Key result
AI phenotype mapping in HFpEF categorizes patients into mutually exclusive phenogroups for targeted therapies.
Phenotype mapping using artificial intelligence may help categorize the heterogeneous HFpEF syndrome into distinct phenogroups to guide specific therapeutic strategies.
AI phenogrouping in HFpEF remains hypothesis-generating; prospective validation required before guiding therapy.
Heart failure with preserved ejection fraction (HFPEF) has become the main phenotypic model of heart failure (HF) in community and referral patients in Brazil and in the world. Despite advances in the development of new drugs for HF treatment, there has been no significant improvement in mortality of this condition. According to many studies, this can be explained by the heterogeneous nature of HF physiopathology, whose basic mechanisms may result in different clinical presentations, culminating in the emerging of different phenogroups in this syndrome. In this context, phenotype mapping of HFPEF has emerged as a possible solution, since it enables the development of clinical trials that establish specific therapeutic strategies for each phenotypic profile. New technologies in the field of artificial intelligence have enabled the assessment of a large volume of data and infer intrinsic patterns and different outcomes. Thereby, it is possible to obtain mutually exclusive categories of HFPEF, with a phenotype mapping of the syndrome and grouping of patients according to their phenotypic features. Besides, other diseases can have the same clinical phenotype but different pathophysiological basis, the so called “phenocopies”. These tools enable the analysis and categorization of the wide spectrum of heart failure, contributing to solve the dilemmas of the treatment of this syndrome.
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Mesquita et al. (2018) conducted a review in Heart failure with preserved ejection fraction (HFPEF). Phenotype mapping using artificial intelligence was evaluated. Phenotype mapping of heart failure with preserved ejection fraction using artificial intelligence enables the categorization of patients into mutually exclusive phenogroups for targeted therapies.
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