DOI: https://doi.org/10.21203/rs.3.rs-2838426/v1
Elevated and low blood pressure (BP) may lead to poor functional outcome after ischemic stroke, which is conflicting. Hence, there must be “confounders” - such as cerebral small vessel disease (cSVD) -interacting with BP and thus, affecting outcome. Here, we investigate the relationship between BP and cSVD regarding outcome after stroke.
Data of 423/503 stroke patients were prospectively analyzed. Diastolic (DBP) and systolic BP (SBP) were collected on hospital admission (BPad) and over the first 72 hours (BP72h). cSVD-burden was determined on MR-scans. Good functional outcome was defined as a modified Rankin Scale score ≤ 2 at hospital discharge and 12 months thereafter.
cSVD was a predictor of poor outcome (OR 2.8; p < 0.001). SBPad, DBPad and SBP72h were not significantly associated with outcome at any time. A significant relationship was found between DBP72h, (p < 0.01), cSVD (p = 0.013) and outcome at discharge. At 12 months, we found a relationship between outcome and DBP72h (p = 0.018) and a statistical tendency regarding cSVD (p = 0.08). Changes in DBP72h were significantly related with outcome. There was a U-shaped relationship between DBP and outcome at discharge.
Our results suggest an individualized stroke care by either lowering or elevating DBP depending on cSVD-burden in order to influence functional outcome.
Increased blood pressure (BP) is found in around 80% of all patients with acute ischemic stroke (AIS) on hospital admission as well as in the acute phase of AIS 1. However, the impact of BP in the acute phase of AIS on functional outcome remains an matter of debate 3–5. So far, there is some evidence that raised BP early after AIS is associated with dependency, clinical deterioration and subsequent death 6. In contrast, some studies revealed that both low and high BP entails poor prognosis after AIS 5,7. Further studies found no effect of BP in the acute phase of AIS on functional outcome 8,9. Of note, some other studies even suggested that an increase of BP in the acute phase of AIS may be a protective response to reduced cerebral perfusion and thus, may enhance decreasing blood flow to the infarcted zone and surrounding penumbra 10–12. Hence, these different and partially contradictory findings suggest that additional factors such as cerebral small vessel disease (cSVD) may interfere prognosis and clinical outcome after AIS. The term cSVD refers to the dysfunction of cerebral microvessel endothelium affecting cell-cell interactions and finally resulting in brain damage 13–15. Clinically, cSVD may lead to stroke, cognitive dysfunction and worsening of gait as well as balance 16. On brain MRI, cSVD presents with lacunes, white matter hyperintensities (WMH), cerebral microbleeds (CMB) and perivascular spaces 13,16,17. In particular, WMH are the most common cSVD lesions that are observed on brain MR scans of most people aged over 70 years 18. CMB also increase with age although they occur less frequent compared to WMH and are unusual in the absence of WMH 14. In a recently published study on stroke patients undergoing endovascular treatment, no signs of cSVD was observed in 61%, mild and moderate or severe degree of cSVD was seen in 20.0% and 19.7%, respectively 19. Hence the question arises whether patients with AIS and no cSVD profit e.g., from a lower BP than stroke patients with a moderate or severe degree of cSVD. Of note, autoregulation of cerebral blood flow is hampered in the acute phase of AIS making cerebral perfusion directly dependent on BP 20–22. Additionally, patients with severe cSVD have an even more reduced cerebral blood flow and impaired cerebral autoregulation 23,24.
With these considerations in mind, we aimed to investigate whether functional outcome in the short term (at discharge) and in the long term (12 months after cerebrovascular event) differs between stroke patients with a high and low burden of cSVD depending on the level of acute-phase systolic (SBP) and/or diastolic blood pressure (DBP). Additionally, we examined whether there is an interaction between BP in the acute phase and severity of cSVD regarding functional impairment, recurrent stroke/TIA and death 12 month after index event.
We conducted a prospective single-center cohort study at the University Clinic Würzburg (Stroke Unit, Department of Neurology). From October 2016 to October 2017, all consecutive patients with an ischemic stroke or transient ischemic attack (TIA) admitted to the emergency room within 24 hours after onset of symptoms were included in the study. Written informed consent from the patient or patients’ next of kin was obtained before enrolment. The study was approved by the local ethics committee of Würzburg (AZ 223/16). The study protocol adheres to the established standards for the reporting of observational studies 25. Anonymous data will be shared by request.
