Abstract
It is generally known that acute minor stroke and transient ischemic attack (TIA) seem to be benign. However, their occurrence in patients with steno‐occlusive arterial disease may result in early neurological deterioration (END). We aimed to elucidate the effect of blood pressure variability (BPV) on the development of END. Consecutive acute minor stroke and TIA patients within 24 hours of onset were prospectively recruited from the Affiliated Hospital of Yangzhou University between Aug 2015 and Feb 2019. END was defined as an NIHSS score increased ≥1 during the first 72 hours compared with the initial NIHSS score. During this period, the mean, maximum (max), the difference between the maximum and minimum (max‐min), the SD, and coefficient of variation of BP (BPCV) were calculated. Of the 160 total patients enrolled in the study (mean age, 68.01 ± 9.33 years; 50.6% female), 52 (32.5%) patients occurred END during the first 72h after admission. To express the BPV as a categorical variable, we classified the subjects into one of four groups, representing four quartiles of BPV. In the multivariable analyses, the lowest quartiles were considered as reference groups. The results showed that patients who fell in the fourth quartile (SBPmax‐min:OR = 3.289, 95% CI 1.147‐9.430; SBPSD:OR = 3.313, 95% CI 1.041‐10.547; SBPCV:OR = 3.425, 95% CI 1.164‐10.077; DBPSD:OR = 3.124, 95% CI 1.065‐9.158) had a significantly higher risk of END after adjusting the variables (age, female, diabetes mellitus, atrial fibrillation, and CRP with P values <.1 in univariate analyses). Our study demonstrated that the acute in‐hospital BPV was associated with the development of END in acute minor stroke and TIA with steno‐occlusive arterial disease.
Keywords: blood pressure, blood pressure variability, early neurological deterioration, minor stroke, transient ischemic attack
1. INTRODUCTION
Minor stroke and transient ischemic attack (TIA) are usually regarded as a whole to study because of the similar pathophysiological mechanism and epidemical characteristics.1, 2 It is reported that minor ischemic stroke and TIA account for ≈65% of all acute ischemic cerebrovascular events.3 Although minor stroke and TIA seem to be benign, recent studies have shown that a significant proportion of patients with steno‐occlusive arterial disease is in unstable clinical state and has high risks of recurrent cerebrovascular events or early neurological deterioration (END) in the hospital, resulting in major physical disability.4, 5, 6, 7 Therefore, it is of great importance to identify factors associated with END in patients with acute minor stroke or TIA due to steno‐occlusive arterial disease. Based on the previous studies, several clinical and biological factors, such as older age, the initial neurological severity, diabetes mellitus, and blood pressure, might influent the development of END in patients with general ischemic stroke.8, 9, 10, 11 To our best known, few studies focus on patients with acute minor stroke or TIA due to steno‐occlusive arterial disease.
It is well known that BP is generally very dynamic and fluctuates considerably during the first several hours of acute ischemic stroke.10, 11 A failure of cerebral autoregulation occurs when there is a narrowing or blockage in the main arteries feeding blood to the brain. And at this moment, blood flow in ischemic brain regions is mainly determined by the systemic arterial pressure. Therefore, even minor fluctuations in BP may lead to under‐ or over‐perfusion of ischemic brain which is closely associated with the clinical outcomes of patients. BP variability (BPV), as a common cause of target organ injury, had got more and more attention. In the field of cardiovascular disease, BPV is becoming increasingly recognized as an important predictor for future cardiovascular events.12, 13, 14 Recent several studies also tell us that high BPV is not only predictive of stroke but also clinical outcomes following general ischemic stroke.15, 16 However, to the best of our knowledge, there are limited data on the relationship between BPV and END following acute minor stroke or TIA. The relationship between BPV and END after acute minor stroke or TIA due to steno‐occlusive arterial disease remains controversial.
In this present study, we attempted to identify the association between BPV and END in patients with acute minor stroke or TIA due to steno‐occlusive arterial disease.
