Literature DB >> 32436819

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

Maria Toumpourleka1, Dimitrios Patoulias2, Alexandra Katsimardou2, Michael Doumas3, Christodoulos Papadopoulos1.   

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. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

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

Year:  2021        PMID: 32436819     DOI: 10.2174/1381612826666200521141249

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  3 in total

1.  Role of depressive symptoms in the prognosis of heart failure and its potential clinical predictors.

Authors:  Jiahao Duan; Kai Huang; Xinying Zhang; Ruting Wang; Zijun Chen; Zifeng Wu; Chaoli Huang; Chun Yang; Ling Yang
Journal:  ESC Heart Fail       Date:  2022-05-27

2.  Structured, Harmonized, and Interoperable Integration of Clinical Routine Data to Compute Heart Failure Risk Scores.

Authors:  Kim K Sommer; Ali Amr; Udo Bavendiek; Felix Beierle; Peter Brunecker; Henning Dathe; Jürgen Eils; Maximilian Ertl; Georg Fette; Matthias Gietzelt; Bettina Heidecker; Kristian Hellenkamp; Peter Heuschmann; Jennifer D E Hoos; Tibor Kesztyüs; Fabian Kerwagen; Aljoscha Kindermann; Dagmar Krefting; Ulf Landmesser; Michael Marschollek; Benjamin Meder; Angela Merzweiler; Fabian Prasser; Rüdiger Pryss; Jendrik Richter; Philipp Schneider; Stefan Störk; Christoph Dieterich
Journal:  Life (Basel)       Date:  2022-05-18

3.  Analysis of the Application Effect of Multidisciplinary Team Cooperation Model in Chronic Heart Failure under WeChat Platform.

Authors:  Jieyu Huang; Yu Su; Xiucai Mao
Journal:  Comput Intell Neurosci       Date:  2022-08-25
  3 in total

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