Background
Cerebral haemodynamic abnormalities may be useful early clinical markers in the development of age-related neurodegenerative disorders with vascular aetiologies [
1], in determining an increased risk of stroke among healthy and diseased populations [
2], and in predicting stroke prognosis [
3,
4]. Due to its clinical relevance, in recent years, polling cerebral haemodynamic data from different international research centres has become, an attractive option to generate larger study cohorts, enhancing the statistical power and the generalizability of study results [
5,
6]. Understanding to what extent regional differences affect cerebrovascular function is a key to planning international collaborative research and also to improve understanding of regional differences in treatment effectiveness and worldwide patient outcomes.
Health has multi-factorial determinants, including social, cultural, economic and environmental factors, genetic variation, and the quality of healthcare available [
5]. Different continents have different health conditions, especially considering marked socioeconomic, ethnical and health care disparities. Moreover, recent studies have reported significant differences between continents in the prevalence of cardiovascular risk factors, such as diabetes mellitus [
7,
8], hypertension [
9], smoking [
10] and hyperlipidaemia [
11]. Nevertheless, little information on the possible international regional differences in cerebral haemodynamics is available.
Therefore, with the aim of pooling individual subjects data from different regions in an on-going international collaborative research study of cerebral haemodynamic changes following acute ischaemic stroke (AIS), we investigated systemic and cerebral haemodynamic parameters in healthy older and AIS populations derived from two different regional research centre databases in the United Kingdom and Brazil. Data from these two regions were chosen in order to ensure the homogeneity of the measurement settings and reduce the interference of other confounding factors (e.g. transcranial Doppler inter-operator reliability), as only one researcher (AS) collected and analysed the data.
Results
A total of 100 participants were recruited from both centres, corresponding to 25 AIS patients and 25 age- and sex-matched control subjects from each centre. Baseline demographic and clinical data are described in Tables
1 and
2, respectively. No significant differences were seen in baseline demographic data, though African ethnicity, dyslipidaemia, cardiomyopathy and atrial fibrillation were more frequent in SP, and sub-surgical carotid artery stenosis (< 50%) more frequent in the LEI stroke population (Table
1). Stroke patients received medication according to local guidelines for secondary prevention at the time of assessment, with the most common antihypertensive treatment including: beta-blockers (LEI = 14 (56%) /SP = 13 (52%)), angiotensin converting enzyme inhibitors (LEI = 11 (44%)/SP = 12 (48%)), diuretics (LEI = 10 (40%) /SP = 7 (28%)). Statin therapy was prescribed to three LEI and two SP patients.
Table 1
Baseline characteristics of the stroke and control participants by geographical population
Age, years | 60.6 (15.8) | 62.4 (11.8) | 61.1 (9.9) | 60.7 (10.0) |
aNIHSS | 11.5 (6.6) | 14.3 (5.9) | NA | NA |
Sex, n (%) |
Female | 10 (40) | 12 (48) | 10 (40) | 11 (44) |
Male | 15 (60) | 13 (52) | 15 (60) | 14 (56) |
Ethnicity, n (%) |
Caucasian | 20 (80) | 15 (60) | 23 (92) | 22 (88) |
African | 4 (16) | 9 (36)* | 2 (8) | 3 (12) |
Natives | 0 | 1(4) | 0 | 0 |
Asian | 1(4) | 0 | 0 | 0 |
Diabetes, n (%) | 2 (8) | 4 (16) | 0 | 0 |
Hypertension, n (%) | 6 (24) | 10 (40) | 2 (8) | 0 |
Dyslipidemia, n (%) | 0 | 4 (16)* | 0 | 0 |
ICA stenosis, n (%) | 4 (16)* | 0 | 0 | 0 |
HIV, n (%) | 1 (4) | 0 | 0 | 0 |
AF, n (%) | 0 | 6 (24)* | 0 | 0 |
Cardiomyopathy, n (%) | 0 | 3 (12)* | 0 | 0 |
Table 2
Stroke characteristics by region
Stroke Side, n (%) |
Left | 11 (44) | 12 (48) |
Right | 14 (56) | 13 (52) |
Stroke aetiology, n (%) |
CE | 14 (56) | 18 (72) |
LAA | 3 (12) | 0 |
SVD | 7 (28)* | 0 |
SOE | 0 | 0 |
SUE | 1 (4) | 7 (28)* |
Stroke type, n (%) |
PACS | 14 (56) | 15 (60) |
TACS | 4 (16) | 10 (40)* |
LACS | 7 (28)* | 0 |
Thrombolysis, n (%) | 5 (20) | 9 (36) |
Compared to LEI stroke patients, SP patients were more likely to have total anterior circulation stroke syndrome and stroke of undetermined aetiology, and less likely to have had a lacunar stroke and small-vessel disease aetiology, though there were no differences in thrombolysis rates (Table
2). No differences between time of stroke onset and haemodynamics assessment was found (LEI = 42.0(5.9) and SP = 39.3(7.6) hours).
