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Testing Acetylcholine Followed by Adenosine for Invasive Diagnosis of Coronary Vasomotor Disorders
Published on: February 3, 2021
Optimal Use of Vasodilators for Diagnosis of Microvascular Angina in the Cardiac Catheterization Laboratory
Haseeb Rahman1, Ozan M Demir1, Matthew Ryan1
1School of Cardiovascular Medicine and Sciences, British Heart Foundation Centre of Excellence and National Institute for Health Research Biomedical Research Centre (H.R., O.M.D., M.R., H.M., H.E., A.W., D.P.), King's College London, United Kingdom.
Insights
Patients with angina and nonobstructive coronary artery disease benefit from assessing coronary microvascular dysfunction. Optimal thresholds for adenosine and acetylcholine flow reserve identify ischemia, guiding diagnosis and treatment for better outcomes.
Area of Science:
- Cardiology
- Vascular Medicine
- Diagnostic Imaging
Background:
- Coronary microvascular dysfunction (CMD) in patients with angina and nonobstructive coronary artery disease (CAD) is linked to poor prognosis.
- Current diagnostic methods for CMD, primarily using endothelium-independent vasodilators like adenosine, lack clear optimal thresholds.
- The added value of assessing endothelial function in conjunction with flow reserve has not been previously evaluated.
Purpose of the Study:
- To determine pharmacological thresholds for coronary flow reserve (CFR) and acetylcholine flow reserve (AchFR) that correlate with exercise-induced pathophysiology and myocardial ischemia.
- To establish the diagnostic accuracy of these thresholds in patients with angina and nonobstructive CAD.
Main Methods:
- Simultaneous coronary pressure and flow measurements during rest, exercise, and pharmacologic vasodilation (adenosine, acetylcholine) were performed.
- Coronary flow reserve (CFR, AchFR) calculated as vasodilator/resting flow.
- Coronary wave intensity analysis assessed exercise response; ischemia evaluated using 3-Tesla stress perfusion MRI.
Main Results:
- Optimal thresholds for CFR and AchFR identifying exercise pathophysiology and ischemia were 2.6 and 1.5, respectively.
- These thresholds demonstrated high positive (91%) and negative (86%) predictive values.
- Abnormal CFR was present in 58% of patients, with 96% also having abnormal AchFR; however, 53% of those with normal CFR had abnormal AchFR, correlating with higher ischemia rates.
Conclusions:
- Established optimal diagnostic thresholds for CFR (2.6) and AchFR (1.5) provide high predictive accuracy for ischemia in nonobstructive CAD.
- A normal CFR warrants further assessment with AchFR, suggesting a stepwise approach.
- Integrating both CFR and AchFR measurements offers a robust algorithm for identifying ischemic causes in this patient population.
Background:
Among patients with angina and nonobstructive coronary artery disease, those with coronary microvascular dysfunction have a poor outcome. Coronary microvascular dysfunction is usually diagnosed by assessing flow reserve with an endothelium-independent vasodilator like adenosine, but the optimal diagnostic threshold is unclear. Furthermore, the incremental value of testing endothelial function has never been assessed before. We sought to determine what pharmacological thresholds correspond to exercise pathophysiology and myocardial ischemia in patients with coronary microvascular dysfunction.
Methods:
Patients with angina and nonobstructive coronary artery disease underwent simultaneous acquisition of coronary pressure and flow during rest, supine bicycle exercise, and pharmacological vasodilatation with adenosine and acetylcholine. Adenosine and acetylcholine coronary flow reserve were calculated as vasodilator/resting coronary blood flow (CFR and AchFR, respectively). Coronary wave intensity analysis was used to quantify the proportion of accelerating wave energy; a normal exercise response was defined as an increase in accelerating wave energy from rest to peak exercise. Ischemia was assessed by quantitative 3-Tesla stress perfusion cardiac magnetic resonance imaging and dichotomously defined by a hyperemic endo-epicardial gradient <1.0.
Results:
Ninety patients were enrolled (58±10 years, 77% female). Area under the curve using receiver-operating characteristic analysis demonstrated optimal CFR and AchFR thresholds for identifying exercise pathophysiology and ischemia as 2.6 and 1.5, with positive and negative predictive values of 91% and 86%, respectively. Fifty-eight percent had an abnormal CFR (of which 96% also had an abnormal AchFR). Of those with a normal CFR, 53% had an abnormal AchFR, and 47% had a normal AchFR; ischemia rates were 83%, 63%, and 14%, respectively.
Conclusions:
The optimal CFR and AchFR diagnostic thresholds are 2.6 and 1.5, with high-positive and negative predictive values, respectively. A normal CFR value should prompt the measurement of AchFR. A stepwise algorithm incorporating both vasodilators can accurately identify an ischemic cause in patients with nonobstructive coronary artery disease.
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