ArticleClinical and translational science2021
Performance of Plasma Adenosine as a Biomarker for Predicting Cardiovascular Risk.
Article in Clinical and translational science, 2021. 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, 9 citations in OpenAlex.
- Development of Optical-Based Molecularly Imprinted Nanosensors for Adenosine Detection.ACS omega · 2023Article
- Dipyridamole and vascular healing following stent implantation.Frontiers in cardiovascular medicine · 2023Article
- Modifiable Risk Factors and Residual Risk Following Coronary Revascularization: Insights From a Regionalized Dedicated Follow-Up Clinic.Mayo Clinic proceedings. Innovations, quality & outcomes · 2021Article
- ADA gene haplotype is associated with coronary-in-stent-restenosis.Molecular biology reports · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors at 3 institutions in 3 countries.
Funding
Abstract
Adenosine boasts promising preclinical and clinical data supporting a vital role in modulating vascular homeostasis. Its widespread use as a diagnostic and therapeutic agent have been limited by its short half-life and complex biology, though adenosine-modulators have shown promise in improving vascular healing. Moreover, circulating adenosine has shown promise in predicting cardiovascular (CV) events. We sought to delineate whether circulating plasma adenosine levels predict CV events in patients undergoing invasive assessment for coronary artery disease. Patients undergoing invasive angiography had clinical data prospectively recorded in the Cardiovascular and Percutaneous ClInical TriALs (CAPITAL) revascularization registry and blood samples collected in the CAPITAL Biobank from which adenosine levels were quantified. Tertile-based analysis was used to assess prediction of major adverse cardiovascular events (MACE; composite of death, myocardial infarction, unplanned revascularization, and cerebrovascular accident). Secondary analyses included MACE subgroups, clinical subgroups and adenosine levels. There were 1,815 patients undergoing angiography who had blood collected with adenosine quantified in 1,323. Of those quantified, 51.0% were revascularized and 7.3% experienced MACE in 12 months of follow-up. Tertile-based analysis failed to demonstrate any stratification of MACE rates (log rank, P = 0.83), when comparing low-to-middle (hazard ratio (HR) 1.10, 95% confidence interval (CI) 0.68-1.78, P = 0.70) or low-to-high adenosine tertiles (HR 0.95, 95% CI 0.56-1.57, P = 0.84). In adjusted analysis, adenosine similarly failed to predict MACE. Finally, adenosine did not predict outcomes in patients with acute coronary syndrome nor in those revascularized or treated medically. Plasma adenosine levels do not predict subsequent CV outcomes or aid in patient risk stratification.
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.