After confirming a lack of significant inter-hemispheral difference, cerebral haemodynamic parameters (CBFv, CrCP, RAP, ARI, gain, phase and coherence) from the right and left hemispheres in control subjects were merged, as performed previously [
13]. Table
3 gives the results of Levene’s tests for equality of variances between LEI and SP populations. The results indicate that the population variances across regions are equivalent.
Table 3
Levene’s test (statistics based on means) of variances equality between LEI and SP (geographical region) and stroke and control participants (participants type)
CBFv, cm.s−1 | 0.721 | 0.399 | 0.195 | 0.662 |
CrCP, mm Hg | 4.276 | 0.080 | 3.153 | 0.091 |
RAP, mmHg.s.cm− 1 | 1.496 | 0.230 | 2.231 | 0.120 |
Coherence VLF range | 2.099 | 0.493 | 2.443 | 0.407 |
Coherence LF range | 1.727 | 0.610 | 1.987 | 0.540 |
Coherence HF range | 0.929 | 0.703 | 1.592 | 0.622 |
Normalized gain VLF range, % mm Hg− 1 | 0.331 | 0.901 | 0.486 | 0.838 |
Normalized gain LF range, % mm Hg− 1 | 0.297 | 0.882 | 3.089 | 0.567 |
Normalized gain HF range, % mm Hg−1 | 3.921 | 0.098 | 3.444 | 0.612 |
Phase VLF range, radians | 2.982 | 0.801 | 2.491 | 0.475 |
Phase LF range, radians | 2.001 | 0.712 | 1.984 | 0.399 |
Phase HF range, radians | 2.665 | 0.723 | 2.091 | 0.523 |
ARI | 0.078 | 0.762 | 0.510 | 0.950 |
Compared to control subjects, stroke patients had significantly higher mean arterial BP, and significantly reduced CBFv in the affected, but not unaffected, hemisphere at the time of assessment (Table
4). RAP was significantly higher in the affected hemisphere than both the unaffected hemisphere in stroke patients, and control subjects (Table
4). No significant geographical differences were seen in either systemic or cerebral haemodynamic parameters for both stroke patients and control subjects (Table
4).
Table 4
Systemic and cerebral hemodynamic parameters in stroke and control participants by region
MAP, mmHg | 109.2 (5.7)# | 103.0 (5.5)# | 90.0 (6.1) | 89.2 (3.9) |
CBFv, cm.s−1 | 47.5 (6.3)# | 55.1 (5.8) | 41.7 (2.4)* | 45.03 (2.8) | 60.3(11.6) | 53.8 (5.5) |
CrCP, mm Hg | 18.2 (6.7) | 18.0 (4.6) | 19.4 (5.0) | 17.0 (5.5) | 14.2 (4.47) | 15.5 (8.0) |
RAP, mmHg.s.cm− 1 | 1.97 (0.32)*# | 1.76 (0.25)# | 2.25 (0.23)*# | 1.77 (0.17)# | 1.56 (0.27) | 1.65 (0.60) |
With respect to CA parameters, compared to control subjects, coherence was significantly increased in both the affected and unaffected hemispheres of AIS patients for both LF and HF ranges (Table
5). In addition, both phase in the VLF range and ARI were significantly reduced in the affected and unaffected hemispheres of AIS compared to control subjects (Table
5). No significant regional differences were observed, except for gain in the HF range between the affected and unaffected hemisphere in SP patients, which was not found in LEI patients (Table
5). Univariate ANCOVA adjusted for stroke aetiology and subtypes of the cerebral haemodynamics parameters also did not revealed any differences between regions (Table
6).
