Preliminary Evidence of Orthostatic Intolerance and Altered Cerebral Vascular Control Following Sport-Related Concussion

We computed aortic flow pulsations from arterial pressure by simulating a nonlinear, time-varying three-element model of aortic input impedance. The model elements represent aortic characteristic impedance, arterial compliance, and systemic vascular resistance. Parameter values for the first two elements were computed from a published, age-dependent, aortic pressure-area relationship (G. J. Langewouters et al. J. Biomech. 17:425-435, 1984). Peripheral resistance was predicted from mean pressure and model mean flow. Model flow pulsations from aortic pressure showed the visual aspects of an aortic flow curve. For evaluation we compared model mean flow from radial arterial pressure with thermodilution cardiac output estimations, 76 times, in eight open heart surgical patients. The pooled mean difference was +7%, the SD 22%. After using one comparison per patient to calibrate the model, however, we followed quantitative changes in cardiac output that occurred either during changes in the state of the patient or subsequent to vasoactive drugs. The mean deviation from thermodilution cardiac output was +2%, the SD 8%. Given these small errors the method could monitor cardiac output continuously.

Despite the importance of blood flow on brainstem control of respiratory and autonomic function, little is known about regional cerebral blood flow (CBF) during changes in arterial blood gases.We quantified: (1) anterior and posterior CBF and reactivity through a wide range of steady-state changes in the partial pressures of CO2 (PaCO2) and O2 (PaO2) in arterial blood, and (2) determined if the internal carotid artery (ICA) and vertebral artery (VA) change diameter through the same range.We used near-concurrent vascular ultrasound measures of flow through the ICA and VA, and blood velocity in their downstream arteries (the middle (MCA) and posterior (PCA) cerebral arteries). Part A (n =16) examined iso-oxic changes in PaCO2, consisting of three hypocapnic stages (PaCO2 =∼15, ∼20 and ∼30 mmHg) and four hypercapnic stages (PaCO2 =∼50, ∼55, ∼60 and ∼65 mmHg). In Part B (n =10), during isocapnia, PaO2 was decreased to ∼60, ∼44, and ∼35 mmHg and increased to ∼320 mmHg and ∼430 mmHg. Stages lasted ∼15 min. Intra-arterial pressure was measured continuously; arterial blood gases were sampled at the end of each stage. There were three principal findings. (1) Regional reactivity: the VA reactivity to hypocapnia was larger than the ICA, MCA and PCA; hypercapnic reactivity was similar.With profound hypoxia (35 mmHg) the relative increase in VA flow was 50% greater than the other vessels. (2) Neck vessel diameters: changes in diameter (∼25%) of the ICA was positively related to changes in PaCO2 (R2, 0.63±0.26; P<0.05); VA diameter was unaltered in response to changed PaCO2 but yielded a diameter increase of +9% with severe hypoxia. (3) Intra- vs. extra-cerebral measures: MCA and PCA blood velocities yielded smaller reactivities and estimates of flow than VA and ICA flow. The findings respectively indicate: (1) disparate blood flow regulation to the brainstem and cortex; (2) cerebrovascular resistance is not solely modulated at the level of the arteriolar pial vessels; and (3) transcranial Doppler ultrasound may underestimate measurements of CBF during extreme hypoxia and/or hypercapnia.

Cerebral autoregulation is the intrinsic ability of the brain to maintain adequate cerebral perfusion in the presence of blood pressure changes. A large number of methods to assess the quality of cerebral autoregulation have been proposed over the last 30 years. However, no single method has been universally accepted as a gold standard. Therefore, the choice of which method to employ to quantify cerebral autoregulation remains a matter of personal choice. Nevertheless, given the concept that cerebral autoregulation represents the dynamic relationship between blood pressure (stimulus or input) and cerebral blood flow (response or output), transfer function analysis became the most popular approach adopted in studies based on spontaneous fluctuations of blood pressure. Despite its sound theoretical background, the literature shows considerable variation in implementation of transfer function analysis in practice, which has limited comparisons between studies and hindered progress towards clinical application. Therefore, the purpose of the present white paper is to improve standardisation of parameters and settings adopted for application of transfer function analysis in studies of dynamic cerebral autoregulation. The development of these recommendations was initiated by (but not confined to) theCerebral Autoregulation Research Network(CARNet -www.car-net.org).