During hospitalization, data on demographic characteristics (age, sex), vascular risk factors (hypertension, diabetes mellitus, dyslipidemia, coronary heart disease, myocardial infarction, atrial fibrillation, previous stroke or TIA, peripheral artery occlusive disease and current cigarette smoking), comorbidities (liver and kidney dysfunction), previous medication (antihypertensives, antiplatelets, anticoagulants, statins), previous degree of disability (according to modified Rankin scale (mRS)) recanalization therapy (intravenous thrombolysis; endovascular treatment) discharge medication (antihypertensives, antiplatelets, anticoagulants, statins) and stroke/TIA characteristics were collected prospectively in a database (Table 1). Stroke characteristics included (1) stroke severity on admission and at discharge assessed by the National Institutes of Health Stroke Scale (NIHSS) score 26 and (2) stroke subtype classified according to the criteria of Trial of Org 10172 in Acute Stroke Treatment (TOAST) 27.
All patients | Good outcome (mRS 0–2) | Poor outcome (mRS 3–6) | p-value | |
---|---|---|---|---|
n | 423 | 311 | 112 | |
Demographics | ||||
Age, median (Q1-Q3), y, n = 423 | 73 (61–79) | 70 (59–79) | 78 (65.8–83) | < 0.0011 |
Female, n = 423 (%) | 184 (43.5%) | 127 (40.8%) | 57 (50.9%) | 0.084 |
Vascular risk factors, n (%) | ||||
Hypertension, n = 422 | 359 (85.1) | 256 (82.3) | 103 (92.8) | 0.012 |
Newly diagnosed, n = 422 | 31 (7.35) | 22 (7.07) | 9 (8.11) | 0.883 |
Atrial fibrillation, n = 422 | 114 (27.0) | 72 (23.2) | 42 (37.8) | 0.004 |
Current Smoking, n = 422 | 74 (17.5) | 58 (18.6) | 16 (14.4) | 0.389 |
Hypercholesterolemia, n = 422 | 238 (56.4) | 180 (57.9) | 58 (52.3) | 0.360 |
Diabetes mellitus, n = 422 | 97 (23.0) | 61 (19.6) | 36 (32.4) | 0.009 |
Coronary heart disease, n = 422 | 56 (13.3) | 32 (10.3) | 24 (21.6) | 0.004 |
Myocardial Infarction, n = 422 | 23 (5.45) | 13 (4.18) | 10 (9.01) | 0.093 |
Prior stroke or TIA, n = 422 | 103 (24.4) | 69 (22.2) | 34 (30.6) | 0.099 |
Positive Family history, n = 422 | 101 (23.9) | 76 (24.4) | 25 (22.5) | 0.782 |
Peripheral artery occlusive disease, n = 422 | 23 (5.45) | 11 (3.54) | 12 (10.8) | 0.008 |
Kidney dysfunction, n = 422 | 135 (32.0) | 86 (27.7) | 49 (44.1) | 0.002 |
Liver dysfunction, n = 422 | 7 (1.66) | 2 (0.64) | 5 (4.5) | 0.015 |
Clinical data | ||||
NIHSS at entry, median (Q1-Q3), n = 423 | 3 (1–6) | 2 (0–4) | 7 (4–12.2) | < 0.0011 |
NIHSS at discharge, median (Q1-Q3), n = 423 | 1 (0–3) | 0 (0–1) | 4 (2–7) | < 0.0011 |
mRS at entry, mean ± SD, n = 423 | 2.37 ± 1.58 | 1.77 ± 1.35 | 4.0 ± 0.76 | < 0.001 |
mRS at discharge, mean ± SD, n = 423 | 1.44 ± 1.43 | 0.71 ± 0.81 | 3.45 ± 0.6 | < 0.001 |
Recanalization therapy, n (%) | ||||
Intravenous thrombolysis, n = 423 | 91 (21.5) | 54 (17.4) | 37 (33.0) | < 0.001 |
Endovascular treatment, n = 423 | 37 (8.75) | 15 (4.82) | 22 (19.6) | < 0.001 |
MRI Findings, n (%) | ||||
Lacunes, n = 412 | 172 (41.7) | 119 (39.0) | 53 (49.5) | 0.074 |
WML (Fazekas score 2–3), n = 414 | 228 (55.1) | 154 (50.5) | 74 (67.9) | 0.003 |
CMB, n = 419 | 113 (27.0) | 76 (24.6) | 37 (33.6) | 0.087 |
cSVD (CMB a./o.WML), n = 419 | 259 (61.8) | 173 (56.0) | 86 (78.2) | < 0.001 |
Stroke etiology, n = 423, n (%) | ||||
Large artery disease | 79 (18.7) | 59 (19.0) | 20 (17.9) | 0.115 |
Cardioembolism | 160 (37.8) | 107 (34.4) | 53 (47.3) | 0.221 |
Small vessel occlusion | 30 (7.09) | 23 (7.40) | 7 (6.25) | 0.849 |
Other determined | 9 (2.13) | 6 (1.93) | 3 (2.68) | 0.609 |
undetermined | 145 (34.3) | 116 (37.3) | 29 (25.9) | 0.364 |
1calculated with Mann-Whitney-U-test |
All patients underwent brain MRI within 72 hours after admission to identify acute ischemic stroke or TIA. WMH were categorized visually on fluid-attenuated inversion recovery (FLAIR) scans using the Fazekas scale and rated as mild (Fazekas 0–1) or severe (Fazekas 2–3) 28. CMB were defined as small, circular or rounded, hypointense lesions within brain parenchyma ranging from 2 to 10 mm in size 29. Assessment of CMB was performed on T2*-weighted gradient-recalled echo (T2*-GRE) scans or on susceptibility-weighted images (SWI). Lacunes were defined as CSF-filled cavities with a diameter of at least 3mm 30. cSVD burden was visually rated on MR scans and divided in absent/ mild cSVD (Fazekas 0–1, no CMB) and moderate/severe cSVD (Fazekas 2–3 and/or ≥ 1 CMB).
