ArticleCurrent treatment options in cardiovascular medicine2012
Adenosine stress cardiovascular magnetic resonance-observation unit management of patients at intermediate risk for acute coronary syndrome: a possible strategy for reducing healthcare-related costs.
Article in Current treatment options in cardiovascular medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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
2 citing papers in PubMed, 5 citations in OpenAlex.
- Cardiac magnetic resonance and computed tomography angiography for clinical imaging of stable coronary artery disease. Diagnostic classification and risk stratification.Frontiers in physiology · 2014Review
- Emergency department observation units and the older patient.Clinics in geriatric medicine · 2013Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
opinion statementAlthough clear algorithms for diagnosis and treatment of patients with chest pain at low or high risk for an acute coronary syndrome (ACS) exist, they are less well delineated for patients presenting with chest pain with an intermediate risk for ACS. In patients presenting acutely or subacutely to emergency departments (EDs) at high risk for ACS, such as those with ST segment elevation on their 12-lead electrocardiogram (ECG), immediate contrast coronary angiography is performed. On the other hand, chest pain observation units (OUs) are recommended for managing those with chest pain at low risk for an ACS event. In this setting, these OUs are associated with lower healthcare resource utilization and improved cost-effectiveness. Cost-effective diagnosis and treatment options are important goals in healthcare delivery systems. The presentation of patients at intermediate risk for ACS represents an emerging source of resource utilization for EDs. These patients often exhibit pre-existing coronary artery disease, may have sustained prior myocardial infarction, and exhibit multiple comorbidities such as diabetes and hypercholesterolemia. Importantly, however, they will not have evidence of ST elevation on their 12-lead ECG nor will they exhibit serum markers (troponin or creatinine kinase elevations) indicative of ACS. As a consequence of existing co-morbidities, their management becomes time-consuming and may require inpatient monitoring, observation, and cardiac stress testing. Cardiovascular magnetic resonance (CMR) is a powerful tool for risk stratification and prognosis determination in patients in need of stress testing at intermediate risk of ACS. For those who present with acute chest pain syndromes, the combination of CMR in an OU setting represents a potentially attractive option for reducing healthcare-related expenditures without compromising patient outcomes. Recent study results from single centers suggest that CMR-OU care may result in fewer unnecessary hospital admissions and invasive procedures in those presenting with intermediate risk ACS. Further research utilizing stress CMR testing from multiple centers in OU settings is needed to determine if this model of care improves efficiency, reduces healthcare costs, and delivers optimum care in individuals presenting to EDs with chest pain at intermediate risk of ACS.
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.