Abstract
High blood pressure (BP) is frequent in acute ischemic stroke (IS). However, the impact of BP change patterns during acute phase on clinical outcomes is not conclusive. This study aims to investigate the association between the acute‐phase BP trajectories and clinical outcomes in IS patients with high admission BP. The cohort consisted of 316 IS patients with admission systolic BP (SBP) ≥160 mm Hg. SBP trajectories during the first 7 days after onset were characterized using a random effects model. The patients were classified into three groups based on the SBP trajectory curve parameters: sustained high SBP (T1), moderate decrease (T2), and rapid decrease in SBP (T3). Poor outcomes were defined as modified Rankin scale score ≥3 in 3 months after onset. The relationship between SBP trajectory groups and the outcome was examined in multivariable logistic regression models. The decreasing trend was greater in the favorable than in the poor outcome group (P = 0.028 for difference in linear slopes). The incidence of poor outcomes was 25.9%, 13.5%, and 9.8% in T1 (n = 54), T2 (n = 170), and T3 (n = 92) groups, respectively. Compared with T1 group, the decrease in SBP in T2 and T3 groups was significantly associated with lower risk of the poor outcome (odds ratio = 0.25, 95% confidence interval = 0.10‐0.67, P = 0.006). These findings suggest that a decrease in BP in the acute phase is predictive of favorable outcomes in IS patients. BP trajectories have a greater power to detect the association than individual BP values at one time‐point.
Keywords: blood pressure, follow‐up study, ischemic stroke, trajectory curve
1. INTRODUCTION
High admission blood pressure (BP) is very common in ischemic stroke (IS) patients,1 and early BP management represents an unresolved issue in acute IS. Despite the established concept of strong association between hypertension and IS, the results of the effect of acute‐phase BP on clinical outcomes from observational studies are conflicting.2, 3, 4, 5, 6 A systematic review of 32 studies has demonstrated that high BP in acute IS was associated with subsequent death, dependency, and deterioration.2 On the other hand, some studies found that both high and low BP was associated with poor prognosis in patients with IS3, 4; some studies reported that BP in the acute phase had no effect on outcomes5, 6; some other studies even suggested that BP elevation may represent a protective response to enhancing perfusion and recanalization in ischemic brain tissue.7, 8, 9
Most previous studies on the effect of acute‐phase high BP on clinical outcomes in IS have used one time‐point BP values as a predictor for the outcome. This approach has a limited power to predict the outcome as the direction and magnitude of subsequent BP changes during the acute phase are divergent among IS patients.9, 10 To date, only a few studies have focused on BP trajectory patterns in the acute phase of IS and their prediction value for clinical outcomes.11, 12
The current study aims to characterize BP trajectory patterns during the first 7 days in IS patients with high admission BP and examine their associations with clinical outcomes by analyzing repeated BP measurements data collected in the Blood Pressure and Clinical Outcome in TIA or Ischemic Stroke Study (BOSS).
2. METHODS
2.1. Study cohort
The BOSS, a hospital‐based, prospective cohort study, focuses on characteristics of office BP, ambulatory BP, and home BP within 7 days after onset of IS and transient ischemic attack (TIA), and their associations with clinical outcomes. The study design of the BOSS registry has been described elsewhere.13 Briefly, 2608 patients with IS and TIA were recruited between October 2012 and February 2014 in 61 hospitals in China, with 1448 patients hospitalized within 24 hours after stroke onset and followed for clinical outcomes for 3 months by personal interview. Acute IS was diagnosed according to World Health Organization criteria combined with brain computed tomography or magnetic resonance imaging confirmation. All patients with acute IS were further classified according to the TOAST criteria.14 The patients with IS in this study were classified into three subtypes: large‐artery atherosclerosis (LAA), small‐artery occlusion (SAO), and others (including cardioembolism, stroke of other determined pathogenesis, and stroke of undetermined pathogenesis). TIA was defined as symptomatic neurologic deterioration lasting <24 hours with no new infarction on neuroimaging.15 Exclusion criteria in this study were patients hospitalized for more than 24 hours after stroke onset or did not complete a 3‐month follow‐up, TIA patients, patients with IS who had systolic BP (SBP) ＜160 mm Hg at the time of admission and patients who received antihypertensive treatment.
The study was approved by the Central Institutional Review Board at Beijing Tiantan Hospital. Written informed consent was obtained from all the patients or their representatives.
