Correlation of Pulse Wave Transit Time with Pulmonary Artery Pressure in a Porcine Model of Pulmonary Hypertension
Abstract
:1. Introduction
2. Materials and Methods
2.1. Animal Model and Anaesthesia
2.2. Instrumentation
2.3. Induction of PH
2.4. Data Acquisition and Processing
2.5. Statistics
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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A | sPAP [mmHg] | mPAP [mmHg] | dPAP [mmHg] | PWTT [ms] | PWV [m/s] |
1 | 42.5 ± 2.9 | 33.0 ± 1.9 | 22.5 ± 2.8 | 54.9 ± 3.4 | n/a |
2 | 28.7 ± 2.3 | 23.2 ± 2.0 | 15.9 ± 2.5 | 55.1 ± 4.1 | 1.9 ± 0.1 |
3 | 25.6 ± 1.3 | 20.1 ± 1.5 | 11.9 ± 1.4 | 27.2 ± 2.2 | 2.3 ± 0.2 |
4 | 25.0 ± 2.2 | 19.5 ± 1.8 | 12.6 ± 1.5 | 24.2 ± 2.4 | 2.7 ± 0.3 |
5 | 21.5 ± 1.6 | 15.0 ± 2.1 | 9.3 ± 2.7 | 38.6 ± 2.7 | 2.7 ± 0.2 |
6 | 29.1 ± 1.8 | 23.7 ± 2.0 | 18.6 ± 2.5 | 35.5 ± 2.9 | 2.0 ± 0.2 |
B | sPAP [mmHg] | mPAP [mmHg] | dPAP [mmHg] | PWTT [ms] | PWV [m/s] |
1 | n/a | n/a | n/a | n/a | n/a |
2 | 25.0 ± 2.0 | 20.5 ± 1.9 | 13.5 ± 2.5 | 62.6 ± 4.8 | 1.6 ± 0.1 |
3 | 21.8 ± 1.8 | 16.4 ± 1.6 | 12.0 ± 2.0 | 57.8 ± 7.2 | 1.6 ± 0.2 |
4 | 22.9 ± 1.6 | 18.4 ± 1.7 | 11.6 ± 2.5 | 54.2 ± 5.3 | 1.2 ± 0.1 |
5 | 21.1 ± 1.2 | 15.4 ± 1.6 | 10.0 ± b1.8 | 55.6 ± 2.3 | 2.0 ± 0.1 |
6 | 27.9 ± 1.7 | 19.5 ± 2.2 | 11.2 ± 3.1 | 47.9 ± 3.4 | 1.7 ± 0.1 |
A | sPAP [mmHg] | mPAP [mmHg] | dPAP [mmHg] | PWTT [ms] | PWV [m/s] |
1 | 60.4 ± 3.1 | 43.9 ± 1.8 | 20.0 ± 5.6 | 42.9 ± 3.3 | n/a |
2 | 37.5 ± 2.2 | 30.8 ± 2.1 | 21.6 ± 2.9 | 42.6 ± 0.7 | 2.4 ± 0.2 |
3 | 42.1 ± 1.9 | 31.4 ± 1.6 | 22.3 ± 1.5 | 13.4 ± 4.1 | 5.0 ± 1.5 |
4 | 47.3 ± 1.4 | 32.4 ± 1.6 | 21.3 ± 1.7 | 10.2 ± 2.0 | 6.5 ± 1.2 |
5 | 28.4 ± 1.8 | 22.3 ± 2.1 | 16.3 ± 2.8 | 21.0 ± 5.2 | 5.3 ± 1.2 |
6 | 46.8 ± 4.4 | 36.6 ± 2.7 | 29.5 ± 2.3 | 16.0 ± 3.5 | 4.5 ± 0.8 |
B | sPAP [mmHg] | mPAP [mmHg] | dPAP [mmHg] | PWTT [ms] | PW [m/s] |
1 | n/a | n/a | n/a | n/a | n/a |
2 | 44.8 ± 1.5 | 35.1 ± 1.7 | 27.1 ± 2.0 | 30.8 ± 6.0 | 3.4 ± 0.7 |
3 | 38.4 ± 1.4 | 29.6 ± 1.5 | 20.6 ± 2.1 | 38.0 ± 3.8 | 2.5 ± 0.2 |
4 | 39.7 ± 2.1 | 29.5 ± 2.4 | 21.0 ± 3.2 | 26.5 ± 6.7 | 2.6 ± 0.6 |
5 | 29.2 ± 1.8 | 23.5 ± 1.8 | 17.9 ± 1.9 | 33.0 ± 4.2 | 3.5 ± 0.5 |
6 | 40.5 ± 3.4 | 31.8 ± 2.9 | 23.7 ± 2.9 | 30.2 ± 6.3 | 2.8 ± 0.5 |
A | sPAP | mPAP | dPAP | ||||||||||
Pig | n | Linear Regression | r2 | F | p | Linear Regression | r2 | F | p | Linear Regression | r2 | F | p |
1 | 1611 | PWTT = 70.945 − (0.481 * sPAP) | 0.356 | 888.151 | <0.001 | PWTT = 83.645 − (0.969 * mPAP) | 0.499 | 1601.15 | <0.001 | PWTT = 49.662 − (0.112 * dPAP) | 0.00885 | 14.364 | <0.001 |
2 | 686 | PWTT = 98.938 − (1.298 * sPAP) | 0.502 | 689.041 | <0.001 | PWTT = 99.054 − (1.616 * mPAP) | 0.466 | 596.726 | <0.001 | PWTT = 84.597 − (1.537 * dPAP) | 0.430 | 517.007 | <0.001 |
3 | 333 | PWTT = 42.133 − (0.646 * sPAP) | 0.547 | 400.226 | <0.001 | PWTT = 44.194 − (0.917 * mPAP) | 0.534 | 379.604 | <0.001 | PWTT = 37.053 − (0.967 * dPAP) | 0.542 | 391.071 | <0.001 |
