On the judicious use of metrics for cerebral autoregulation.
On the judicious use of metrics for cerebral autoregulation.
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关于明智地使用大脑自动调节指标。
DOI:
10.1007/s00421-013-2718-4
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发表时间:
2013
影响因子:
3
通讯作者:
Taylor,JAndrew
中科院分区:
文献类型:
--
作者:
Tan,CanOzan;Taylor,JAndrew
We read the review by Tzeng and Ainslie (2013) with great interest and appreciate their emphasis on limitations in current paradigms to explore cerebral autoregulation. Clearly,‘‘many extant methods… are based on simplistic assumptions that can give rise to misleading interpretations.’’Indeed, though the ability to easily capture beat-bybeat data on a myriad of interacting variables has led to numerous unique insights, these same insights can often be limited by our ability to apply well-informed analyses. In fact, the same data may lead to different conclusions if the assumptions that underlie the analytic methods are violated. The authors highlight the inconsistency between different metrics, and underscore that only ‘‘few [metrics] exhibit statistical associations with each other.’’Though lack of agreement may indicate flawed assumptions, it might also indicate that some metrics are unfit to study the phenomenon under investigation. The lack of convergence between metrics may evidence ‘‘a lack of a common functional basis’’, and hence the researcher might ask ‘‘which metric, or combination of metrics, one should use.’’However, the construct validity of the proposed metrics may provide the answer. The hallmark of autoregulation is the ability to buffer against arterial pressure changes and is manifested as a lack of linear dependence between pressure and cerebral blood flow fluctuations (ie, low cross-spectral coherence or poor correlation). Most metrics are, in fact predicated on this manifestation: pressure-flow fluctuations exhibit low coherence (or correlation) when autoregulation is intact, and a close linear relation indicates when autoregulation is impaired. But, the issue is that if the pressure-flow relation displays a low linear relation (eg, coherence), it cannot be quantified reliably via linear analyses. Autoregulation by its very nature limits the utility of linear estimates. Therefore, while all linear metrics may indicate the ‘presence’or ‘absence’of cerebral autoregulation, none can reliably quantitate the pressure-flow relation when autoregulation is intact. Therefore, the search for ‘‘analytical innovations that enable multivariate quantification of… linear… properties of the cerebral circulation’’will suffer from the exact same limitations. For example, approximation of a three-element Windkessel model to characterize autoregulation is simply a multiple linear regression, and thus, is vulnerable to this very limitation; although it may provide excellent fits at the population level, its utility for intra-individual relationships remains unclear. As the authors state,‘‘physiological inferences are only as valid as the assumptions inherent in our methodological approaches.’’Our two recent studies, wherein we showed that alpha-adrenergic and muscarinic receptor blockade increases the coherence and gain relation between pressure and flow at frequencies less than 0.06 Hz (ie, slower than 15 s) were cited as particularly representative of this issue. Pressure and flow were highly coherent in both studies due to the use of oscillatory lower body negative pressure, thus, the authors suggest that it remains unclear to what extent