2.2. Baseline variables
Brachial BP was recorded twice daily by nurses during the first 7 days after admission according to a standard measurement method recommended by the American Heart Association16 using a semi‐automatic upper‐arm BP monitor (HEM‐4030; OMRON Life Science Co. Ltd). The patients were classified into three BP trajectory groups (sustained high SBP, moderate decrease, and rapid decrease) based on SBP change parameters over the first 7 days.
Other baseline information, including age, sex, body mass index (BMI), smoking, alcohol drinking, disease history, and medications, was obtained by means of a nurse‐administered standardized questionnaire at the time of admission. History of stroke was defined as previous IS, intracerebral hemorrhage, and subarachnoid hemorrhage confirmed by medical records; history of hypertension was defined as previous hypertension and antihypertensive medication.
2.3. Outcome assessment
Modified Rankin scale (mRS) score ranging from 0 to 6, a measure of major disability, was calculated based on the information collected by nurses in a face‐to‐face interview.17 A score of 0 indicated no symptoms, a score of 5 indicated severe disability, that is, bedridden, incontinent, or requiring constant nursing care and attention, and a score of 6 indicated death. Death events were confirmed through death certificates from the local citizen registry or by the attended hospital. The primary adverse outcome of this study was defined as mRS ≥3 at 3 months.
2.4. Statistical analyses
Growth curve parameters of SBP repeatedly measured during the first 7 days were estimated using a random‐effects mixed model by SAS Proc MIXED, as previously reported.18, 19 The mixed model incorporates fixed and random effects and allows the intercept, linear, and nonlinear parameters to vary from individual to individual. The random effect coefficients represent the difference between the fixed effect parameters and the observed values for each individual. This model computes maximum likelihood estimates of the curve parameters, generating a set of parameters for each patient. The model fitting assessment was based on Akaike's information criterion. The most parsimonious model was selected based on P‐values of the independent variable (day) at a significance level of 0.05. Day and its higher‐order terms were included one by one for model building. The higher‐order terms of day were not included in the model if they were not significant, or made lower‐order terms not significant, or did not improve the goodness‐of‐fit of the model based on AIC values. Quadratic curves were fitted for SBP in sex groups.
where β = (β 0, β 1, β 2)’ is a vector of fixed effect parameters, b = (b 0, b 1, b 2)’ is a vector of random effect parameters, and ɛ is an unknown error term. Days were centered to the mean (4 days) to remove the collinearity of day with day2. The growth curve parameters estimated in the random effects model provided detailed information on individual‐specific parameters in different days as shown in Figure 2. β 0 + b 0 is the intercept (the level of SBP at day 4) because days were centered at its sample mean value; β 1 + b 1 describes linear slope (the tangent line) at the point of day 4; β 2 + b 2 shows the changes in linear slopes at time‐points. The random effects model allows for repeated measurements and computes maximum likelihood estimates of curve parameters, generating 316 different sets of curve parameters for all the study participants. The patients were classified into three SBP trajectory groups, that is sustained high (T1), moderate decrease (T2), and rapid decrease (T3), based on individual's linear slope parameters, with β 1 + b 1 i > −2 for T1 group, β 1 + b 1 i = −2 to −4 for T2 group, and β1 + b 1 i < −4 for T3 group.
Figure 2.
SBP trajectory curves by sex groups. All curve parameters were significantly different from 0 (P < 0.01). SBP, systolic blood pressure
The differences in trajectory curve parameters between outcome groups were tested by analysis of covariance. The relationship between SBP trajectory groups and the outcome was examined in multivariable logistic regression models. Covariates included in the model for adjustment were age, sex, BMI, smoking, drinking, National Institutes of Health stroke scale, stroke subtype, history of stroke, and hypertension. The association of individual values of SBP levels and slopes with the outcome was also examined. Odds ratio (OR) and 95% confidence interval (CI) were estimated in logistic regression models. All statistical analyses were performed using SAS software (version 9.4; SAS Institute Inc).
3. RESULTS
After excluding 162 TIA patients and 96 IS patients who received antihypertensive treatment, 316 patients with IS who had systolic BP (SBP) ≥160 mm Hg at the time of admission and completed baseline and follow‐up interview surveys formed the current study cohort. The flowchart of the patient selection is presented in Figure 1. Characteristics of patients included in and excluded from the study were compared in Table S1.
Figure 1.
