| Literature DB >> 29445973 |
Bhavik N Modi1, Haseeb Rahman1, Sara Abou Sherif1, Howard Ellis1, Kseniia Eruslanova1, Amedeo Chiribiri1, Divaka Perera2.
Abstract
Introduction Growing evidence supports ischemia-guided management of chest pain, with invasive and non-invasive tests reliant upon achieving adenosine-induced coronary hyperemia (defined as increased blood flow to an organ's perfusion bed). In the non-invasive setting, surrogate markers of hyperemia, such as increases in heart rate, are often used, despite not being formally validated. We tested whether heart rate and other non-invasive indices are reliable markers of coronary hyperemia. Methods The first part involved Doppler flow-based validation of the best pressure-wire markers of hyperemia in 53 patients. Subsequently, using these validated pressure-derived parameters, 265 pressure-wire traces were analysed to determine whether heart rate and other non-invasive parameters correlated with hyperemia. Results In the flow derivation cohort, the best determinant of hyperemia came from having 2 out of 3 of: (1) Ventriculisation of the distal pressure waveform, (2) disappearance of distal dicrotic pressure notch, (3) separation of mean aortic and distal pressures. Within the 244 patients demonstrating hyperemia, non-invasive markers of hyperemia, such as change in heart rate (p = 0.77), blood pressure (p = 0.60) and rate-pressure product (p = 0.86), were poor correlates of coronary hyperemia, with only 37.3% demonstrating a ≥ 10% increase in heart rate that is commonly used to adjudge adenosine-induced hyperemia in the non-invasive setting. Conclusions We demonstrate, by correlation with Doppler-flow data, a validated method of identifying coronary hyperemia within the catheter laboratory using the pressure-wire. We subsequently show that non-invasive parameters, such as heart rate change, are poor predictors of coronary hyperemia during stress imaging protocols that rely upon achieving adenosine-induced hyperemia.Entities:
Keywords: Adenosine; Coronary artery disease; Fractional flow reserve; Hyperemia; Stress perfusion cardiac MRI
Mesh:
Substances:
Year: 2018 PMID: 29445973 PMCID: PMC6280851 DOI: 10.1007/s10554-018-1309-1
Source DB: PubMed Journal: Int J Cardiovasc Imaging ISSN: 1569-5794 Impact factor: 2.357
Fig. 1Pressure-Derived Invasive Parameters. 1 The three-invasive pressure-based parameters that were investigated (A, B and C) and subsequently used to define hyperemia during IV adenosine infusion. Red trace = Pa (aortic wave), yellow trace = Pd (distal coronary wave). 2 Magnification of the three-invasive pressure-bounded parameters
Fig. 2Relationship between coronary flow reserve (CFR) and the three invasive parameters of hyperemia: graph illustrating the presence and absence of pressure-based parameters of hyperemia in 53 patients where simultaneous CFR value were measured. CFR cut-off of 1.2 used as a marker of definitive hyperemia
Diagnostic performance of each invasive parameter, and combinations of 2, at a CFR threshold of 1.2
| Sens | Spec | NPV | PPV | |
|---|---|---|---|---|
| Dicrotic notch disappearance | 84.2 | 73.3 | 88.9 | 64.7 |
| Separation of Pa and Pd | 97.4 | 20 | 75.5 | 75 |
| Ventricularisation of Pd trace | 84.2 | 53.3 | 82.1 | 57.1 |
| Dicrotic notch disappearance + ventricularisation | 73.7 | 93.3 | 96.6 | 58.3 |
| Dicrotic notch disappearance + separation of Pa and Pd | 81.6 | 73.3 | 88.6 | 61.1 |
| Separation of Pa and Pd + ventricularisation | 81.6 | 60 | 83.8 | 56.3 |
Within the validation cohort of patients with pressure and flow data, a CFR cut-off of 1.2 was used to calculate sensitivity (Sens), specificity (Spec), negative predictive (NPV) and positive predictive value (PPV) of the three pressure based parameters. Diagnostic performance was assessed both on their own and/or in different paired combinations
Fig. 3Flow chart: 265 patients with pressure data were analysed using the flow-validated pressure indices to determine hyperemic or not. The predictive accuracy of commonly used non-invasive haemodynamic markers (HR heart rate, SBP systolic blood pressure and HR × SBP rate pressure product) were analysed as % change in each parameter in response to IV adenosine from rest to the onset of the lowest Pd/Pa ratio
Demographics of patient population
| Hyperemic | Non hyperemic | p value | |||
|---|---|---|---|---|---|
| Variables | N = 244 | % | N = 21 | % | |
| Age | 65 ± 10.8 | 67 ± 9.7 | 0.63 | ||
| Sex (M/F) | 181/63 | 74.2/25.8 | 16/5 | 76.2/23.8 | 0.54 |
| Hypertension | 152 | 62.3 | 10 | 47.6 | 0.14 |
| Hypercholesterolemia | 181 | 74.2 | 16 | 76.2 | 0.54 |
| Diabetes mellitus | 59 | 24.2 | 8 | 38.1 | 0.13 |
| Smoker | 49 | 20.1 | 4 | 19 | 0.59 |
| Patients with a history of MI | 61 | 25 | 3 | 14.3 | 0.21 |
| Patients with a history of PCI | 90 | 36.9 | 3 | 14.3 | 0.03 |
| Patients with a history of CABG | 10 | 4.1 | 0 | 0 | |
| Indication for PCI: stable elective | 221 | 90.6 | 20 | 95.2 | 0.41 |
| Indication for PCI: ACS | 23 | 9.4 | 1 | 4.8 | 0.41 |
Comparison of demographics in hyperemic and non-hyperemic groups
M male, F female, MI myocardial infarction, PCI percutaneous coronary intervention, CABG coronary artery bypass graft, ACS acute coronary syndrome
*p value calculated by independent samples t test for age variable and Chi-squared significance for remaining variables
Fig. 4Heart rate variability. Pie chart representation of variability in percentage change in HR in patients deemed to be hyperemic versus those that were not
Fig. 5Variability in heart rate and Pd/Pa over time. An illustration of how the mean HR and Pd–Pa changed over the course of adenosine infusion in 244 hyperemic patients
Fig. 6Variability of non-invasive surrogate markers of hyperemia: a comparison of haemodynamic markers (RPP, HR and SBP) between patients achieving hyperemia and those that did not. Values are quoted as means ± standard deviation