ReviewReviews in cardiovascular medicine2025
Classification, Diagnosis, and Prognosis of Cardiomyopathy: A Comprehensive Narrative Review.
Review in Reviews in cardiovascular medicine, 2025. 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.
- Review
- The Impact of Risk Factors and Comorbidities on Heart Failure in the Aging Population.International journal of molecular sciences · 2026Review
- Autoantibody Profiling in Cardiomyopathies: Toward Immune-Guided Risk Stratification and Therapy.Journal of clinical medicine · 2026Review
- AI-Enabled Sensor Technologies for Remote Arrhythmic Monitoring in High-Risk Cardiomyopathy Genotypes.Sensors (Basel, Switzerland) · 2026Review
- Molecular Pathology of Cardiomyopathies: Bridging Morphology, Genomics, and Clinical Phenotypes.Current issues in molecular biology · 2026Review
- CardioVar: a machine learning framework for pathogenicity prediction of cardiomyopathy genetic variants.Bioinformatics advances · 2026Article
- HDAC5 Inhibition as a Therapeutic Strategy for Titin Deficiency-Induced Cardiac Remodeling: Insights from Human iPSC Models.Medicines (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiomyopathy denotes a group of heart diseases caused by structural or functional heart muscle disorders, with various genetic and non-genetic etiologies. Based on the current literature, this narrative review synthesizes key findings from available information on the classification, diagnosis, and prognosis of inherited or acquired cardiomyopathies. Following a different approach to prior systematic reviews, this study does not implement any formal inclusion or exclusion criteria or structured search strategy. However, this review does consider the evidence of influential studies, prominent cardiology guidelines, and expert consensuses to provide a comprehensive overview of recent advancements in the field. Further, explication is performed for the latest advances in genetic mutations, diagnostic imaging techniques, and therapeutic techniques. All diagnoses involve clinical presentations, imaging, and laboratory tests. Future research directions include personalized therapy, quantitative imaging techniques, and new drug treatments. This review highlights cardiomyopathy research by emphasizing the integration of precision medicine, advanced imaging, and molecular diagnostics. Future research on cardiomyopathy should include precision medicine and personalized therapies with an exhaustive integration of techniques and resources to catalyze further innovations in diagnostics and therapeutic approaches. Thus, this narrative review will provide clinicians and researchers with insight into the future of cardiomyopathy management by summarizing key developments and trends.
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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.