2. SUBJECTS AND METHODS
2.1. Patient selection
Between Aug 2015 and Feb 2019, consecutive patients with acute minor stroke or TIA were prospectively recruited from the Department of Neurology, the Affiliated Hospital of Yangzhou University. Inclusion criteria were (a) age older 18‐80 years; (b) patients within 24 hours after onset of minor stroke (National Institutes of Health Stroke Scale [NIHSS] ≤ 3) or TIA; (c) magnetic resonance imaging (MRI) conducted during the first 24 hours after admission; (d) patients who had arterial steno‐occlusion on MRA or CT angiograms (>50% luminal stenosis or occlusion of major responsible large artery). We excluded patients who met the following criteria: (a) Concomitant atherosclerosis of other cerebrocervical arteries except for those related to the minor stroke or TIA; (b) other etiologies such as vasculitis, moyamoya disease, or cancer‐related stroke; (c) a score of more than 2 on modified Rankin scale (scores range from 0[no symptoms] to 6 [death]) before the stroke; and (d) early discharge or had inadequate BP data, defined as BP measured fewer than 40 times during the first 72 hours. The study was approved by Ethics Committees of the Affiliated Hospital of Yangzhou University, and written informed consent was obtained from each patient.
2.2. Demographic and clinical assessment
Detailed demographic information, clinical characteristics, previous medication history (including hypertension, diabetes mellitus, atrial fibrillation and coronary artery disease, stroke and TIA), and laboratory data including fasting plasma glucose (FPG), hsCRP, and neuroimaging data were all analyzed. Hypertension referred to two conditions: no antihypertensive drugs but blood pressure ≥140/90 mm Hg on repeated measurements, or current use of antihypertensive medications; Diabetes mellitus was defined as a fasting blood glucose ≥126 mg/dL, positive ≥75 g oral glucose tolerance test result, or current treatment with oral hypoglycemic drugs or insulin to control blood glucose. Smoking was considered for individuals currently smoking or with <6 months from quitting. Alcohol consumption referred to current drinking habits or less than 6 months from quitting. History of stroke, TIA, atrial fibrillation, and coronary artery disease was also recorded.
2.3. Cerebral atherosclerosis evaluation
According to our imaging protocol, the infarct lesion was evaluated using a 3.0‐T (Magnetom Avanto; Siemens) MRI including T1‐weighted imaging (T1WI), T2‐weighted imaging (T2WI), diffusion‐weighted imaging (DWI), fluid‐attenuated inversion recovery (FLAIR), and magnetic resonance angiography (MRA) during the first 24 hours after admission. The status (>50% luminal narrowing or occlusion) of the responsible large artery was analyzed by using either MRA or computer tomography angiography (CTA). Generally, the intracranial atherosclerotic stenosis was degreed according to the WASID criteria, while the extracranial atherosclerotic stenosis according to the NASCET criteria.17, 18 The presence and the degree of cerebrocervical artery stenosis were analyzed by consensus among two physicians who were blinded to the clinical status.
2.4. BP measurements and management
We studied the systolic BP (SBP) and diastolic BP (DBP) data obtained during the first 72 hours after admission. In the stroke unit, BP was measured in the same side depending on the patient's conditions, including paralysis and intravenous infusion. And, a BP in the nonparalyzed arm was measured by using a noninvasive BP monitoring device and recorded automatically into the electronic medical record. For each patient, BP values with ≥40 measurements were used to calculate the variability indices.
The BP profile was described using various parameters for each of SBP and DBP: the mean (an average of values BP), maximum (BPmax), and minimum (BPmin) values for the SBP and DBP were measured for each individual. Differences between the maximum and minimum (BPmax‐min), SD (BPSD), and coefficient of variation (equal to [SD × 100]/mean, BPCV) were calculated and consider to be the parameters of BPV.
2.5. Early neurological deterioration
The evaluation of neurological deficits was conducted by certified investigators blind to clinical and imaging information using the NIHSS at admission and continued during the following 72 hours 1‐3 times a day, and the detailed NIHSS score was recorded. END was defined as any worsening of presenting neurological deficits detected on a full neurological examination or recurrence of deficits not attributable to any other medical condition (such as fever, infection, or metabolic derangement).
