ReviewCirculation journal : official journal of the Japanese Circulation Society2021
Endotyping in Heart Failure - Identifying Mechanistically Meaningful Subtypes of Disease.
Review in Circulation journal : official journal of the Japanese Circulation Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- The Relationship between Angiotensin-Neprilysin Treatment, Echocardiographic Parameters, and NT-proBNP Levels in HFpEF Patients with Acute Decompensated Heart Failure.Computational and mathematical methods in medicine · 2022Trial
- Molecular Mechanisms and Multi-Omics Integration in Heart Failure: From Pathophysiology to Precision Medicine.International journal of molecular sciences · 2026Review
- Non-coding RNA-driven cardiovascular immunometabolic reprogramming: from inflammatory endotypes to therapeutic opportunities.Frontiers in cell and developmental biology · 2026Review
- Sendotypes predict worsening renal function in chronic kidney disease patients.Clinical and translational medicine · 2025Article
- Comprehensive Transcriptomics Profiling of MicroRNA Reveals Plasma Circulating Biomarkers of Hypertrophic Cardiomyopathy and Dysregulated Signaling Pathways.Circulation. Heart failure · 2023Article
- Connections for Matters of the Heart: Network Medicine in Cardiovascular Diseases.Frontiers in cardiovascular medicine · 2022Review
- Machine Learning on Prediagnostic Metabolite Data Identifies Etiologic Endotypes of Exfoliation Glaucoma in United States Health Professionals.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics. The derivation of these HF endotypes has important implications in promoting individualized treatment and facilitating more targeted selection of patients for clinical trials, as well as in potentially revealing new pathways of disease that may serve as therapeutic targets. One challenge in the integrated analysis of high-throughput omics and detailed clinical data is that it requires the ability to handle "big data", a task for which machine learning is well suited. In particular, unsupervised machine learning has the ability to uncover novel endotypes of disease in an unbiased approach. In this review, we will discuss recent efforts to identify HF endotypes and cover approaches involving proteomics, transcriptomics, and genomics, with a focus on machine-learning methods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.