ArticleNature reviews. Cardiology2017
Role of microRNAs in wasting in heart failure.
Article in Nature reviews. Cardiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 5 citations in OpenAlex.
- Non-coding RNA basis of muscle atrophy.Molecular therapy. Nucleic acids · 2021Review
- Angiotensin II-induced muscle atrophy via PPARγ suppression is mediated by miR-29b.Molecular therapy. Nucleic acids · 2021Article
- Alteration in the expression of the renin-angiotensin system in the myocardium of mice conceived by in vitro fertilization.Biology of reproduction · 2018Article
- Muscle wasting and sarcopenia in heart failure: a brief overview of the current literature.ESC heart failure · 2018Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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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.