Flowchart of patient selection
Table 1 summarizes characteristics of study variables in the total sample and by SBP trajectory groups. Analyses of covariance and chi‐square test were used to test the differences in continuous and categorical variables, respectively, between SBP trajectory groups, adjusting for age and sex. Patients in T3 group were younger than those in T1 and T2 groups. The prevalence of history of hypertension was highest in T1 group and lowest T3 group. SBP levels in the total sample had a marked decreasing trend from day 1 to day 7. T1 and T3 groups had the highest and the lowest SBP, respectively, on day 2 to day 7, while SBP on day 1 had an opposite trend across the three groups. mRS showed a decreasing but nonsignificant trend across the three groups. The difference in the incidence rates of poor outcome (mRS ≥ 3) between groups was significant (P = 0.024), with T1 group having the highest rate and T3 group having the lowest rate.
Table 1.
Characteristics of study patients by SBP trajectory groups
| Total | T1 Group | T2 Group | T3 Group | P‐value* | |
|---|---|---|---|---|---|
| N | 316 | 54 | 170 | 92 | |
| Age (y) | 63.4 (11.3) | 64.2 (10.7) | 64.5 (11.8) | 60.8 (10.4) | 0.017 |
| Females, n (%) | 93 (29.4) | 9 (16.7) | 53 (31.2) | 31 (33.7) | 0.071 |
| BMI (kg/m2) | 25.8 (2.9) | 25.4 (2.9) | 25.7 (2.8) | 26.3 (2.9) | 0.052 |
| Current smokers, n (%) | 141 (44.6) | 31 (57.4) | 69 (40.6) | 41 (44.6) | 0.096 |
| Current drinkers, n (%) | 114 (36.1) | 27 (50.0) | 54 (31.8) | 33 (35.9) | 0.052 |
| NIHSS on admission | 2.39 (2.99) | 2.36 (2.99) | 2.42 (3.14) | 2.35 (2.74) | 0.915 |
| Ischemic stroke subtype, n (%) | |||||
| Large‐artery atherosclerosis | 193 (61.1) | 31 (57.4) | 109 (64.1) | 53 (57.6) | 0.628 |
| Small‐artery occlusion | 101 (32.0) | 19 (35.2) | 52 (30.6) | 30 (32.6) | |
| Other | 22 (7.0) | 4 (7.4) | 9 (5.3) | 9 (9.8) | |
| Stroke history, n (%) | 76 (24.1) | 19 (35.2) | 40 (23.5) | 17 (18.5) | 0.072 |
| HTN history, n (%) | 236 (74.7) | 44 (81.5) | 134 (78.8) | 58 (63.0) | 0.009 |
| SBP on day 1 | 174.3 (14.0) | 168.1 (7.8) | 172.0 (10.5) | 182.1 (18.7) | <0.001 |
| SBP on day 2 | 156.0 (16.5) | 158.8 (16.3) | 157.4 (15.8) | 151.7 (17.2) | 0.014 |
| SBP on day 3 | 153.8 (16.4) | 160.5 (13.7) | 155.2 (15.8) | 147.3 (17.0) | <0.001 |
| SBP on day 4 | 153.1 (15.6) | 162.0 (12.4) | 154.9 (14.3) | 144.4 (15.7) | <0.001 |
| SBP on day 5 | 151.2 (16.1) | 163.7 (12.3) | 153.4 (13.5) | 139.9 (15.4) | <0.001 |
| SBP on day 6 | 149.6 (15.4) | 164.8 (12.1) | 151.5 (11.3) | 137.1 (14.0) | <0.001 |
| SBP on day 7 | 149.0 (14.9) | 165.7 (10.3) | 149.7 (11.7) | 138.0 (13.0) | <0.001 |
| mRS | 1.14 (1.21) | 1.37 (1.42) | 1.11 (1.20) | 1.05 (1.08) | 0.335 |
| mRS ≥ 3, n (%) | 46 (14.6) | 14 (25.9) | 23 (13.5) | 9 (9.8) | 0.024 |
Data are presented in means (SD) or %.
T1 group, patients who had sustained high SBP.
T2 group, patients who had a moderate decrease in SBP.
T3 group, patients who had a rapid decrease in SBP.
Abbreviations: BMI, body mass index; HTN, hypertension; mRS, modified Rankin scale; NIHSS, National Institutes of Health stroke scale; SBP, systolic blood pressure; SD, standard deviation.