Blood pressure (BP) was measured by a noninvasive BP monitoring device on the non-paralytic arm according to our in-hospital guidelines for acute stroke management. BP values obtained on patients’ admission and during their stay in the stroke unit were entered in the electronic health record system. From the collected BP data, we retrieved SBP and DBP values at the time of admission and thereafter every 8 hours during the first 72 hours after hospital admission. In addition, patients with known and treated hypertension continued antihypertensive treatment, unless BP was below 120/70 mmHg (intern guidelines). When SBP at the stroke unit was > 160mmHg, antihypertensive treatment was adjusted accordingly. The number of patients with newly diagnosed arterial hypertension on hospital was 7.35%. Change in SBP or DBP over the time was calculated as SBP or DBP at time point – SBP or DBP at baseline (i.e. at hospital admission) 22.
In order to evaluate functional outcome of TIA and stroke patients, the mRS score was assessed prospectively on discharge (outcomedisc) and at 12 months after cerebrovascular event (outcome12mo) through a structured follow-up telephone interview by a trained stroke fellow (S.G.). During the interview, current medication and BP were collected. The mRS score on discharge as well as at 12 months was dichotomized into good (mRS score 0–2) and poor outcome (mRS score of 3–6) 31.
The baseline data of all patients are demonstrated as mean ± SD or median (first quartile, Q1; third quartile, Q3) for continuous variables or frequency (percentage) for categorical variables.
First, study parameters were compared in a descriptive manner regarding good and poor functional outcome at discharge and at 12 months after stroke. Metric or ordinal variables have been compared with unpaired t-Test, or Mann-Whitney-U-test as appropriate. For dichotomous traits like hypertension or diabetes mellitus, Chi-square-test was used. Second, multivariable logistic regression was used to estimate the influence of the different study variables in respect to functional outcome at discharge and at 12 months thereafter. DBP and age were modelled in a non-linear way using a 3-knot restricted cubic spline, as described in detail elsewhere 32. Results of the regression analysis were depicted as odds ratios (OR) and 95% confidence interval (95%CI). Possible interactions between selected variables were calculated using Likelihood-ratio Chi-square-tests. P < 0.05 was regarded statistically significant. Statistical analyses were performed using R version 4.0.4 (R: a Language and Environment for Statistical Computing; Vienna, Austria, 2021-03-15).
A total of 503 patients with either ischemic stroke or TIA were screened for this study. Out of them, full data set was available for 423 at discharge, and 369 patients completed follow-up 12 months after event (Fig. 1). The baseline characteristics for the final cohort are summarized in Tables 1 and 2.
