances in pharmacotherapy should be developed in the future.

Keywords: Heart failure, heart failure with reduced ejection fraction, prediction score, prediction model, chronic, prediction models.

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[1]
Ponikowski P, Voors AA, Anker SD, et al. ESC Scientific Document Group. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016; 37(27): 2129-200.
[http://dx.doi.org/10.1093/eurheartj/ehw128] [PMID: 27206819]
[2]
Bleumink GS, Knetsch AM, Sturkenboom MCJM, et al. Quantifying the heart failure epidemic: prevalence, incidence rate, lifetime risk and prognosis of heart failure The Rotterdam Study. Eur Heart J 2004; 25(18): 1614-9.
[http://dx.doi.org/10.1016/j.ehj.2004.06.038] [PMID: 15351160]
[3]
Conrad N, Judge A, Tran J, et al. Temporal trends and patterns in heart failure incidence: a population-based study of 4 million individuals. Lancet 2018; 391(10120): 572-80.
[http://dx.doi.org/10.1016/S0140-6736(17)32520-5] [PMID: 29174292]
[4]
Cook C, Cole G, Asaria P, Jabbour R, Francis DP. The annual global economic burden of heart failure. Int J Cardiol 2014; 171(3): 368-76.
[http://dx.doi.org/10.1016/j.ijcard.2013.12.028] [PMID: 24398230]
[5]
Maggioni AP, Dahlström U, Filippatos G, et al. Heart Failure Association of the European Society of Cardiology (HFA). EURObservational Research Programme: regional differences and 1-year follow-up results of the Heart Failure Pilot Survey (ESC-HF Pilot). Eur J Heart Fail 2013; 15(7): 808-17.
[http://dx.doi.org/10.1093/eurjhf/hft050] [PMID: 23537547]
[6]
Tsao CW, Lyass A, Enserro D, et al. Temporal trends in the incidence of and mortality associated with heart failure with preserved and reduced ejection fraction. JACC Heart Fail 2018; 6(8): 678-85.
[http://dx.doi.org/10.1016/j.jchf.2018.03.006] [PMID: 30007560]
[7]
Owan TE, Hodge DO, Herges RM, Jacobsen SJ, Roger VL, Redfield MM. Trends in prevalence and outcome of heart failure with preserved ejection fraction. N Engl J Med 2006; 355(3): 251-9.
[http://dx.doi.org/10.1056/NEJMoa052256] [PMID: 16855265]
[8]
Gerber Y, Weston SA, Redfield MM, et al. A contemporary appraisal of the heart failure epidemic in Olmsted County, Minnesota, 2000 to 2010. JAMA Intern Med 2015; 175(6): 996-1004.
[http://dx.doi.org/10.1001/jamainternmed.2015.0924] [PMID: 25895156]
[9]
Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. 2nd ed. New York: Springer 2019.
[http://dx.doi.org/10.1007/978-3-030-16399-0]
[10]
Laupacis A, Sekar N, Stiell IG. Clinical prediction rules. A review and suggested modifications of methodological standards. JAMA 1997; 277(6): 488-94.
[http://dx.doi.org/10.1001/jama.1997.03540300056034] [PMID: 9020274]
[11]
Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009; 339: b2535.
[http://dx.doi.org/10.1136/bmj.b2535] [PMID: 19622551]
[12]
McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. J Clin Epidemiol 2016; 75: 40-6.
[http://dx.doi.org/10.1016/j.jclinepi.2016.01.021] [PMID: 27005575]
[13]
Hayden JA, van der Windt DA, Cartwright JL, Côté P, Bombardier C. Assessing bias in studies of prognostic factors. Ann Intern Med 2013; 158(4): 280-6.
[http://dx.doi.org/10.7326/0003-4819-158-4-201302190-00009] [PMID: 23420236]
[14]
Levy WC, Mozaffarian D, Linker DT, et al. The Seattle Heart Failure Model: prediction of survival in heart failure. Circulation 2006; 113(11): 1424-33.