Table 5
Dynamic CA parameters in stroke and control participants by geographical region
Coherence VLF range | 0.65 (0.19) | 0.64 (0.14) | 0.61 (0.14) | 0.59 (0.14) | 0.52 (0.16) | 0.48 (0.11) |
Coherence LF range | 0.68 (0.23)# | 0.73 (0.19)# | 0.68 (0.17)# | 0.71 (0.15)# | 0.56 (0.18) | 0.58 (0.15) |
Coherence HF range | 0.72 (0.18)# | 0.77 (0.10)# | 0.69 (0.17)# | 0.67 (0.16)# | 0.52 (0.21) | 0.51 (0.15) |
Normalized gain VLF range, % mm Hg− 1 | 1.26 (0.57) | 1.17 (0.66) | 0.94 (0.33) | 0.91 (0.34) | 1.01 (0.39) | 1.19 (0.43) |
Normalized gain LF range, % mm Hg− 1 | 1.32 (0.48) | 1.22 (0.46) | 1.35 (0.44) | 1.26 (0.69) | 1.45 (0.83) | 1.49 (0.78) |
Normalized gain HF range, % mm Hg− 1 | 1.50 (0.74)* | 1.36 (0.51) | 1.36 (0.54) | 1.28 (0.55) | 1.35 (0.63) | 1.40 (0.58) |
Phase VLF range, radians | 0.53 (0.42)# | 0.78 (0.39)# | 0.58 (0.50)# | 0.70 (0.49)# | 0.88 (0.35) | 0.87 (0.41) |
Phase LF range, radians | 0.30 (0.45) | 0.25 (0.38) | 0.30 (0.35) | 0.31 (0.39) | 0.48 (0.19) | 0.45 (0.41) |
Phase HF range, radians | 0.09 (0.29) | 0.10 (0.25) | 0.11 (0.40)# | 0.17 (0.21)# | 0.05 (0.21) | 0.01 (0.28) |
ARI | 4.8 (2.3)# | 4.9 (2.0)# | 5.1 (1.8)# | 5.0 (1.1)# | 5.9 (1.5) | 5.5 (1.2) |
Table 6
ANCOVA and ANOVA results for comparison of cerebral haemodynamics parameters between geographical regions (stroke only)
CBFv, cm.s−1 | 3.2 | 8.6 | 0.7 | 0.9 | 0.83 | 0.42 |
CrCP, mm Hg | 2.5 | 3.0 | 5.2 | 4.8 | 0.60 | 0.81 |
RAP, mmHg.s.cm− 1 | 4.9 | 3.0 | 6.1 | 1.8 | 0.10 | 0.24 |
Coherence VLF range | 5.7 | 9.2 | 3.2 | 4.5 | 0.31 | 0.19 |
Coherence LF range | 3.8 | 4.4 | 2.9 | 4.3 | 0.44 | 0.31 |
Coherence HF range | 3.1 | 5.3 | 2.3 | 3.6 | 0.56 | 0.29 |
Normalized gain VLF range, % mm Hg− 1 | 14.0 | 5.1 | 5.2 | 1.4 | 0.07 | 0.33 |
Normalized gain LF range, % mm Hg−1 | 8.1 | 4.5 | 0.9 | 2.3 | 0.30 | 0.12 |
Normalized gain HF range, % mm Hg−1 | 7.8 | 4.4 | 5.5 | 1.2 | 0.21 | 0.40 |
Phase VLF range, radians | 4.2 | 2.5 | 0.2 | 0.1 | 0.90 | 0.90 |
Phase LF range, radians | 6.7 | 1.8 | 0.2 | 0.4 | 0.80 | 0.90 |
Phase HF range, radians | 5.5 | 1.4 | 1.0 | 0.2 | 0.80 | 0.30 |
ARI | 1.5 | 1.9 | 4.5 | 3.9 | 0.51 | 0.77 |
Discussion
Main findings
To the best of our knowledge, this is the first study to compare CA in participants from different geographical regions with marked environmental and socio-economic differences. These pooled analyses suggest no geographical differences in key, commonly measured cerebral haemodynamic parameters, including CBFv, CrCP, RAP and ARI. Overall, and in keeping with previous studies, impairment of cerebral haemodynamic parameters was reported in stroke compared to control participants, particularly in the affected hemisphere. Importantly, no geographical regional differences were found.