All patients | Good outcome (mRS 0–2) | Poor outcome (mRS 3–6) | p-value | |
---|---|---|---|---|
n | 369 | 261 | 108 | |
Demographics | ||||
Age, median (Q1-Q3), n = 369, y | 72 (60–79) | 68 (58–77) | 78 (69–83) | < 0.0011 |
Female, n = 369, n (%) | 157 (42.5%) | 104 (39.8%) | 53 (49.1%) | 0.106 |
Vascular risk factors, n (%) | ||||
Hypertension, n = 369 | 310 (84.0) | 214 (82.0) | 96 (88.9) | 0.137 |
Newly diagnosed, n = 369 | 25 (6.78) | 20 (7.66) | 5 (4.63) | 0.408 |
Atrial fibrillation, n = 369 | 97 (26.3) | 50 (19.2) | 47 (43.5) | < 0.001 |
Current Smoking, n = 369 | 66 (17.9) | 53 (20.3) | 13 (12.0) | 0.082 |
Hypercholesterolemia, n = 369 | 211 (57.2) | 154 (59.0) | 57 (52.8) | 0.325 |
Diabetes mellitus, n = 369 | 86 (23.3) | 51 (19.5) | 35 (32.4) | 0.012 |
Coronary heart disease, n = 369 | 50 (13.6) | 28 (10.7) | 22 (20.4) | 0.022 |
Myocardial Infarction, n = 369 | 20 (5.42) | 10 (3.83) | 10 (9.26) | 0.065 |
Prior stroke or TIA, n = 369 | 93 (25.2) | 55 (21.1) | 38 (35.2) | 0.007 |
Positive Family history, n = 369 | 93 (25.2) | 69 (26.4) | 24 (22.2) | 0.474 |
Peripheral artery occlusive disease, n = 369 | 23 (6.23) | 7 (2.68) | 16 (14.8) | < 0.001 |
Kidney dysfunction, n = 369 | 115 (31.2) | 76 (29.1) | 39 (36.1) | 0.232 |
Liver dysfunction, n = 369 | 5 (1.36) | 2 (0.77) | 3 (2.78) | 0.152 |
Clinical data | ||||
NIHSS at entry, median (Q1-Q3), n = 369 | 2 (1–5) | 2 (0–4) | 5 (2–9) | < 0.0011 |
NIHSS at discharge, median (Q1-Q3), n = 369 | 1 (0–3) | 0 (0–2) | 2 (0–6) | < 0.0011 |
mRS at entry, mean ± SD, n = 369 | 2.31 ± 1.58 | 1.87 ± 1.45 | 3.37 ± 1.38 | < 0.001 |
mRS at discharge, mean ± SD, n = 369 | 1.38 ± 1.41 | 0.87 ± 1.06 | 2.61 ± 1.39 | < 0.001 |
Recanalization therapy, n (%) | ||||
Intravenous thrombolysis, n = 369 | 74 (20.1) | 49 (18.8) | 25 (23.1) | 0.417 |
Endovascular treatment, n = 369 | 29 (7.86) | 16 (6.13) | 13 (12.0) | 0.088 |
MRI Findings, n (%) | ||||
Lacunes, n = 361 | 153 (42.4) | 97 (37.7) | 56 (53.8) | < 0.001 |
WML (Fazekas score 2–3), n = 368 | 200 (54.9) | 126 (48.8) | 74 (69.8) | 0.003 |
CMB, n = 368 | 103 (28.0) | 68 (26.1) | 35 (32.7) | 0.244 |
cSVD (CMB a./o.WML), n = 368 | 229 (62.2) | 145 (55.6) | 84 (78.5) | < 0.001 |
Stroke etiology, n (%), n = 369 | ||||
Large artery disease | 70 (19.0) | 49 (18.8) | 21 (19.4) | 0.037 |
Cardioembolism | 137 (37.1) | 86 (33.0) | 51 (47.2) | 0.307 |
Small vessel occlusion | 29 (7.86) | 22 (8.43) | 7 (6.48) | 0.574 |
Other determined | 7 (1.90) | 4 (1.53) | 3 (2.78) | 0.508 |
undetermined | 126 (34.1) | 100 (38.3) | 26 (24.1) | 0.3149 |
Death within 1 year, n (%), n = 368 | 28 (7.61) | 0 | 28 (25.9%) | < 0.001 |
Recurrent stroke within 1 year, n (%), n = 368 | 42 (11.4) | 25 (9.58) | 17 (15.9) | 0.122 |
1calculated with Mann-Whitney-U-test |
At hospital discharge, 311 (73.5%) patients had a good clinical outcome and 112 (26.5%) a poor outcome (Table 1). WMH (Fazekas score 2–3) occurred significantly more often in patients with a poor outcome (74 (67.9%) vs 154 (50.5%), p < 0.001), whereas CMB did not (37 (33.6% vs 76 (24.6%), p = 0.087). Previous lacunes were more common in patients with a poor outcome than in those with a good outcome at hospital discharge, however there was no significant difference between these two groups (119 (39%) vs 53 (49.5%), p = 0.07). When comparing the burden of cSVD among these two groups (i.e., WMH and/or CMB), patients with a poor outcome were significantly more often affected by cSVD (86 (78.2%) vs 173 (56%), p < 0.001) (Table 1).
SBP and DBP detected on admission (SBPad; DBPad) did not differ significantly between the group with good and poor functional outcome (mean SBPad 161 ± 28 mmHg vs 166 ± 36 mmHg; p = 0.23; mean DBPad 84 ± 17 mmHg vs 85 ± 22 mmHg; p = 0.58)), the same was true for the mean SBP measured during the first 72 hours (SBP72h) at the stroke unit (mean SBP72h 145 ± 15 mmHg vs 144 ± 18 mmHg; p = 0.55). Interestingly, mean DBP of the first 72 hours (DBS72h) was significantly higher in patients with good outcome compared to those with poor outcome (mean DBP72h 74 ± 10 mmHg vs 70 ± 13 mmHg; p < 0.001) (Table 3). A trajectory of SBP and DBP of both groups during the first 72 hours is outlined in Fig. 2. Mean SBP decrease during the first 72 hours after cerebrovascular event did not differ significantly between patients with good and poor functional outcome (-16 ± 22 mmHg vs -22 ± 28 mmHg; p = 0.07). In contrast, mean DBP decrease over 72 hours was significantly higher in patients with poor outcome compared to those with good outcome at discharge (-10 ± 15 mmHg vs -15 ± 21 mmHg; p = 0.012) (Table 3).
