ArticleBMJ open2020
Cardiovascular imaging of women and men visiting the outpatient clinic with chest pain or discomfort: design and rationale of the ARGUS Study.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04682756 (A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model), which is not on this map. Cited by 4 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.
A Multicenter Study on Early Diagnosis of NSTE-ACS Patients Based on Machine Learning Model
Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Cardiac Magnetic Resonance Imaging (CMRI) Applications in Patients with Chest Pain in the Emergency Department: A Narrative Review.Diagnostics (Basel, Switzerland) · 2023Review
- Machine learning approaches that use clinical, laboratory, and electrocardiogram data enhance the prediction of obstructive coronary artery disease.Scientific reports · 2023Article
- Preventing unnecessary imaging in patients suspect of coronary artery disease through machine learning of electronic health records.European heart journal. Digital health · 2022Article
- Artificial Intelligence-A Good Assistant to Multi-Modality Imaging in Managing Acute Coronary Syndrome.Frontiers in cardiovascular medicine · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionChest pain or discomfort affects 20%-40% of the general population over the course of their life and may be a symptom of myocardial ischaemia. For the diagnosis of obstructive macrovascular coronary artery disease (CAD), algorithms have been developed; however, these do not exclude microvascular angina. This may lead to false reassurance of symptomatic patients, mainly women, with functionally significant, yet non-obstructive coronary vascular disease. Therefore, this study aims to estimate the prevalence of both macrovascular and microvascular coronary vascular disease in women and men presenting with chest pain or discomfort, and to subsequently develop a decision-support tool to aid cardiologists in referral to cardiovascular imaging for both macrovascular and microvascular CAD evaluation. METHODS AND ANALYSIS: Women and men with chest pain or discomfort, aged 45 years and older, without a history of cardiovascular disease, who are referred to an outpatient cardiology clinic by their general practitioner are eligible for inclusion. Coronary CT angiography is used for anatomical imaging. Additionally, myocardial perfusion imaging by adenosine stress cardiac MRI is performed to detect functionally significant coronary vascular disease. Electronic health record data, collected during regular cardiac work-up, including medical history, cardiovascular risk factors, physical examination, echocardiography, (exercise) ECG and blood samples for standard cardiovascular biomarkers and research purposes, are obtained. Participants will be classified as positive or negative for coronary vascular disease based on all available data by expert panel consensus (a cardiovascular radiologist and two cardiologists). After completion of the clinical study, all collected data will be used to develop a decision support tool using predictive modelling and machine-learning techniques. ETHICS AND DISSEMINATION: The study protocol was approved by the Institutional Review Board of the University Medical Center Utrecht. Results will be disseminated through national and international conferences and in peer-reviewed journals in cardiovascular disease. TRIAL REGISTRATION NUMBER: Trialregister.nl Registry NL8702.
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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.