Clinical relevance
Recognizing similarities and differences in the cerebral haemodynamics in healthy subjects and stroke has public health and clinical implications for several cardiovascular outcomes. Haemodynamic abnormalities may be useful early clinical markers in the development of age-related vascular neurodegenerative disorders. Describing cerebral haemodynamic changes and their regulation in different geographical populations may help understand differences across age and ethnicities, as well as the potential generalizability of clinical studies results.
Impairment of CBFv and CA has a direct and major impact on secondary brain injury and clinical outcomes [
3,
4], as well as on planning effective therapeutic strategies that consider BP management and early mobilization protocols. In line with previous studies, our results showed a deterioration of important haemodynamic parameters in the acute phase of ischaemic stroke, particularly reduced phase and ARI values compared to controls [
3,
20‐
23]. Moreover, no significant alteration in gain between groups was found [
6,
20]. Though TFA became a popular approach for assessment of dynamic CA, very few acute stroke studies have reported the use of coherence estimates [
3,
22]. These previous studies failed to find raised coherence values in acute stroke, but an analogous parameter (the squared correlation coefficient) was found to be increased bilaterally after the first 48 h of stroke onset, suggesting worsening of CA [
23].
The importance and novelty of our results, however, stem from the similarities of the haemodynamic responses from research centres in both UK and Brazil, irrespective of the participant group (stroke or healthy controls). Despite the potential differences in dietary habits and lifestyles, and particularly in SP participants, higher prevalence of uncontrolled hypertension and widespread use of over-the-counter medications, cerebral haemodynamic parameters were not significantly different in our study. The authors believe that the outcome of this paper will strengthen the argument in favour of multicentre and multinational collaborative studies of the impact of cerebral haemodynamics in stroke and other conditions, such as sepsis and traumatic brain injury.
Environment effects on cerebral haemodynamics
Since differences in CBF and its control mechanisms between European and South American populations have not been previously reported, it is difficult to assess consistency with other studies in the literature. A previous TCD study of healthy young participants (
n = 20) in Germany and Hong Kong described no CBFv differences in the posterior cerebral arteries at rest and during cerebral activation [
24]. Nevertheless, slower initial haemodynamic responses to visual activation paradigms were described in the Asian group that may be related to deficits in the nitric oxide system. Previous studies have also compared cerebral haemodynamic responses between South Asian and Caucasian participants, but the results were inconsistent. In a United Kingdom-based study, resting MCA CBFv and cerebrovascular resistance parameters (Pourcelot’s resistive index and Gosling’s pulsatility index) were significantly higher, and CA impaired in South Asian participants [
25]. By contrast, no difference in the same parameters of CBFv and cerebrovascular resistance was found in another recent study of Canadian-based South Asians and Caucasians [
26].
Disparities in cardiovascular and cerebrovascular health and mortality among populations have been well documented, but poorly understood [
27,
28]. Studies have shown that the prevalence and mortality from hypertensive heart disease, stroke, and renal disease are higher among individuals of African compared to Caucasian descent [
29]. Moreover, intracranial atherosclerosis is highly prevalent among patients with Asian, Hispanic, and African ancestry [
30].