All patients | Good outcome (mRS 0–2) | Poor outcome (mRS 3–6) | p-value | |
---|---|---|---|---|
At entry (n = 422) | ||||
SBP mmHg ± SD | 163 ± 30 | 161 ± 28 | 166 ± 36 | 0.2291 |
DBP mmHg ± SD | 84 ± 18 | 84 ± 17 | 85 ± 22 | 0.5761 |
SBP > 140 mmHg n (%) | 341 (80.8) | 255 (82.0) | 86 (77.5) | 0.3702 |
DBP > 90 mmHg n (%) | 180 (42.7) | 126 (40.5) | 54 (48.6) | 0.1692 |
Day 1 (n = 420) | ||||
SBP mmHg ± SD | 149 ± 20 | 149 ± 19 | 147 ± 22 | 0.3531 |
DBP mmHg ± SD | 75 ± 13 | 76 ± 12 | 72 ± 14 | 0.0231 |
SBP > 140 mmHg n (%) | 294 (70) | 221 (71.3) | 73 (66.4) | 0.3972 |
DBP > 90 mmHg n (%) | 64 (15.2) | 45 (14.5) | 19 (17.3) | 0.5912 |
Day 2 (n = 418) | ||||
SBP mmHg ± SD | 143 ± 17 | 144 ± 16 | 143 ± 20 | 0.7421 |
DBP mmHg ± SD | 72 ± 12 | 73 ± 12 | 69 ± 14 | 0.0021 |
SBP > 140 mmHg n (%) | 260 (62.2) | 192 (62.3) | 68 (61.8) | 0.9992 |
DBP > 90 mmHg n (%) | 36 (8,6) | 27 (8.8) | 9 (8.2) | 0.9992 |
Day 3 (n = 414) | ||||
SBP mmHg ± SD | 143 ± 17 | 143 ± 16 | 142 ± 19 | 0.8721 |
DBP mmHg ± SD | 72 ± 12 | 74 ± 11 | 69 ± 14 | 0.0011 |
SBP > 140 mmHg n (%) | 238 (57.5) | 175 (57.6) | 63 (57.3) | 0.9992 |
DBP > 90 mmHg n (%) | 30 (7.3) | 22 (7.2) | 8 (7.3) | 0.9992 |
Ø 72 h (n = 420) | ||||
SBP mmHg ± SD | 145 ± 16 | 145 ± 15 | 144 ± 18 | 0.5481 |
DBP mmHg ± SD | 73 ± 11 | 74 ± 10 | 70 ± 13 | 0.0011 |
BP decrease over 72 h, reference BP at entry | ||||
SBP mmHg ± SD | -17.6 ± 24 | -16.1 ± 22 | -21.6 ± 28 | 0.0691 |
DBP mmHg ± SD | -11.1 ± 17 | -9.7 ± 15 | -15.3 ± 21 | 0.0121 |
1calculated with t-Test, 2calculated with Chi2-Test or Fishers-Exact-Test when expected frequencies were < 5. |
In multivariable logistic regression, significant predictors for poor clinical outcome at discharge are mean DBP measured during the first 72 hours after admission (OR 0.73; 95%CI 0.54–0.99) and cSVD (OR 2.07; 95%CI 1.17–3.68) (Fig. 3). Additionally, we found a significant U-shaped dependence of the mean DBP72h and clinical outcome (Fig. 4). Mean DBP < 66 mmHg and mean DBP > 80 mmHg over 72 hours were associated with a poor outcome at discharge.
One year after cerebrovascular event, new ischemic stroke or TIA was reported in 11.9% of patients with a good and in 9.89% of those with a poor clinical outcome at discharge (p = 0.62). Among patients with good and poor outcome, 5.78% and 12.9%, respectively, died within one year (p = 0.035).
Twelve months after ischemic stroke or TIA, good functional outcome was found in 261 (70.7%) patients and poor outcome in 108 (29.3%) patients (Table 2). Among patients with a poor outcome, WMH (Fazekas score 2–3) were more frequent observed than in those with a good outcome at 12 months (74 (69.8%) vs 126 (48.8%), p < 0.001). The same was true for the presence of lacunes (56 (53.8%) vs 97 (37.7%), p = 0.007). CMB occurred in both, patients with poor and good outcome almost in the same frequency (35 (32.7%) vs 65 (26.1%), p = 0.24). Over all, the burden of cSVD was higher in patients with poor outcome compared to the group with good outcome at 12 months (84 (78.5%) vs 145 (55.6%), p < 0.001) (Table 2).