[http://dx.doi.org/10.1161/CIRCULATIONAHA.105.584102] [PMID: 16534009]
[15]
Pocock SJ, Wang D, Pfeffer MA, et al. Predictors of mortality and morbidity in patients with chronic heart failure. Eur Heart J 2006; 27(1): 65-75.
[http://dx.doi.org/10.1093/eurheartj/ehi555] [PMID: 16219658]
[16]
Pocock SJ, Ariti CA, McMurray JJ, et al. Meta-analysis global group in chronic heart failure. Predicting survival in heart failure: a risk score based on 39 372 patients from 30 studies. Eur Heart J 2013; 34(19): 1404-13.
[http://dx.doi.org/10.1093/eurheartj/ehs337] [PMID: 23095984]
[17]
Barlera S, Tavazzi L, Franzosi MG, et al. GISSI-HF Investigators. Predictors of mortality in 6975 patients with chronic heart failure in the Gruppo Italiano per lo Studio della Streptochinasi nell’Infarto Miocardico-Heart Failure trial: proposal for a nomogram. Circ Heart Fail 2013; 6(1): 31-9.
[http://dx.doi.org/10.1161/CIRCHEARTFAILURE.112.967828] [PMID: 23152490]
[18]
Agostoni P, Corrà U, Cattadori G, et al. MECKI Score Research Group. Metabolic exercise test data combined with cardiac and kidney indexes, the MECKI score: a multiparametric approach to heart failure prognosis. Int J Cardiol 2013; 167(6): 2710-8.
[http://dx.doi.org/10.1016/j.ijcard.2012.06.113] [PMID: 22795401]
[19]
O’Connor CM, Whellan DJ, Wojdyla D, et al. Factors related to morbidity and mortality in patients with chronic heart failure with systolic dysfunction: the HF-ACTION predictive risk score model. Circ Heart Fail 2012; 5(1): 63-71.
[http://dx.doi.org/10.1161/CIRCHEARTFAILURE.111.963462] [PMID: 22114101]
[20]
Collier TJ, Pocock SJ, McMurray JJ, et al. The impact of eplerenone at different levels of risk in patients with systolic heart failure and mild symptoms: insight from a novel risk score for prognosis derived from the EMPHASIS-HF trial. Eur Heart J 2013; 34(36): 2823-9.
[http://dx.doi.org/10.1093/eurheartj/eht247] [PMID: 23864130]
[21]
Wedel H, McMurray JJ, Lindberg M, et al. CORONA Study Group. Predictors of fatal and non-fatal outcomes in the Controlled Rosuvastatin Multinational Trial in Heart Failure (CORONA): incremental value of apolipoprotein A-1, high-sensitivity C-reactive peptide and N-terminal pro B-type natriuretic peptide. Eur J Heart Fail 2009; 11(3): 281-91.
[http://dx.doi.org/10.1093/eurjhf/hfn046] [PMID: 19168876]
[22]
Álvarez-García J, Ferrero-Gregori A, Puig T, et al. investigators of the Spanish Heart Failure Network (REDINSCOR). A simple validated method for predicting the risk of hospitalization for worsening of heart failure in ambulatory patients: the Redin-SCORE. Eur J Heart Fail 2015; 17(8): 818-27.
[http://dx.doi.org/10.1002/ejhf.287] [PMID: 26011392]
[23]
Senni M, Parrella P, De Maria R, et al. Predicting heart failure outcome from cardiac and comorbid conditions: the 3C-HF score. Int J Cardiol 2013; 163(2): 206-11.
[http://dx.doi.org/10.1016/j.ijcard.2011.10.071] [PMID: 22130225]
[24]
Vazquez R, Bayes-Genis A, Cygankiewicz I, et al. MUSIC Investigators. The MUSIC Risk score: a simple method for predicting mortality in ambulatory patients with chronic heart failure. Eur Heart J 2009; 30(9): 1088-96.