The present study did not demonstrate significant geographical differences in cerebral haemodynamic parameters between UK and Brazilian populations, with exception of gain at high frequency band. Immink and colleagues (2005) found an increase in gain only at higher frequencies in MCA-only stroke group. This may be the reason for the difference between regions, as SP comprised MCA infarcts only, whereas seven lacunar strokes were included in the LEI group (Table
2). Though recommended by the Cerebral Autoregulation Network (CARNet) [
31], there is limited information in the literature on CA status in the complete frequency dependence of coherence, gain and phase in the range 0.02–0.40 Hz. While the TFA parameters changes in VLF and LF ranges are familiar, very little is known about the behaviour of the BP/CBFv system at frequencies higher than 0.25 Hz. In the TFA model, phase and gain are considered two different aspects of a high-pass filter that acts primarily in the VLF and LF ranges. At high frequencies, CA is considered less relevant and CBFv changes are associated with heart stroke volume beat-to-beat variability. More clinical studies are necessary to investigate the clinical importance of investigating CA in the higher frequency band, taking advantage of the work that has already been done. A further finding of the present study related to the responses of cerebrovascular resistance mechanisms, derived from a two-parameter model: RAP-CrCP. Levene’s test revealed a marginal difference in CrCP between geographical regions, with a tendency to higher values in LEI participants. Further research is needed to assess the clinical value of this finding.
Standardized protocol
The experimental design of previous cerebral haemodynamic studies has been inconsistent, making it difficult to compare results directly [
32,
33]. Furthermore, there have been no previous CA studies in either older or stroke populations in Brazil. In contrast, in the UK, some studies have previously described the haemodynamic responses to spontaneous BP fluctuations, carbon dioxide modulations and brain activation paradigms in both populations [
12,
13,
34,
35]. More recently, the Department of Cardiovascular Sciences at the University of Leicester (Leicester, UK) has constructed a large database incorporating recordings from a series of separate studies performed in the same laboratory, using similar protocols, operator training and equipment [
36]. They have presented normative values for cerebral haemodynamic parameters in a large healthy population indicating parameters that may help distinguish between normal and abnormal CA.
The present study was only possible due to the development of standardized data collection and analysis that provided a robust approach for the systematic evaluation of CBFv and its main regulatory mechanisms [
37]. Similar to the Leicester normative study [
36], all data collected in this study were acquired with similar study protocols and laboratory set-up, albeit with minor differences in the equipment used, and most importantly, without observer variability since all recordings were performed by only one researcher (AS). This avoids inter-observer variability in the study protocol (particularly concerning the TCD data), and it consequently increases the reproducibility of study reports.
Study limitations
This study has limitations, including the use of non-invasive measurements of CBF and BP. Another limitation to consider is stroke patients received medication according to local guidelines for secondary prevention at the time of assessment. Though patients were on vasoactive therapy at time of assessment, no significant difference between populations was found. Although TFA and the ARI index can be regarded as the most widely used approach for assessment of dynamic CA, it is important to note that neither can be regarded as a ‘gold standard’. Future studies are needed to replicate our findings using alternative approaches such as time-domain analysis or the Mx index [
12]. Finally, the sample size is relatively small, and is unlikely to be representative enough to ensure robust conclusions. Therefore, the authors strongly advocate a large multicentre validation study with larger sample size to explore further the possibility of regional geographical influences on cerebral haemodynamics, and possible mechanisms to support any differences.
Conclusion
In conclusion, our results showed no significant differences in selected cerebral haemodynamic parameters between two different socio-economical geographical regions. In both research centres, acute ischaemic stroke depressed key measures of CA compared to a healthy older control population. These findings encourage further larger international studies of cerebral haemodynamic changes following AIS by pooling individual subject’s data from different regions.
Acknowledgements
Authors acknowledge Dr. João Loures Salinet Junior for his contribution in the data analysis and revising the manuscript. TGR is an NIHR Senior Investigator.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (
http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (
http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.