4 | 377 | PWTT = 46.632 − (0.683 * sPAP) | 0.399 | 248.757 | <0.001 | PWTT = 44.595 − (0.815 * mPAP) | 0.210 | 90.716 | <0.001 | PWTT = 43.850 − (1.239 * dPAP) | 0.245 | 121.935 | <0.001 |
5 | 426 | PWTT = 81.659 − (2.047 * sPAP) | 0.649 | 783.579 | <0.001 | PWTT = 62.936 − (1.719 * mPAP) | 0.597 | 628.24 | <0.001 | PWTT = 46.610 − (1.243 * dPAP) | 0.447 | 342.462 | <0.001 |
6 | 440 | PWTT = 63.723 − (0.972 * sPAP) | 0.765 | 1422.27 | <0.001 | PWTT = 62.645 − (1.129 * mPAP) | 0.686 | 955.157 | <0.001 | PWTT = 58.002 − (1.188 * dPAP) | 0.628 | 738.206 | <0.001 |
B | sPAP * | mPAP | dPAP | ||||||||||
Pig | n | Linear Regression | r2 | F | p | Linear Regression | r2 | F | p | Linear Regression | r2 | F | p |
1 | 686 | PWTT = 98.938 − (1.298 * sPAP) | 0.502 | 689.041 | <0.001 | PWTT = 99.054 − (1.616 * mPAP) | 0.466 | 596.726 | <0.001 | PWTT = 84.597 − (1.537 * dPAP) | 0.430 | 517.007 | <0.001 |
2 | 1022 | PWTT = 95.676 − (1.501 * sPAP) | 0.671 | 2083.98 | <0.001 | PWTT = 90.743 − (1.719 * mPAP) | 0.598 | 1518.03 | <0.001 | PWTT = 85.160 − (2.027 * dPAP) | 0.503 | 1030.82 | <0.001 |
3 | 444 | PWTT = 93.021 − (1.542 * sPAP) | 0.597 | 653.743 | <0.001 | PWTT = 93.907 − (1.967 * mPAP) | 0.547 | 534.506 | <0.001 | PWTT = 77.779 − (1.806 * dPAP) | 0.467 | 386.649 | <0.001 |
4 | 1040 | PWTT = 117.075 − (2.902 * sPAP) | 0.750 | 3114.64 | <0.001 | PWTT = 97.682 − (2.717 * mPAP) | 0.730 | 2804.00 | <0.001 | PWTT = 80.169 − (2.548 * dPAP) | 0.709 | 2531.34 | <0.001 |
5 | 290 | PWTT = 88.233 − (1.354 * sPAP) | 0.716 | 725.429 | <0.001 | PWTT = 74.310 − (1.249 * mPAP) | 0.652 | 539.333 | <0.001 | PWTT = 60.839 − (1.024 * dPAP) | 0.551 | 354.094 | <0.001 |
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Mueller-Graf, F.; Merz, J.; Bandorf, T.; Albus, C.F.; Henkel, M.; Krukewitt, L.; Kühn, V.; Reuter, S.; Vollmar, B.; Pulletz, S.; et al. Correlation of Pulse Wave Transit Time with Pulmonary Artery Pressure in a Porcine Model of Pulmonary Hypertension. Biomedicines 2021, 9, 1212. https://doi.org/10.3390/biomedicines9091212
Mueller-Graf F, Merz J, Bandorf T, Albus CF, Henkel M, Krukewitt L, Kühn V, Reuter S, Vollmar B, Pulletz S, et al. Correlation of Pulse Wave Transit Time with Pulmonary Artery Pressure in a Porcine Model of Pulmonary Hypertension. Biomedicines. 2021; 9(9):1212. https://doi.org/10.3390/biomedicines9091212
Chicago/Turabian StyleMueller-Graf, Fabian, Jonas Merz, Tim Bandorf, Chiara Felicitas Albus, Maike Henkel, Lisa Krukewitt, Volker Kühn, Susanne Reuter, Brigitte Vollmar, Sven Pulletz, and et al. 2021. "Correlation of Pulse Wave Transit Time with Pulmonary Artery Pressure in a Porcine Model of Pulmonary Hypertension" Biomedicines 9, no. 9: 1212. https://doi.org/10.3390/biomedicines9091212
APA StyleMueller-Graf, F., Merz, J., Bandorf, T., Albus, C. F., Henkel, M., Krukewitt, L., Kühn, V., Reuter, S., Vollmar, B., Pulletz, S., Böhm, S. H., Reuter, D. A., & Zitzmann, A. (2021). Correlation of Pulse Wave Transit Time with Pulmonary Artery Pressure in a Porcine Model of Pulmonary Hypertension. Biomedicines, 9(9), 1212. https://doi.org/10.3390/biomedicines9091212