Regional Hospital of Godstrup
Herning, 7400, Denmark
NCT Number: NCT06708000
This study aims to assess whether the use of clinical risk models, known as Clinical Likelihood (CL) models, can reduce the need for diagnostic examinations without negatively impacting quality of life or prognosis after 12 months in patients with stable new onset chest pain. Additionally, the project will evaluate a newly developed method called Laser Speckle Contrast Imaging for measuring function and oxygen content in the smallest blood vessels (microvasculature) of the hand, which may also reflect blood flow and oxygen content in the microvasculature of the heart.
Interested in participating?
Request Info30 year–75 year
All sexes
Interventional
Phase 3
Herning, 7400, Denmark
Ischemic heart disease poses a significant burden on society and affects many Danes annually. With more than 300,000 citizens in Denmark living with cardiovascular disease, and more than 17,500 cardiovascular deaths annually, the need for effective diagnosis and treatment is crucial. Cardiac Computed Tomography Angiography (CCTA) has become an important tool in diagnosing arteriosclerotic obstructive coronary artery disease (CAD) in patients with typical or atypical chest pain, but the increasing use of this method requires a more efficient selection of patients before initial testing. Early and accurate risk stratification could improve patient management, reduce morbidity, and improve patient outcomes, highlighting the importance of optimizing diagnostic pathways.
At Gødstrup Hospital, novel clinical likelihood (CL) models have been developed to assess the pre-test probability of obstructive CAD. Based on sex, age, and symptom characteristics, and including traditional cardiovascular risk factors, the risk factor-weighted clinical likelihood (RF-CL) model improves discrimination of obstructive CAD and prognosis compared to traditional models. Additionally, the utilization of a coronary artery calcium score (CACS) in conjunction with the RF-CL model, i.e., the CACS-weighted clinical likelihood (CACS-CL) model, further enhances patient management in external validation cohorts. Recently, both CL models have been implemented in the European guidelines on CAD management. However, the CL models have only been applied in observational studies, and no randomized trials substantiate their use in clinical practice.
It is hypothesized that a diagnostic strategy based on an assessment including the CL models is non-inferior to the current standard strategy, as measured by the number of asymptomatic patients during follow-up. Secondly, it is assumed that the CL-based strategy reduces unnecessary diagnostic tests and improve resource utilization without compromising patient safety.
Emerging alongside these developments is Laser Speckle Contrast Imaging (LSCI), a promising non-invasive technique for assessing microvascular function. Several studies have suggested a link between reduced microcirculation in the skin and heart among patients with angina and non-significant calcification, compared to healthy controls. LSCI measures red blood cell movement to quantify blood flow, making it an effective, fast, and cost-efficient tool already in use in other medical fields. If a correlation between peripheral and cardiac microcirculation is established, LSCI could address a diagnostic gap in detecting microvascular dysfunction, particularly for angina patients without significant coronary calcification. Integrating LSCI into the diagnostic process offers potential to further refine patient selection for testing and provide more targeted diagnostic pathways.
This study will increase the evidence for utilizing the RF-CL and CACS-CL models in clinical practice. Currently, the use of pre-test likelihood models is only recommended with a IB recommendation and deferral of diagnostic testing in individuals with CL>=5% with IIa B recommendation due to a lack of randomized studies. The study will focus on symptomatic endpoints and investigate quality of life measurements in patients deferred for testing based on the CL estimation. Secondary endpoints include both effectiveness and safety metrics.
This project is an ambitious endeavor that builds on previous work performed within our research group. The supervisors are experienced researchers with substantial expertise in this area and conducting randomized studies. The findings from this study have the potential to significantly impact clinical practice by providing evidence-based recommendations (Level/Class of evidence 1A) for the use of CL models in the diagnostic pathway of ischemic heart disease.
By demonstrating that using the CL model in the management of patients with new-onset chest pain substantially and safely reduces the necessity for cardiac CT and other advanced diagnostic procedures, resource utilization could improve and costs be lowered for the healthcare system. Additionally, as tests could be deferred without compromising safety, patient-related quality of life could improve. Finally, the findings are expected to contribute to clinical guidelines and practices, benefiting the broader field of cardiology. By validating the CL models in a large, diverse patient population, this study could provide strong evidence for their broader implementation in clinical practice.
The incorporation of LSCI into this framework also presents an exciting avenue for further improving diagnostic precision. If LSCI can reliably identify microvascular dysfunction, it could serve as a complementary tool in optimizing diagnostic strategies, particularly for patients in whom obstructive CAD has been ruled out but who still experience angina-like symptoms.
If CL model utilization proves capable of safely reducing the necessity for CCTA and other advanced diagnostic procedures in patients with obstructive CAD, resource utilization could improve, lowering costs for the healthcare system while maintaining or enhancing patient quality of life.
The present research addresses a significant gap in current diagnostic strategies and has the potential to shift clinical practices towards more personalized and efficient care pathways for stable chest pain.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
The Clinical Likelihood (CL) model-based diagnostic strategy utilizes two models: the RF-CL model and the CACS-CL model. These models assess the pre-test probability of obstructive coronary artery disease (CAD) based on patient factors such as age, sex, symptoms, and traditional cardiovascular risk factors like smoking, diabetes, and hypertension. The CACS-CL model incorporates coronary artery calcium scoring to further refine the risk assessment. Patients identified with a low likelihood of CAD may avoid unnecessary diagnostic testing, such as cardiac CT, while maintaining diagnostic accuracy and safety. This approach aims to optimize resource use, reduce patient burden, and focus on other potential causes of symptoms when CAD is unlikely.