We found no significant difference between patients with good and poor functional outcome in respect to mean SBPad (161 ± 28 mmHg vs 166 ± 33 mmHg, p = 0.13) and mean DBPad (84 ± 16 mmHg vs 85 ± 22 mmHg, p = 0.73). SBP72h was similar between patients with good and poor outcome at 12 months (mean SBP72h 145 ± 16 mmHg vs 146 ± 16 mmHg; p = 0.86). In contrast, patients with a good outcome showed a significantly higher mean DBP72h when comparing to patients with a poor outcome (mean DBP72h 75 ± 10 mmHg vs 69 ± 10 mmHg; p < 0.001) (Table 4).
All patients | Good outcome (mRS 0–2) | Poor outcome (mRS 3–6) | p-value | |
---|---|---|---|---|
At entry (n = 422) | ||||
SBP mmHg ± SD | 162 ± 30 | 161 ± 28 | 166 ± 33 | 0,1331 |
DBP mmHg ± SD | 84 ± 18 | 84 ± 16 | 85 ± 22 | 0,7251 |
SBP > 140 mmHg n (%) | 300 (81.3) | 211 (80.8) | 89 (82.4) | 0,8382 |
DBP > 90 mmHg n (%) | 157 (42.5) | 111 (42.5) | 46 (42.6) | 0,9992 |
Day 1 (n = 420) | ||||
SBP mmHg ± SD | 149 ± 20 | 149 ± 19,4 | 148 ± 20 | 0,8161 |
DBP mmHg ± SD | 75 ± 12 | 76 ± 12 | 71 ± 12 | < 0,0011 |
SBP > 140 mmHg n (%) | 260 (70.7) | 184 (70.8) | 76 (70.4) | 0,9992 |
DBP > 90 mmHg n (%) | 56 (15.2) | 45 (17.3) | 11 (10.2) | 0,1162 |
Day 2 (n = 418) | ||||
SBP mmHg ± SD | 144 ± 17 | 144 ± 17 | 144 ± 17 | 0,6211 |
DBP mmHg ± SD | 72 ± 12 | 74 ± 12 | 70 ± 11 | < 0,0011 |
SBP > 140 mmHg n (%) | 260 (62.2) | 162 (62.5) | 69 (63.9) | 0,9022 |
DBP > 90 mmHg n (%) | 36 (8.6) | 25 (9.7) | 5 (4.6) | 0,1642 |
Day 3 (n = 414) | ||||
SBP mmHg ± SD | 143 ± 17 | 142 ± 16 | 144 ± 16 | 0,3091 |
DBP mmHg ± SD | 72 ± 12 | 74 ± 11 | 68 ± 12 | < 0,0011 |
SBP > 140 mmHg n (%) | 238 (57.5) | 143 (55.9) | 68 (63.0) | 0,2552 |
DBP > 90 mmHg n (%) | 30 (7.3) | 19 (7.4) | 7 (6.5) | 0,9242 |
Ø 72 h (n = 420) | ||||
SBP mmHg ± SD | 145 ± 16 | 145 ± 16 | 146 ± 16 | 0,6831 |
DBP mmHg ± SD | 73 ± 11 | 75 ± 10 | 70 ± 10 | < 0,0011 |
BP decrease over 72 h, reference BP at entry | ||||
SBP mmHg ± SD | -17.3 ± 23 | -15.8 ± 22 | -20.6 ± 26 | 0.0901 |
DBP mmHg ± SD | -11.1 ± 17 | -9.4 ± 15 | -15.5 ± 21 | 0.0071 |
1calculated with t-Test, 2calculated with Chi2-Test or Fishers-Exact-Test when expected frequencies were < 5. |
Mean SBP decrease during the first 72 hours after cerebrovascular event did not show a statistic difference between patients with good and poor functional outcome (-16 ± 22 mmHg vs -21 ± 26 mmHg; p = 0.09). However, mean DBP decrease over 72 hours was significantly higher in patients with poor outcome compared to those with good outcome at 12 months (-9 ± 15 mmHg vs -15 ± 21 mmHg; p = 0.007) (Table 4).
In multivariable logistic regression, significant and predictors for poor clinical outcome at 12 months are mean DBP72h (OR 0.59; 95%CI 0.41–0.86; p = 0.018) and age (OR 2.7; 95%CI 1.71–4.27; p < 0.001) (Fig. 5). The burden of cSVD did not significantly predict poor outcome at 12 months; nonetheless, there was a statistical trend (OR 1.69; 95%CI 0.94–3.04; p = 0.08) (Fig. 5).
Twelve months after cerebrovascular event, recurrent ischemic stroke or TIA was diagnosed in 9.58% of patients with a good outcome and in 15.9% of those with a poor clinical outcome (p = 0.09).
