Maria Toumpourleka, Dimitrios Patoulias, Alexandra Katsimardou, Michael Doumas* and Christodoulos Papadopoulos Pages 1 - 10 ( 10 )
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, 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.
heart failure, heart failure with reduced ejection fraction, prediction score, prediction model
Third Department of Cardiology, Aristotle University, Thessaloniki, 2 nd Propedeutic Department of Internal Medicine, Aristotle University, Thessaloniki, 2 nd Propedeutic Department of Internal Medicine, Aristotle University, Thessaloniki, VA Medical Center and George Washington University, Washington, DC, Third Department of Cardiology, Aristotle University, Thessaloniki