In term of prognostic value, aortic blood pressure may be superior compared to the brachial pressure. A non-invasive technique for the computation of aortic pressure from peripheral information through the use of the generalized transfer function (GTF) is the most-used in clinical research. However, the dispersed and biased appraisal of aortic pressure obtained through this technique might hamper the scientific results obtained in population studies. Low-order, patient-specific whole-body mathematical models might help to bridge brachial to aortic pressure waveforms.
The object of the present investigation was to compare (i) GTF method, (ii) a patient-specific 1D-0D mathematical model, and (iii) brachial blood pressure in the appraisal of aortic pressure measured through catheter.
One-hundred patients referred to diagnostic coronary angiography were included. Brachial pressure and tonometric radial waveform were quantified simultaneously to invasive aortic pressure, which was quantified with a calibrated, fluid-filled catheter. End-systolic and end-diastolic left ventricular volumes and carotid-femoral pulse wave velocity were measured immediately prior to the invasive procedure and were used to set the mathematical model.
Systolic aortic pressure was underestimated (9.4 ± 11 mmHg, R2 = 0.71) while diastolic aortic pressure was overestimated (4.5 ± 10.2 mmHg, R2 = 0.4) by the GTF method. Mathematical model underestimated systolic (4 ± 16.5 mmHg, R2 = 0.47) and diastolic (3.9 ± 10.4 mmHg, R2 = 0.62) aortic pressure values. Oscillometric brachial pressure overestimated systolic (2.4 ± 12.6 mmHg, R2 = 0.71) and diastolic (3.7 ± 9.8 mmHg, R2 = 0.48) aortic pressure. Both brachial pressure and GTF methods presented a trend for higher systolic and diastolic pressure overestimation for higher aortic pressure, while mathematical modeling did not.
Despite oscillometric brachial pressures overestimate aortic pressure extremes its predictions correlate with invasive pressure similarly to both the widely-used GTF method and the subject specific, multiscale mathematical model.
1Hospital Vall d’Hebron, Department of Cardiology. VHIR, Universitat Autònoma de Barcelona, Barcelona, Spain
2Internal and Hypertension Division, Department of Medical Sciences, AOU Citta della Salute e della Scienza of Turin, Turin, Italy
3Division of Cardiology, Department of Medical Sciences, AOU Citta Salute e Scienza of Turin, University of Turin, Turin, Italy
4DIATI, Politecnico di Torino, Turin, Italy