This prospective study of 423 patients with an AIS or TIA showed that cSVD burden was significantly higher in patients with a poor functional outcome at discharge and 12 months after cerebrovascular event. However, neither SBPad nor mean SBP72h was significantly related to functional outcome at discharge or at 12 months after index event. An unexpected finding of the present study was a significant association between mean DBP72h and functional outcome at discharge and 12 months afterwards.
A growing number of studies suggest that cSVD in patients with AIS is independently associated with poor functional outcome in the short and long term after cerebrovascular event 33–35 which is in line with our findings. The impact of cSVD on functional outcome after AIS is poorly understood. It has been shown that severe cSVD may lead to a reduction of cerebral blood flow and is associated with impaired cerebral autoregulation 24,36,37. Thus, one might argue that low SBP during the acute phase of IS may result in a drop in cerebral blood flow of those patients with severe cSVD, which in itself may result in an increase of cerebral tissue damage and therefore in a poor functional outcome. Though, we did not find a statistically significant relationship between SBPad or SBP72h and functional outcome in stroke patients with or without cSVD, which was a surprising finding. This might be due to the small sample size in this study. Additionally, we included patients with AIS as well as with TIA who were treated for hypertension; furthermore, some patients had a mRS > 0 prior to study enrollment, which might – to some extent – influence the results. Another reason for the missing effect of SBP on functional outcome in patients with cSVD could be the fact that SBP only impacts functional outcome when cerebral perfusion is severely compromised as one would expect in patients with high burden of cSVD (e.g., Fazekas grade 3, multiple lacunes and/or CMB). Importantly, we combined patients with Fazekas grade 2 and 3 in one group which could have biased the results. In addition, cSVD burden was determined by using a qualitative and not by a quantitative approach, i.e., we did not assess the volume of WMH in our patients. However, a higher Fazekas scale score is highly correlated with higher WMH volume 38. Furthermore, different regional distribution of WMH load and/or locations of stroke lesions might also impact functional outcome 39. On the other hand, a large randomized trial (n = 3035) has also revealed that SBP is not likely to explain a relationship between cSVD and poor functional outcome after stroke when adjusting for age 40. In contrast to our study, the main focus of the aforementioned study was on SBP variability during the first 24 hours after stroke.
Although SBP decreased over the first 72 hours after admission, there was no statistically significant relationship between SBP decline and functional outcome at discharge and at 12 months after AIS, and thus, an interaction between these parameters and cSVD burden was not expected. Our results are in contrast with findings of a previously published study, showing that a large change of SBP over the first 24 hours after stroke is related with a poor functional outcome in the short term (i.e. at day 7 after stroke) as well as in the long term (90 days after stroke) 22. However, patients with cSVD burden were not particularly addressed in that study.
Little is known about the impact of DBP on functional outcome in stroke survivors with and without cSVD. Here, we found that mean DBP72h was significantly lower in stroke patients with cSVD. Moreover, DBP72h and cSVD burden were associated with a poor outcome at discharge. In contrast to our findings, a previously published trial revealed no consistent association between the level of DBP measured over 24 hours and functional outcome, however, in the aforementioned trial, DBP was generally lower in patients with a poor outcome at day 7 and at day 90 22. In another previously published study, DBP variability was associated with poor functional outcome at hospital discharge 41. Of note, the aforementioned studies did not focus in particular on stroke patients with/without cSVD in their analyses. Göthel-Ezzeiani and coworkers also investigated the impact of WMH and blood pressure on clinical outcome. They found a relationship between DBP and mortality but none between DBP and functional outcome at 3 months 42; of note, only stroke patients undergoing mechanical recanalization were included in their study. In the present study, there was still a significant linear relationship between DBP72h and late functional outcome (at 12 months) but only a statistical trend for cSVD burden when adjusting for sex and age. In contrast, a previous trial reported similar DBP measured over 24 hours after stroke in patients with good and poor late functional outcome (at 3 months) 43. However, that study did not specifically investigate stroke survivors presenting cSVD and enrolled only stroke patients treated with intravenous thrombolysis.
Additionally, we observed a U-shaped relationship between mean DBP72h and functional outcome at discharge among stroke patients with and without cSVD meaning that only a DBP of about 60–80 mmHg was related to a better functional outcome. A U-shaped relationship between DBP on admission and early deterioration as well as functional outcome at 3 months 5 or 6 months 44 was provided by previous studies. In contrast to our study, the cutoff value for DBP was higher, namely at 100–110 mmHg 5 or 87.8–95 mmHg, respectively 44. In the latter study however, this association was no longer significant, when assessed with logistic regression. Other large studies on patients with ischemic stroke (n > 300’000 patients) 45 or TIA (n > 200’000 patients) 46 reported a U-shaped relationship between DBP on admission and independent ambulation at discharge, likelihood of being discharged at home, and in-hospital death such that below and above 70 mmHg the unadjusted and adjusted odds of these outcomes increased. This value is in the same range as observed in our study. In a cohort study of patients with ischemic stroke treated with endovascular therapy, DBP on admission and functional outcome at 3 months showed a J-shaped relationship with an inflection point at the median value of DBP of 81 mmHg 47. In contrast to our work, cSVD was not in the scope of these studies.
