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We aimed to assess cerebral autoregulation (CA) and neurovascular coupling (NVC) in stroke patients of differing severity comparing responses to healthy controls and explore the association between CA and NVC with functional outcome. Patients admitted with middle cerebral artery (MCA) stroke and healthy controls were recruited. Stroke severity was defined by the National Institutes of Health Stroke Scale (NIHSS) scores: ≤4 mild, 5-15 moderate and ≥16 severe. Transcranial Doppler ultrasound and Finometer recorded MCA cerebral blood flow velocity (CBFv) and blood pressure, respectively, over 5 min baseline and 1 min passive movement of the elbow to calculate the autoregulation index (ARI) and CBFv amplitude responses to movement. All participants were followed up for three months. A total of 87 participants enrolled in the study, including 15 mild, 27 moderate and 13 severe stroke patients, and 32 control subjects. ARI was lower in the affected hemisphere (AH) of moderate and severe stroke groups. Decreased NVC was seen bilaterally in all stroke groups. CA and NVC correlated with stroke severity and functional outcome. CBFv regulation is significantly impaired in acute stroke, and further compromised with increasing stroke severity. Preserved CA and NVC in the acute period were associated with improved three-month functional outcome.

Acute stroke is associated with high morbidity and mortality. In the last decades, new therapies have been investigated with the aim of improving clinical outcomes in the acute phase post stroke onset. However, despite such advances, a large number of patients do not demonstrate improvement, furthermore, some unfortunately deteriorate. Thus, there is a need for additional treatments targeted to the individual patient. A potential therapeutic target is interventions to optimize cerebral perfusion guided by cerebral hemodynamic parameters such as dynamic cerebral autoregulation (dCA). This narrative led to the development of the INFOMATAS (Identifying New targets FOr Management And Therapy in Acute Stroke) project, designed to foster interventions directed towards understanding and improving hemodynamic aspects of the cerebral circulation in acute cerebrovascular disease states. This comprehensive review aims to summarize relevant studies on assessing dCA in patients suffering acute ischemic stroke, intracerebral haemorrhage, and subarachnoid haemorrhage. The review will provide to the reader the most consistent findings, the inconsistent findings which still need to be explored further and discuss the main limitations of these studies. This will allow for the creation of a research agenda for the use of bedside dCA information for prognostication and targeted perfusion interventions.

Objective: Different methods to calculate dynamic cerebral autoregulation (dCA) parameters are available. However, most of these methods demonstrate poor reproducibility that limit their reliability for clinical use. Inter-centre differences in study protocols, modelling approaches and default parameter settings, have all led to a lack of standardisation and comparability between studies. We evaluated reproducibility of dCA parameters by assessing systematic errors in surrogate data resulting from different modelling techniques. Approach: Fourteen centres analysed 22 datasets consisting of two repeated physiological blood pressure measurements with surrogate cerebral blood flow velocity signals, generated using Tiecks curves (autoregulation index , ARI 0-9) and added noise. For reproducibility, dCA methods were grouped in three broad categories: 1. Transfer function analysis (TFA)-like output; 2. ARI-like output; 3. Correlation coefficient-like output. For all methods, reproducibility was determined by one-way Intraclass Correlation Coefficient analysis (ICC). Main results: For TFA-like methods the mean (SD; [range]) ICC gain was 0.71 (0.10; [0.49-0.86]) and 0.80 (0.17; [0.36-0.94]) for VLF and LF (p=0.003) respectively. For phase, ICC values were 0.53 (0.21; [0.09-0.80]) for VLF, and 0.92 (0.13; [0.44-1.00]) for LF (p <0.001). Finally, ICC for ARI-like methods was equal to 0.84 (0.19; [0.41-0.94]), and for correlation-like methods , ICC was 0.21 (0.21; [0.056-0.35]). Significance: When applied to realistic surrogate data, free from the additional exogenous influences of physiological variability on cerebral blood flow, most methods of dCA modelling showed ICC values considerably higher than what has been reported for physiological data. This finding suggests that the poor reproducibility reported by previous studies may be mainly due to the inherent physiological variability of cerebral blood flow regulatory mechanisms rather than related to (stationary) random noise and the signal analysis methods.

Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-center study, we evaluated the influence of multiple analytical methods on the reproducibility of DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting of 5 min of spontaneous fluctuations in blood pressure and cerebral blood flow velocity signals, based on their usual methods of analysis. DCA methods were grouped into three broad categories, depending on output types: (1) transfer function analysis (TFA); (2) autoregulation index (ARI); and (3) correlation coefficient. Only TFA gain in the low frequency (LF) band showed good reproducibility in approximately half of the estimates of gain, defined as an intraclass correlation coefficient (ICC) of >0.6. None of the other DCA metrics had good reproducibility. For TFA-like and ARI-like methods, ICCs were lower than values obtained with surrogate data ( p < 0.05). For TFA-like methods, ICCs were lower for the very LF band (gain 0.38 ± 0.057, phase 0.17 ± 0.13) than for LF band (gain 0.59 ± 0.078, phase 0.39 ± 0.11, p ≤ 0.001 for both gain and phase). For ARI-like methods, the mean ICC was 0.30 ± 0.12 and for the correlation methods 0.24 ± 0.23. Based on comparisons with ICC estimates obtained from surrogate data, we conclude that physiological variability or non-stationarity is likely to be the main reason for the poor reproducibility of DCA parameters.

Background: Acute ischaemic stroke (AIS) patients often show impaired cerebral autoregulation (CA). We tested the hypothesis that CA impairment and other alterations in cerebral haemodynamics are associated with stroke subtype and severity. Methods: AIS patients (n = 143) were amalgamated from similar studies. Data from baseline (< 48 h stroke onset) physiological recordings (beat-to-beat blood pressure [BP], cerebral blood flow velocity (CBFV) from bilateral insonation of the middle cerebral arteries) were calculated for mean values and autoregulation index (ARI). Differences were assessed between stroke subtype (Oxfordshire Community Stroke Project [OCSP] classification) and severity (National Institutes of Health Stroke Scale [NIHSS] score < 5 and 5–25). Correlation coefficients assessed associations between NIHSS and physiological measurements. Results: Thirty-two percent of AIS patients had impaired CA (ARI < 4) in affected hemisphere (AH) that was similar between stroke subtypes and severity. CBFV in AH was comparable between stroke subtype and severity. In unaffected hemisphere (UH), differences existed in mean CBFV between lacunar and total anterior circulation OCSP subtypes (42 vs. 56 cm•s^–1, p < 0.01), and mild and moderate-to-severe stroke severity (45 vs. 51 cm•s^–1, p = 0.04). NIHSS was associated with peripheral (diastolic and mean arterial BP) and cerebral haemodynamic parameters (CBFV and ARI) in the UH. Conclusions: AIS patients with different OCSP subtypes and severity have homogeneity in CA capability. Cerebral haemodynamic measurements in the UH were distinguishable between stroke subtype and severity, including the association between deteriorating ARI in UH with stroke severity. More studies are needed to determine their clinical significance and to understand the determinants of CA impairment in AIS patients.

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