Continuous positive airway pressure might not solve your cerebral autoregulation problem if you have obstructive sleep apnoea.

Abstract

In an intriguing paper in this issue of The Journal of Physiology, Waltz et al. (2016) tackle a very important question: can we reduce the impairment in cerebral autoregulation that is found in subjects with obstructive sleep apnoea (OSA) through the use of continuous positive airway pressure (CPAP)? It has previously been shown by Nasr et al. (2009) that, under normocapnic conditions, there is a correlation between the severity of OSA and impairment in cerebral autoregulation. OSA is also a risk factor for stroke: the recent review by Torabi-Nami et al. (2015) considers the impact of OSA on both cerebral autoregulation and neurocognition. However, we have only a poor understanding of this area and so this study's attempt to improve cerebral autoregulation is both novel and very welcome. The first interesting finding by Waltz et al. is that during normoxia there is impaired cerebral autoregulation in subjects with severe OSA compared to normal subjects, but that this difference is not found during (isocapnic) hypoxia. Waltz et al. make an interesting suggestion about the relationship between isocapnic hypoxia and sympathetic activity, although this may be very difficult to demonstrate. The importance of hypoxia provides an immediate link to studies performed at altitude where it has been shown that changes in cerebral autoregulation are directly linked to hypoxia (Subudhi et al. 2014). Focusing on hypoxia might well be a promising avenue for future work in this and other contexts. This does of course raise the question of cause and effect. Do alterations in oxygenation level directly cause impaired cerebral autoregulation, at either normocapnia or hypercapnia, and over what time period does this occur? Is OSA the risk factor for both cerebral autoregulation impairment and stroke or is it a risk factor for cerebral autoregulation impairment, which is then a risk factor for stroke? The interactions between these three conditions are of great physiological interest; however, to untangle the different causes and effects is challenging. What treatment would be best is clearly a difficult question to answer. The second result of Waltz et al. does, though, come as a surprise. Treatment of OSA might be thought to be critical to reducing cerebral autoregulation impairment with a possible further effect on stroke risk. However, Waltz et al. show that the treatment of OSA with CPAP does not alter cerebral autoregulation, even after 1 month of therapy. It is not yet clear whether or not this will affect the risk of stroke. After all, although impaired cerebral autoregulation is implicated in a number of pathological conditions, we do not yet know whether it is a cause or a symptom (Payne, 2016). We do need to understand how longer-term CPAP or other treatments might affect this impairment in cerebral autoregulation. Indeed, we should note that there is surprisingly little evidence that cerebral autoregulation can be ‘improved’; this study shows that it is unlikely to be straightforward or quick in the context of OSA. What is needed are longer term studies that look at patients over a prolonged period to see if therapies can improve cerebral autoregulation and/or reduce the risk of stroke. The question is also raised of whether it is possible to identify OSA patients early enough to keep the risks of impaired cerebral autoregulation and/or stroke low. Answers to these questions would help to disentangle the relationship between OSA, cerebral autoregulation and stroke in terms of cause and effect. This is very important in the context of a widespread chronic problem that affects a significant proportion of the population and with the continuing increase in obesity levels is likely to rise further. The risks associated with OSA do need to be more widely known to aid in prevention, even if we are not yet able to provide a cure for the impaired autoregulation. Finally, it is worth noting that the studies by Waltz et al. and Subudhi et al. both used transfer function analysis (with different parameter values), whilst the study by Nasr et al. used the Mx correlation metric. Future studies in this area should build upon recent recommendations on the implementation of transfer function analysis for cerebral autoregulation (Claassen et al. 2016), so that direct comparisons can be made. Modelling will also help to interpret these metrics, so that we can understand what an altered transfer function means and how it relates to the underlying physiology: without this, it is difficult to relate the analysis to the physiology. This combination of techniques should aid in trying to identify alternative suitable future therapies. None declared.