The reason why there was a U-shaped relationship between DBP and functional outcome whereas this was not true for SBP in the present study remains elusive. One possible explanation of this observation could be the small number of patients. The U-shaped association between low and high DBP and poor functional outcome might be closely linked to the state of cerebral perfusion for several reasons. First of all, there is some evidence that cerebral perfusion might be lower in patients with arterial hypertension irrespective of the presence of WMH compared to healthy controls 48. Patients with WMH have been reported to exhibit a reduction of cerebral blood flow of the white matter (up to 38%) compared with those without WMH 49,50. There was even a decrease in CBF within normal appearing white matter surrounding the WMH 51. On the other hand, levels of cerebral perfusion especially in the early phase of AIS display a reverse U-shaped curve depending on SBP and DBP levels and – in turn – impact functional outcome at 3 months after stroke 52. The most favorable functional outcome was associated with a SBP between 161 to 177 mmHg and DBP ranging from 103 to 114 mmHg 52. Interestingly, Park and Ovbiagele found also an independent association between DBP and vascular outcomes 2 years after non-cardioembolic stroke, showing that DBP < 70 mmHg as well as DBP > 90 mmHg was linked to an increased risk of vascular events 53. Although this study revealed that patients with low DBP had higher comorbidities of diabetes mellitus, heart failure and carotid artery disease, DBP < 70 mmHg (but not DBP > 90 mmHg) was an independent predictor of vascular events, in particular recurrent stroke, after multivariable adjustment 53. Notably, when the BP in the brachial artery is 117/75 mmHg in normotensive subjects, the pressure in the lenticulostriate vascular bed would be 91/58 mmHg and that in the same-size parietal arterioles 59/38 mmHg according to the calculation of Blanco and coworkers 54. Given that there is a BP gradient in the brain, a decrease in peripheral DBP may result in a critical undersupply of cerebral tissue, since more than half of cerebral perfusion is during diastole 55.
The present study has some limitations. First, the sample size of this work is relatively small. Second, we included patients receiving intravenous thrombolysis and/or undergoing mechanical thrombectomy as well as those with neither of these acute stroke therapies. However, this reflects the real, less than ideal clinical everyday practice. Third, the patients showed mild symptoms of stroke making a generalization of the study data difficult. Fourth, no additional cerebral MRI was performed at 12 months (except in patients with recurrent stroke or TIA) and thus, new or enlarged WMH were not able to detect. Notably, WMH may regress over time after stroke and thus, provide potentially better functional and brain tissue outcome 56. The strength of this work are the prospective study design and well-characterized patients. Furthermore, we used mean SBP and DBP over the first 72 hours along with BP on admission. In contrast, a plenty of studies investigating the effect of acute-phase BP on functional outcome after AIS have used a single BP value (mainly the BP on admission) or BP values over the first 24 hours as a predictor for the functional outcome. However, different mechanisms may be responsible for an elevation of BP values measured on admission. Beside a physiological response to cerebral ischemia, untreated arterial hypertension as well as increased sympathetic activation, fear of serious illness and hospitalization may contribute to increased BP values on admission 57,58. Moreover, data collection and functional assessment by means of a structured telephone interview were carried out by one mRS-experienced person (S. G.).
In conclusion, this observational prospective study demonstrates that cSVD predicts a poor outcome among stroke survivors and thus corroborates findings of previous studies. We did not find a statistically significant relationship between cSVD, level of SBP, and functional outcome probably due to the fact that SBPad and SBP72h values ranged between 145 and 160 mmHg, values that have been associated with a good functional outcome after AIS. However, DBP and cSVD were associated with poor outcome depending on the level of DBP; additionally, DBP showed a U-shaped relationship with functional outcome. This may suggest an individualized stroke care by either lowering or elevating DBP in order to influence functional outcome. However additional large randomized studies are required to further investigate an association between DBP, cSVD and functional outcome after IS.
This study was funded by the Interdisziplinäres Zentrum für Klinische Forschung (IZKF), University Hospital, Würzburg. This publication was supported by the Open Access Publication Fund of the University of Würzburg.
Author contributions
Conceived and designed the study: FF, SG. Performed the study: SG, AS, FF. Analyzed the data: SG, AS, FF. Contributed analysis tools: SG, FF, AS. Wrote the paper: SG, AS, FF.
The authors have nothing to disclose and declare no competing interests..
Data availability
All data generated or analyzed during this study are included in this published article.
Corresponding Author
Correspondence to Felix Fluri ([email protected])