2.6. Statistical analysis
SPSS 16.0 for Windows was used for all statistical analysis. Continuous variables of baseline characteristics were compared using student t‐test or Mann‐Whitney test and described by their mean ± SD or median (interquartile range [IQR]). Categorical variables of baseline characteristics were compared using Chi‐square test or Fisher's exact and presented as the number (%) of subjects. To express the BPV as a categorical variable, we classified the subjects into one of four groups, representing four quartiles of BPV and considered the first quartile as reference groups. Logistic regression model was built to determine the independent association between BPV and END by adjusting the following variables with a P value ≤ .1 in univariate analysis. P < .05 was considered statistically significant in this study.
3. RESULT
3.1. Baseline characteristics
A total of 203 patients met the inclusion criteria were screened. Of those, 43 patients were excluded, 28 because of concomitant moderate‐severe carotid stenosis, 11 because of the other etiologies under the minor and TIA, such as vasculitis, moyamoya disease, or cancer‐related stroke, and 4 because of the inadequate BP data. Thus, 160 patients were included, the average age was 68.01 ± 9.33 years, and 50.6% was female. The baseline characteristics of 160 included patients are listed in Table 1. Hypertension was present in 108 patients (67.5%), diabetes mellitus in 56 patients (35.0%), AF in 24 patients (15.0%), current smoking in 60 patients (37.5%), and drinking in patients 33 (20.6%). Forty‐one patients (25.6%) and 27 patients (16.9%) had histories of ischemic heart disease and stroke‐TIA, respectively.
Table 1.
Comparison of baseline characteristics according to the presence of END
| Characteristics | END (N = 52) | No END (N = 108) | P |
|---|---|---|---|
| General clinical characteristics | |||
| Age, years, mean (SD) | 70.37 ± 7.21 | 66.88 ± 10.03 | .026 |
| Female, N (%) | 34 (65.4) | 47 (43.5) | .010 |
| Hypertension, N (%) | 37 (71.2) | 71 (65.7) | .494 |
| Diabetes mellitus, N (%) | 27 (51.9) | 29 (26.9) | .002 |
| Ischemic heart disease, N (%) | 16 (30.8) | 25 (23.1) | .301 |
| History of TIA‐S, N (%) | 11 (21.2) | 16 (14.8) | .316 |
| Atrial fibrillation, N (%) | 12 (23.1) | 12 (11.1) | .047 |
| Smoking, N (%) | 19 (36.5) | 41 (38.0) | .862 |
| Drinking, N (%) | 12 (23.1) | 21 (19.4) | .595 |
| Initial NIHSS, median (IQR) | 1 (0‐2) | 1 (0‐2) | .704 |
| Index event, N (%) | |||
| Minor stroke | 32 (61.5) | 64 (59.3) | .783 |
| TIA | 20 (38.5) | 44 (40.7) | |
| Hematological parameters | |||
| WBC (109, ± s) | 8.02 ± 2.60 | 7.42 ± 2.79 | .192 |
| RBC (×1012, ± s) | 4.44 ± 0.64 | 4.51 ± 0.58 | .450 |
| FBG (mmol/L, ± s) | 9.60 ± 4.52 | 8.66 ± 4.27 | .203 |
| CRP (mg/L, ± s) | 16.85 ± 14.47 | 13.11 ± 11.74 | .082 |
| TC, mmol/L | 4.36 ± 1.01 | 4.40 ± 1.11 | .850 |
| TG, (mmol/L, ± s) | 1.86 ± 1.25 | 1.88 ± 1.32 | .927 |
| HDL, (mmol/L, ± s) | 1.08 ± 0.23 | 1.11 ± 0.28 | .380 |
| LDL, (mmol/L, ± s) | 2.54 ± 0.89 | 2.40 ± 0.93 | .368 |
| Urea, (mmol/L, ± s) | 6.00 ± 1.80 | 5.89 ± 1.75 | .702 |
| Cr, (mmol/L, ± s) | 75.25 ± 20.94 | 73.41 ± 18.38 | .567 |
| Current medications | |||
| Mono antiplatelet therapy, N (%) | 36 (69.2) | 76 (70.4) | .883 |
| Dual‐antiplatelet therapy, N (%) | 16 (30.8) | 32 (29.6) | |
Abbreviations: Cr, creatinine; END, early neurological deterioration; FBG, fasting blood glucose; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; RBC, red blood cell; TC, total cholesterol; TG, triglycerides; TIA, Transient Ischemic Attack; WBC, white blood cell.
