ReviewPharmacology & therapeutics2017
Current state of the art for cardiac arrhythmia gene therapy.
Review in Pharmacology & therapeutics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed, 18 citations in OpenAlex.
- Gene therapy for atrial fibrillation.Journal of molecular and cellular cardiology · 2024Review
- A Comprehensive Analysis of Conventional Acupuncture and Pharmacological Approaches for Cardiac Arrhythmias: An Umbrella Review.The Journal of innovations in cardiac rhythm management · 2024Review
- Exploration of Mechanisms of Sacubitril/Valsartan in the Treatment of Cardiac Arrhythmias Using a Network Pharmacology Approach.Frontiers in cardiovascular medicine · 2022Article
- Acupuncture as an adjunctive therapy for arrhythmia: a Delphi expert consensus survey.Cardiovascular diagnosis and therapy · 2021Article
- Recent advances in gene therapy for atrial fibrillation.Journal of cardiovascular electrophysiology · 2021Review
- Regulatory mechanism of calcium/calmodulin-dependent protein kinase II in the occurrence and development of ventricular arrhythmia (Review).Experimental and therapeutic medicine · 2021Review
- Big Data and Atrial Fibrillation: Current Understanding and New Opportunities.Journal of cardiovascular translational research · 2020Review
- Translational Models of Arrhythmia Mechanisms and Susceptibility: Success and Challenges of Modeling Human Disease.Frontiers in cardiovascular medicine · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Cardiac arrhythmias are a leading cause of morbidity and mortality. Currently available therapeutic options lack sufficient efficacy and safety. Gene therapy has been proposed for treatment of cardiac arrhythmias. This review will discuss the current state of development for arrhythmia gene therapy. So far, all published studies are short-term, proof-of-concept animal studies. Potential replacement of cardiac pacemakers has been shown for combination gene therapy using the HCN2 gene and either the gene for adenylate cyclase, the skeletal muscle isoform of the sodium channel, or a dominant negative mutant of the potassium channel responsible for resting membrane potential. Atrial fibrillation has been prevented by gene transfer of either a dominant negative mutant of a repolarizing potassium channel, a gap junction, or an siRNA directed against caspase 3. Inherited arrhythmia syndromes have been corrected by replacement of the causative genes. Post-infarct ventricular tachycardia has been reduced by gene therapy with the skeletal muscle sodium channel and connexins and eliminated with the dominant negative mutant of the potassium channel responsible for resting membrane potential. These ideas show considerable promise. Long-term efficacy and safety studies are required to see if they can become viable therapies.
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.