P‐values for difference in study variables between SBP trajectory groups.
Figure 2 presents overall trajectories of SBP in 316 IS patients by sex. SBP decreased rapidly during the first 4 days, the decrease slowed down on days 5 and 6, and then, a mild increase occurred, representing nonlinear quadratic curves. Although female patients showed a sharper decreasing linear slope (β 1 + b 1 = −3.52 mm Hg/d) than male patients (β 1 + b 1 = −3.19 mm Hg/d), the difference in linear slopes between males and females was not significant (P = 0.126).
Figure 3 presents trajectory curves of SBP by outcome groups. Patients with favorable outcomes showed a deeper decreasing linear slope than patients with poor outcomes (β 1 + b 1 = −3.37 vs −2.79 mm Hg/d), and the difference in linear slopes between the two groups was significant (P = 0.028). The deeper slopes during the first 4 days resulted in the biggest differences in SBP levels on days 5 and 6 between the two groups. Then, a mild elevation occurred in both groups, but the difference in the quadratic slopes (β 2 + b 2 = 1.11 vs 0.88 mm Hg/d2) was not significant (P = 0.605).
Figure 3.
SBP trajectory curves by outcome groups. All curve parameters were significantly different from 0 (P < 0.01). SBP, systolic blood pressure
Figure 4 shows trajectory groups of SBP measured during the first 7 days after admission. The patients were classified into three SBP trajectory groups based on the linear slope parameters (β 1 + b 1) of the SBP trajectory curves: T1 group (β 1 + b 1 = −1.20, n = 54) had sustained high SBP; T2 group (β 1 + b 1 = −3.03, n = 170) had a moderate decrease in SBP; and T3 group (β 1 + b 1 = −4.96, n = 92) had a rapid decline in SBP.
Figure 4.
Trajectory groups of SBP repeatedly measured during the first 7 days after admission. All curve parameters were significantly different from 0 (P < 0.01). T1, a group characterized as a sustained high SBP (n = 54); T2, a group characterized as a moderate decrease in SBP (n = 170); T3, a group characterized as a rapid decrease in SBP (n = 92); SBP, systolic blood pressure
Table 2 shows the association between SBP trajectory groups and outcome, adjusting for covariates. Older age and higher NIHSS were significantly associated with higher risk of worse outcome. Compared with T1 group, T2 and T3 groups were significantly associated with lower risk of poor outcome as shown in model 1. When T2 and T3 groups were combined, the decrease in SBP had a stronger association with lower risk of poor outcome as shown in model 2.
Table 2.
Logistic regression analyses of SBP trajectory groups on outcome
| Model 1 | Model 2 | |||
|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | |
| Age | 1.05 (1.01‐1.10) | 0.022 | 1.06 (1.01‐1.10) | 0.015 |
| Sex | 1.23 (0.45‐3.40) | 0.689 | 1.24 (0.45‐3.40) | 0.680 |
| BMI | 1.00 (0.87‐1.15) | 0.947 | 1.00 (0.87‐1.15) | 0.971 |
| Smoking | 0.59 (0.17‐2.01) | 0.400 | 0.62 (0.19‐2.03) | 0.425 |
| Drinking | 1.39 (0.40‐4.78) | 0.605 | 1.22 (0.35‐4.20) | 0.756 |
| NIHSS | 1.67 (1.44‐1.93) | <0.001 | 1.68 (1.45‐1.95) | <0.001 |
| Stroke subtype | 1.30 (0.81‐2.10) | 0.278 | 1.35 (0.83‐2.20) | 0.231 |
| Stroke history | 1.72 (0.72‐4.10) | 0.224 | 1.66 (0.69‐3.99) | 0.254 |
| HTN history | 1.60 (0.49‐5.29) | 0.439 | 1.67 (0.51‐5.49) | 0.398 |
| Trajectory group | 0.47 (0.25‐0.89) | 0.021 | 0.25 (0.10‐0.67) | 0.006 |
Model 1: Trajectory group value: 0 = T1 (reference), 1 = T2, and 2 = T3.
Model 2: Trajectory group value: 0 = T1 (reference), 1 = T2 and T3.
Abbreviations: BMI, body mass index; CI, confidence interval; HTN, hypertension; NIHSS, National Institutes of Health stroke scale; OR, odds ratio; SBP, systolic blood pressure.