3.2. The association between BPV and END
Of the 160 patients, 52 (32.5%) patients developed END during the first 72h after admission. In patients with END, the age (P = .026), the proportion of female (P = .010), diabetes mellitus (P = .002), and atrial fibrillation (P = .047) were higher than that in patients without END according to univariate analysis (Table 1). In this study, we regarded the BPV as a categorical variable and classified the subjects into one of four groups, representing four quartiles of BPV. The proportion of END was significantly different between quartiles of SBPmean, SBPmax, SBPmax‐min, SBPSD, SBPCV, DBPmax, DBPmax‐min, DBPSD, and DBPCV using a chi‐square test (Figures 1 and 2).
Figure 1.
Proportions of patients developing END according to SBP parameters. P values for the association between SBP quintiles and END according to the chi‐square test: P = .171 for SBPmean; P = .227 for SBPmax; P = .022 for SBPmax‐min; P = .038 for SBPSD; P = .038 for SBPCV; CV, coefficient of variation; END, early neurological deterioration; max, maximum; min, minimum; Q, quartile; Q1, the first quartile; Q2, the second quartile; Q3, the third quartile; Q4, the fourth quartile; SBP, systolic blood pressure; SD, standard deviation
Figure 2.
Proportions of patients developing END according to DBP parameters. P values for the association between DBP quintiles and END according to the chi‐square test: P = .434 for DBPmean; P = .096 for DBPmax; P = .013 for DBPmax‐min; P = .004 for DBPSD; P = .013 for DBPCV; CV, coefficient of variation; DBP, diastolic blood pressure; max, maximum; min, minimum; Q, quartile; Q1, the first quartile; Q2, the second quartile; Q3, the third quartile; Q4, the fourth quartile; SD: standard deviation
In the multivariable logistic regression analyses, the lowest quartiles were considered as reference groups (Table 2). The results showed that patients who fell in the fourth quartile (SBPmax‐min:OR = 3.289, 95% CI 1.147‐9.430; SBPSD:OR = 3.313, 95% CI 1.041‐10.547; SBPCV:OR = 3.425, 95% CI 1.164‐10.077; DBPSD:OR = 3.124, 95% CI 1.065‐9.158) had a significantly higher risk of END after adjusting the variables (age, female, diabetes mellitus, atrial fibrillation, and CRP [P = .082]) with P values < .1 in univariate analyses.
Table 2.
Multivariable analysis of the associations between BP parameters and the development of END
| SBP parameters | Unadjusted model | Adjusted modela | DBP parameters | Unadjusted model | Adjusted modela |
|---|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | ||
| SBPmean | DBPmean | ||||
| Q1 | 1 | 1 | Q1 | 1 | 1 |
| Q2 | 1.714 (0.613‐4.794) | 2.140 (0.687‐6.668) | Q2 | 2.067 (0.776‐5.507) | 1.828 (0.600‐5.568) |
| Q3 | 2.667 (0.981‐7.250) | 2.005 (0.673‐7.973) | Q3 | 1.658 (0.614‐4.482) | 1.392 (0.465‐4.168) |
| Q4 | 2.667 (0.981‐7.250) | 2.272 (0.755‐6.843) | Q4 | 2.067 (0.776‐5.507) | 2.280 (0.799‐7.086) |
| SBPmax | DBPmax | ||||
| Q1 | 1 | 1 | Q1 | 1 | 1 |
| Q2 | 1.524 (0.559‐4.151) | 1.644 (0.555‐4.869) | Q2 | 0.758 (0.283‐2.026) | 0.625 (0.209‐1.869) |
| Q3 | 1.975 (0.747‐5.222) | 1.613 (0.550‐4.773) | Q3 | 1.948 (0.748‐5.074) | 2.393 (0.820‐6.983) |
| Q4 | 2.709 (1.012‐7.253) | 2.724 (0.921‐8.058) | Q4 | 2.078 (0.805‐5.367) | 1.595 (0.549‐4.636) |
| SBPmax‐min | DBPmax‐min | ||||