[http://dx.doi.org/10.1093/eurheartj/ehp032] [PMID: 19240065]
[25]
Kasahara S, Sakata Y, Nochioka K, et al. The 3A3B score: The simple risk score for heart failure with preserved ejection fraction - A report from the CHART-2 Study. Int J Cardiol 2019; 284: 42-9.
[http://dx.doi.org/10.1016/j.ijcard.2018.10.076] [PMID: 30413304]
[26]
Komajda M, Carson PE, Hetzel S, et al. Factors associated with outcome in heart failure with preserved ejection fraction: findings from the Irbesartan in Heart Failure with Preserved Ejection Fraction Study (I-PRESERVE). Circ Heart Fail 2011; 4(1): 27-35.
[http://dx.doi.org/10.1161/CIRCHEARTFAILURE.109.932996] [PMID: 21068341]
[27]
Carluccio E, Dini FL, Biagioli P, et al. The ‘Echo Heart Failure Score’: an echocardiographic risk prediction score of mortality in systolic heart failure. Eur J Heart Fail 2013; 15(8): 868-76.
[http://dx.doi.org/10.1093/eurjhf/hft038] [PMID: 23512095]
[28]
Xanthopoulos A, Tryposkiadis K, Giamouzis G, et al. Larissa Heart Failure Risk Score: a proposed simple score for risk stratification in chronic heart failure. Eur J Heart Fail 2018; 20(3): 614-6.
[http://dx.doi.org/10.1002/ejhf.1132] [PMID: 29271552]
[29]
Zafrir B, Goren Y, Paz H, et al. Risk score model for predicting mortality in advanced heart failure patients followed in a heart failure clinic. Congest Heart Fail 2012; 18(5): 254-61.
[http://dx.doi.org/10.1111/j.1751-7133.2012.00286.x] [PMID: 22994439]
[30]
Moons KGM, Kengne AP, Woodward M, et al. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker. Heart 2012; 98(9): 683-90.
[http://dx.doi.org/10.1136/heartjnl-2011-301246] [PMID: 22397945]
[31]
McMurray JJV, Packer M, Desai AS, et al. PARADIGM-HF Investigators and Committees. Angiotensin-neprilysin inhibition versus enalapril in heart failure. N Engl J Med 2014; 371(11): 993-1004.
[http://dx.doi.org/10.1056/NEJMoa1409077] [PMID: 25176015]
[32]
McMurray JJV, Solomon SD, Inzucchi SE, et al. DAPA-HF Trial Committees and Investigators. Dapagliflozin in patients with heart failure and reduced ejection fraction. N Engl J Med 2019; 381(21): 1995-2008.
[http://dx.doi.org/10.1056/NEJMoa1911303] [PMID: 31535829]
[33]
Rahimi K, Bennett D, Conrad N, et al. Risk prediction in patients with heart failure: a systematic review and analysis. JACC Heart Fail 2014; 2(5): 440-6.
[http://dx.doi.org/10.1016/j.jchf.2014.04.008] [PMID: 25194291]
[34]
Canepa M, Fonseca C, Chioncel O, et al. ESC HF long term registry investigators. Performance of prognostic risk scores in chronic heart failure patients enrolled in the european society of cardiology heart failure long-term registry. JACC Heart Fail 2018; 6(6): 452-62.
[http://dx.doi.org/10.1016/j.jchf.2018.02.001] [PMID: 29852929]
[35]
Sahlollbey N, Lee CKS, Shirin A, Joseph P. The impact of palliative care on clinical and patient-centred outcomes in patients with advanced heart failure: a systematic review of randomized controlled trials. Eur J Heart Fail 2020; 22(12)
[http://dx.doi.org/10.1002/ejhf.1783] [PMID: 32176831]
[36]
Howlett JG. Should we perform a heart failure risk score? Circ Heart Fail 2013; 6(1): 4-5.
[http://dx.doi.org/10.1161/CIRCHEARTFAILURE.112.973172] [PMID: 23322877]

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