Table 3 presents logistic regression analyses of individual SBP levels and slopes of each day on the outcome. SBP slopes (mm Hg/d) were calculated as SBP minus SBP on the day before. SBP levels and slopes on each day were examined in separate models. SBP levels and slopes on individual days were not significantly associated with the outcome. Given that SBP slopes were strongly and negatively correlated with their baseline values, the values of SBP levels were also included in the model for adjustment. A smaller decrease in SBP on day 7 (a smaller absolute value of the slope) was significantly associated with higher risk of poor outcome, with adjustment for its level on the day before.
Table 3.
Logistic regression analyses of individual SBP levels and slopes on outcome
| SBP Levels | SBP Slopes | SBP Slopesa | ||||
|---|---|---|---|---|---|---|
| OR (95% CI) | P | OR (95% CI) | P | OR (95% CI) | P | |
| Day 1 | 0.99 (0.96‐1.02) | 0.555 | ||||
| Day 2 | 1.00 (0.98‐1.02) | 0.691 | 1.00 (0.98‐1.02) | 0.971 | 1.00 (0.98‐1.02) | 0.832 |
| Day 3 | 1.00 (0.98‐1.03) | 0.841 | 1.02 (0.98‐1.05) | 0.352 | 1.02 (0.98‐1.06) | 0.396 |
| Day 4 | 1.01 (0.98‐1.03) | 0.499 | 1.01 (0.98‐1.05) | 0.464 | 1.02 (0.98‐1.06) | 0.369 |
| Day 5 | 1.02 (0.99‐1.05) | 0.143 | 1.02 (0.99‐1.07) | 0.230 | 1.03 (0.99‐1.08) | 0.122 |
| Day 6 | 1.01 (0.98‐1.04) | 0.457 | 0.98 (0.94‐1.02) | 0.225 | 0.99 (0.95‐1.03) | 0.488 |
| Day 7 | 1.03 (1.00‐1.05) | 0.067 | 1.03 (1.00‐1.07) | 0.079 | 1.05 (1.00‐1.09) | 0.036 |
Covariates included age, sex, BMI, smoking, drinking, National Institutes of Health stroke scale, stroke subtype, history of stroke, and hypertension.
SBP slopes (mm Hg/d) were calculated as SBP minus SBP on the day before.
Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio; SBP, systolic blood pressure.
SBP levels on the day before were included in the model for adjustment.
4. DISCUSSION
The initial rise in BP is commonly observed early after IS onset.20, 21 This phenomenon of elevation in BP within 24 hours of onset is defined as acute hypertensive response.22 Then, the BP declines spontaneously over the first week and returns to prestroke levels in most patients without specific antihypertensive therapy. There are multiple mechanisms underlying this pathophysiologic response. They are related to pre‐existing high BP, activation of the neuroendocrine systems (sympathetic nervous system, renin‐angiotensin axis, and glucocorticoid system), increased cardiac output, and white coat hypertension.22 In the present study, SBP decreased rapidly during the first 4 days in patients with high admission BP, the decrease slowed down on days 5 and 6, and then, a mild increase occurred. This quadratic decreasing trajectory pattern was substantially similar to the course of BP in the acute‐phase observed in previous studies.20, 21, 23 Stroke patients in this study did not receive BP‐lowering therapy, indicating that the decrease in the acute‐phase BP was spontaneous in nature. To date, there is no general agreement regarding the role of the acute hypertensive response and the decrease in BP in prognosis of IS.