| Q1 | 1 | 1 | Q1 | 1 | 1 |
| Q2 | 1.550 (0.584‐4.111) | 1.502 (0.518‐4.357) | Q2 | 1.234 (0.423‐3.596) | 0.919 (0.288‐2.926) |
| Q3 | 0.872 (0.312‐2.435) | 0.571 (0.182‐1.799) | Q3 | 3.477 (1.291‐9.363) | 3.540 (1.206‐10.397) |
| Q4 | 3.263 (1.262‐8.437) | 3.289 (1.147‐9.430) | Q4 | 3.440 (1.264‐9.362) | 2.413 (0.797‐7.301) |
| SBPSD | DBPSD | ||||
| Q1 | 1 | 1 | Q1 | 1 | 1 |
| Q2 | 1.000 (0.350‐2.856) | 0.640 (0.199‐2.065) | Q2 | 1.000 (0.334‐2.991) | 0.661 (0.195‐2.236) |
| Q3 | 2.153 (0.850‐5.450) | 1.381 (0.502‐3.795) | Q3 | 2.400 (0.879‐6.556) | 2.461 (0.842‐7.189) |
| Q4 | 3.444 (1.207‐9.829) | 3.313 (1.041‐10.547) | Q4 | 4.421 (1.638‐11.930) | 3.124 (1.065‐9.158) |
| SBPCV | DBPCV | ||||
| Q1 | 1 | 1 | Q1 | 1 | 1 |
| Q2 | 1.333 (0.464‐3.828) | 1.057 (0.337‐3.316) | Q2 | 1.103 (0.385‐3.159) | 0.555 (0.169‐1.819) |
| Q3 | 2.400 (0.879‐6.556) | 1.951 (0.650‐5.854) | Q3 | 1.651 (0.614‐4.441) | 1.398 (0.483‐4.048) |
| Q4 | 3.619 (1.341‐9.765) | 3.425 (1.164‐10.077) | Q4 | 3.930 (1.497‐10.319) | 2.553 (0.892‐7.309) |
Abbreviations: Cr, creatinine; CV, coefficient of variation; DBP, diastolic blood pressure; END, early neurological deterioration; FBG, fasting blood glucose; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein; max, maximum; min, minimum; Q, quartile; Q1, the first quartile; Q2, the second quartile; Q3, the third quartile; Q4, the fourth quartile; RBC, red blood cell; SBP, systolic blood pressure; SD, standard deviation; TC, total cholesterol; TG, triglycerides; TIA, Transient Ischemic Attack; WBC, white blood cell.
Adjusted variables were age, female, diabetes mellitus, atrial fibrillation, and CRP.
4. DISCUSSION
It is reported that END observed in the acute phase of the stroke and usually leading to an unexpectedly severe disability status, is not rare in acute stroke patients.19, 20, 21 Until now, the pathophysiology under END is yet incompletely illustrated. In addition, as yet no medical intervention proven to be useful in preventing the clinical phenomenon, the END following acute stroke was considered as an important unresolved clinical problem. A few clinical studies aimed at detecting predictors of END in general stroke that may help to identify patients who are at risk of worsening. However, few studies had been concerned with patients suffered from minor stroke or TIA. The present study was aimed to explore the association between BPV and END in a large series of consecutive patients with minor stroke or TIA. To prove the association of BPV and END, we adopted a definition of END as a ≥1‐point increase in NIHSS score during the first 72 hours after admission. And, the rate of END was 32.5% in this study, which was consistent with the rates in previous studies.4, 5, 6, 7, 8, 9, 10 And also, our findings were similar to that in the Chungs' study.16 Both studies suggested that the acute in‐hospital BPV was strongly associated with the risk of having a END. To the best known of our knowledge, this was the first study to investigate the role of BPV in the prediction of END in acute minor stroke or TIA, which might help identify people at high risk for END in a specific population of patients. In addition, the results of the study suggested that the outcome of minor stroke and TIA was not always favorable as we think.