Patients will follow the standard diagnostic pathway, which includes the use of cardiac CT and other advanced diagnostic procedures based on clinical guidelines. This approach is the current standard of care for patients with suspected obstructive coronary artery disease (CAD). The control group allows for comparison of outcomes with those in the intervention arm, particularly in terms of resource utilization, patient safety, and diagnostic accuracy.
Time frame: From enrollment to 6 months after patient inclusion
Resolution 6 months after inclusion, as assessed by SAQ Angina Frequency score of 100%, indicating the absence of angina-related symptoms. This measure will assess the effectiveness of a diagnostic strategy based on Clinical Likelihood (CL) models compared to the standard approach for evaluating patients suspected of stable ischemic heart disease (IHD).
Time frame: From enrollment to 12 months after patient inclusion.
The study aims to evaluate the diagnostic accuracy of the CL-based strategy in detecting obstructive coronary artery disease (CAD) compared to the standard approach. The key metrics include sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). These outcomes will be aggregated and reported as percentages to assess the effectiveness of the diagnostic pathway.
Time frame: From enrollment to 12 months after patient inclusion
This measure evaluates the change in the proportion of patients who undergo cardiac CT imaging when managed with the Clinical Likelihood (CL)-based diagnostic strategy compared to the standard approach. The primary metric is the percentage of enrolled patients receiving cardiac CT scans during the diagnostic process. Data will be collected from diagnostic records and pathways utilized during patient care.
Time frame: 3, 6, and 12 months after enrollment
This outcome evaluates angina-specific quality of life using the Seattle Angina Questionnaire (SAQ). The SAQ assesses multiple domains, including physical limitation, angina stability, angina frequency, treatment satisfaction, and disease perception. Scores range from 0 to 100 for each domain, with higher scores indicating better quality of life. Data will be collected at three time points to track changes in symptoms and their impact on daily activities.
Time frame: 3, 6 and 12 months after enrollment
This outcome measures dyspnea severity using the Rose Dyspnea Score. The Rose Dyspnea Score assesses the impact of dyspnea on physical activity. Scores range from 0 to 4, with higher scores indicating worse symptoms.
Time frame: At baseline and 6 months after enrollement
This outcome will assess whether Laser Speckle Contrast Imaging (LSCI) can reliably detect microvascular dysfunction by evaluating the correlation between peripheral microvascular function (measured through LSCI) and cardiac microvascular function. The goal is to determine if LSCI can serve as a diagnostic tool for microvascular dysfunction in patients with chest pain, particularly those without significant coronary artery calcification. The outcome will examine the effectiveness of LSCI in identifying patients with potential microvascular dysfunction and explore its role in improving diagnostic accuracy.
Time frame: 10 years
This outcome will assess whether the implementation of CL models impacts long-term prognosis. Prognosis will be assessed based on cardiovascular events and overall health status.
Time frame: Baseline
The number of patients who, at baseline, have a very low risk according to the RF-CL (≤5%) and CACS-CL (≤5%) models for significant coronary artery disease (CAD).
Time frame: 3, 6, and 12 months after enrollment
Proportion of patients with very low RF-CL who require further diagnostic testing due to ongoing symptoms of angina pectoris and dyspnea.
Time frame: Baseline
The proportion of patients undergoing cardiac CT scans that show no significant findings, indicating no substantial coronary artery disease.
Time frame: 3, 6, and 12 months after enrollment
The number of myocardial perfusion scans performed that reveal no significant findings.
Time frame: 3, 6, and 12 months after enrollment
The number of invasive coronary angiograms that show no significant coronary artery disease, relative to the total number performed.
Time frame: 6 months after enrollment
Proportion of patients prescribed preventive medications, including statins and anti-hypertensive drugs, to manage cardiovascular risk.
Time frame: 1, 5 and 10 years after enrollment
The proportion of patients undergoing revascularization procedures, including percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG).
Time frame: 12 months
Economic analysis of the cost of care, including medication, clinic visits, and diagnostic tests over the 12-month follow-up period.
Time frame: 6 months after enrollment
Identification of patients with microvascular or spasm angina who continue to experience symptoms despite standard anti-anginal treatment.
Time frame: 10 years after enrollment
Exploration of the utility of genetic and proteomic models to enhance patient stratification for cardiovascular disease risk and treatment response.
Time frame: 6, 12, 36, and 120 months after enrollment
The number of deaths and acute myocardial infarctions recorded over the follow-up period.
Time frame: 3, 6, and 12 months after enrollment
This outcome assesses the utility of the Work Ischemic Symptom Score (WISS) in evaluating ischemic symptoms and overall symptom burden in patients with new-onset chest pain. The WISS captures patient-reported data on the frequency and severity of chest discomfort and shortness of breath during varying levels of physical activity (e.g., heavy, moderate, light, or at rest). Responses will be analyzed to identify patterns of symptom burden and their correlation with clinical outcomes.
Time frame: Up to 10 years after enrollement
This measure evaluates the concentration of proteomic biomarkers in blood samples and their correlation with the extent of heart disease observed via cardiac CT. Proteomic biomarkers will be quantified (e.g., ng/mL) and analyzed for associations with imaging findings. Results will provide insights into the biological mechanisms of heart disease.
Time frame: Up to 10 years after enrollement
This measure assesses metabolomic biomarkers in blood samples to evaluate their correlation with patient prognosis, including outcomes such as symptom progression or adverse cardiovascular events. Biomarker concentrations will be reported in standardized units (e.g., µmol/L) and analyzed over time.
Gødstrup Hospital
Other
Personalized Evaluation of Suspected Myocardial Ischemia
Acronym: PERMI
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