The majority of studies supports the notion that high BP in the acute‐phase is associated with poor outcomes in IS as summarized in a systematic review of 32 studies.2 However, the findings in this regard are inconsistent or even conflicting. A U‐shaped relationship was found in the International Stroke Trial study, indicating that both high and low BP were independent prognostic factors for poor outcome in IS.3 Some studies reported that BP in the acute‐phase had no effect on outcomes in IS.5, 6, 24 On the contrary, some other studies even suggested that BP elevation may represent a protective response to enhancing perfusion and recanalization in ischemic brain tissue.7, 8, 9 The effect of the acute hypertensive response on the outcomes in IS has remained a topic of debate for decades. We constructed a trajectory curve model utilizing BP repeatedly measured during the first week in IS patients with high admission BP in the BOSS cohort who did not take antihypertensive treatment. The rationale for selecting patients with high admission SBP (≥160 mm Hg) was to ensure a sufficient number of patients who had a marked decreasing trajectory and thus an adequate power to test the hypothesis. In addition to analyses of SBP trajectory curve parameters as a continuous variable, three trajectory groups were also analyzed as a categorical variable. The trajectory group approach captured combined information of all curve parameters. It is found in this study that a marked decrease in SBP during the first week was significantly associated lower risk of poor outcomes using both linear slope parameters and trajectory groups. The current study provided additional evidence for the effect of early management of BP on the outcome in IS. These findings are consistent with observations from recent studies in Chinese and Korean populations that the decreasing trajectory of BP during the acute phase has a beneficial effect on the clinical outcomes of stroke patients.11, 12
Repeated measures data of BP have at least two types of variation, among‐individual and within‐individual variance.18, 19, 25 Longitudinal studies are necessary to examine within‐individual changes over time. Most previous studies on the acute‐phase BP‐outcome association in IS patients have used a single time‐point BP value as a predictor for the outcome. This is the most possible reason for the discrepancies in previous studies because one time‐point value does not reflect within‐individual changes in BP over time. Two studies reported the effect of BP changes in the first 2 days and achieved opposite conclusions on the BP change‐outcome association.9, 10 In the present study, individual values of SBP levels and slopes on each of the 7 days were analyzed in relation to the outcome. They were not significantly associated with the outcomes except the SBP slope on day 7, with adjustment for SBP level on the day before. Compared with the results obtained from trajectory parameters and groups, a single value of SBP levels as well as slopes did not have an adequate power to detect the association. These observations suggest that SBP trajectory patterns over a longer period have advantage over the use of individual values of BP levels and changes on a single day.
Our study has several short comings. First, the small sample size is associated with relatively limited statistical power for the association analysis, especially for the BP trajectory group analysis. Second, antihypertensive therapy is customarily not commenced in guidelines during the acute phase with the exception of stroke patients who have extremely high BP.26 For this reason, we could not examine the association of the clinical outcome with changes in the acute‐phase BP due to BP‐lowering medications. Third, the current analysis was not a prespecified study design. The results might be influenced by potential selection bias and confounding factors. Further studies are needed to validate the findings of this study. In addition, participants in our study are middle‐aged and elderly Asians. Further studies including other ethnicities, races, and younger participants are needed to confirm the generalizability of our findings.
5. CONCLUSIONS
The current observational study demonstrates that a decrease in the acute‐phase BP predicts favorable clinical outcome in IS patients with high admission BP recruited in the BOSS. The BP trajectory patterns characterized by repeated measures of BP in the random effects model have a greater statistical power than individual values of BP levels and slopes to detect such an association. This observation emphasizes the importance in prediction of clinical outcome of IS patients in using BP trajectory data over the acute phase, the first week in this case. These findings on the prediction value of BP trajectories in the acute phase for functional outcomes would improve our understanding of the effect of early management of BP in acute IS. The present study emphasized the advantage of the BP trajectory approach which deserves attention in future observational and clinical trial studies.
CONFLICT OF INTEREST
There are no conflict of interest.
AUTHOR CONTRIBUTIONS
Dr Yongjun Wang: had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Jie Xu, Liye Dai, and Zimo Chen: contributed equally to this work. Jie Xu, Liye Dai, Zimo Chen, and Yongjun Wang: study concept and design. Jie Xu, Liye Dai, Anxin Wang: acquisition, analysis, or interpretation of data. Jie Xu, LiyeDai, and Zimo Chen: drafting of the manuscript. Xia Meng, Hao Li, Yilong Wang, Xingquan Zhao, and Yilong Wang: critical revision of the manuscript for important intellectual content. Jinglin Mo, Aichun Cheng, Anxin Wang: statistical analysis. Yongjun Wang: study supervision.
Supporting information
Xu J, Dai L, Chen Z, et al. Acute‐phase blood pressure trajectories and clinical outcomes in ischemic stroke. J Clin Hypertens. 2019;21:1108–1114. 10.1111/jch.13599
J. Xu, L. Dai and Z. Chen are contributed equally.
Funding information
This study was supported by grants from the Ministry of Science and Technology of China (2006BAI01A11, 2011BAI08B01, 2011BAI08B02, 2012ZX09303‐005‐001, 2013BAI09B03, and 2015BAI09B01), the National Natural Science Foundation of China (No. 81701141), and a grant from Beijing Municipal Administration of Hospitals’ Youth Programme (QML2015 0504).
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