It was very known that approximately 80% of patients present with elevated blood pressure during the acute stage of stroke. Studies had demonstrated that increased BP in the acute stage of ischemic stroke may be associated with poor functional outcome because there is augmentation of cerebral edema, hemorrhagic transformation, or stroke recurrence.22, 23, 24, 25, 26 In addition, variability of BP in the acute stage of ischemic stroke is also reported to be associated with stroke outcome with respect to mortality, lesion growth on diffusion‐weighted MRI, functional outcome, and symptomatic hemorrhagic transformation.15, 16 In this study, BPV was proved to be related to the development of END in patients with acute minor stroke or TIA due to steno‐occlusive arterial disease.
The conclusion of our study was similar to a previous study that demonstrated an independent association between BPV and END in general ischemic stroke.16 Autonomic dysfunction during the acute stage of acute ischemic stroke had been extensively analyzed. During this period, the human brain has a decreased ability to auto‐regulate. BP is generally very dynamic and experiences important changes. And even minor fluctuations in BP may lead to important changes in cerebral perfusion via collaterals, especially in stoke with steno‐occlusive arterial disease.27, 28, 29 Therefore, we thought that BPV may contribute to the development of END by altering the hemodynamic status. Firstly, higher BPV may aggravate hypoperfusion of the human brain, which could lead to lesion extension, or even a stroke recurrence and other vascular events. Secondly, higher BPV may also be associated with over‐perfusion of the delicate ischemic neurons, which could cause encephala edema, hemorrhagic transformation, or other vascular events. In short, these under‐ or over‐perfusion of the delicate ischemic neurons caused by higher BPV may worsen early functional outcome. However, it should be noted that our explanations of END are speculative. To better understand the pathogenesis of END and its relationship with BPV, second neuroimaging findings should be adopted and analyzed. And the progression or recurrence of stroke, symptomatic hemorrhagic transformation, seizure, and medical complications might be the cause of END, just as Chungs' study had suggested.16 However, this information was not available in the current study because of the absence of neuroimaging findings.
Therefore, several limitations of this study should be noted. Firstly, our data were designed as a single center–based study, and hence, generalizability of the results may be limited. Our findings needed to be further confirmed in multicenter prospective studies with large sample. Secondly, the perfusion imaging or repeated MRI was unavailable for us to directly analyze the mechanism of END, so the specific pathophysiology of END was incompletely understood. Thirdly, we cannot fully exclude the possibility that BPV may have been the result of END, rather than the cause of END, because a deteriorating or fluctuating clinical course may lead to a variable BP profile, and therefore, cannot definitively claim a causal relationship between BP and END. Although confounding factors were adjusted for, the possibility of residual confounding cannot be excluded.
In conclusion, this study demonstrated that BPV during acute stage may be a key independent predictor of END in acute minor stroke or TIA with steno‐occlusive arterial disease. Further multicenter prospective studies with large samples are warranted to investigate the causal relation between BPV and END.
CONFLICT OF INTEREST
The authors declare that they have no conflict of interest.
AUTHOR CONTRIBUTIONS
Zuowei Duan wrote the first draft of the manuscript and provided statistical analysis. Lihong Tao and Ming Yang were involved in data collection and literature review searches. Kaizheng Gong provided intellectual input in the area of data collection and analyses. Zuowei Duan and Tieyu Tang wrote the protocol and designed the study. All authors contributed and approved the final manuscript. All the authors listed have approved the submitted manuscript.
ETHICAL APPROVAL
The study was approved by Ethics Committees of the Affiliated Hospital of Yangzhou University.
Duan Z, Tao L, Yang M, Gong K, Tang T. Acute in‐hospital blood pressure variability predicts early neurological deterioration in acute minor stroke or transient ischemic attack with steno‐occlusive arterial disease. J Clin Hypertens. 2020;22:205–211. 10.1111/jch.13809
Funding information
This study was supported by the Foundation of Jiangsu Provincial Commission of Health and Family Planning (QNRC2016353).
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