Strain pattern and T‐wave alterations are predictors of mortality and poor neurologic outcome following stroke

Abstract Background Stroke is associated with electrocardiogram (ECG) abnormalities. However, the role of strain pattern as predictor of poor neurologic outcome and mortality after stroke has not yet been demonstrated. Hypothesis ECG abnormalities, with a particular focus on ST‐segment changes, are predictors of mortality and neurologic disability 90 days after stroke. Methods Patients with up to 24 hours of stroke were prospectively recruited. An ECG was taken at the time of admission. The patients' clinical evolution was evaluated during hospitalization and after discharge by means of a prescheduled return in 90 days. The degree of disability was measured by the modified Rankin scale (mRs). In relation to the mRs, patients were divided into those with scores from 0 to 2 and those with scores equal to or greater than 3 at the end of the observation period. Results Of the 112 patients studied, 29 (25.8%) died during the study period. Patients who died presented higher National Institute of Health Stroke Scale and mRs scores on admission, elevated biomarkers of myocardial necrosis, and abnormalities on the ECG. The prevalence of ECG abnormalities was 63%. A logistic regression model showed that strain pattern and T‐wave alterations were predictors of mortality (odds ratio [OR]: 12.970, 95% confidence interval [CI]: 1.519‐110.723, P = .019; OR: 3.873, 95% CI: 1.135‐13.215, P = .031, respectively) and mRs at 90 days (OR: 12.557, 95% CI: 1.671‐94.374, P = .014; OR: 15.970, 95% CI: 3.671‐69.479, P < .001, respectively) after stroke, adjusted by sex, age, stroke subtype, entrance NIH, previous mRs score, and stroke thrombolysis. Conclusion Strain pattern and T‐wave alterations were predictors of mortality and poor neurologic outcome 90 days after stroke.


| INTRODUCTION
Stroke is a major cause of morbidity and mortality around the world.
In addition to representing a profound burden of physical and psychological suffering for patients and their families, this pathology also represents enormous social costs, whether measured in days of lost work or the costs of treatment, secondary prevention, and rehabilitation. 1 A relevant challenge in the management of stroke is that this pathology is associated with heterogeneous prognoses. Therefore, predictors of poor outcome after an acute stroke, including age, severity of stroke, clinical subtype, previous stroke history, score on the Glasgow Coma Scale, arm strength, ability to walk, and prestroke dependence, are critical for the best management of patients. 1 In recent years, particular attention has focused on the electrocardiogram (ECG).
It is well known that stroke can induce ECG abnormalities and it has been hypothesized that these alterations are associated with adrenergic hyperstimulation, with consequent myocyte injury. [2][3][4] Several [5][6][7][8][9][10][11] but not all 12 studies suggest that ECG abnormalities, including alterations in T waves, prolongation of the QT interval, and ST changes, can be predictors of mortality after stroke. However, the kind of ST-segment abnormality associated with poststroke prognosis remains to be determined. Likewise, it is unknown whether ECG abnormalities can predict a poor neurologic outcome. Therefore, the main objective of our study was to analyze ECG abnormalities, with a particular focus on ST-segment changes as predictors of mortality and neurologic disability 90 days after stroke. In addition, we assessed associations between ECG abnormalities and biomarkers of myocardial necrosis and clinical stroke syndromes. Acute stroke was diagnosed in the presence of a sudden episode of focal dysfunction of the brain or retina and/or evidence of focal infarction or hemorrhage on cranial computed tomography (CT). 1 Exclusion criteria were as follows: nonvascular acute neurologic deficit; active malignancy; infection; end-stage cardiac, pulmonary, or hepatic disease; pregnancy; age less than 18 years; previous myocardial infarction; and serious valve disease.

| METHODS
At admission, data on patient characteristics were recorded, including waist circumference, body mass index, age, gender, heart rate, cardiovascular risk factors, concomitant diseases, medical and neurological complications, medical treatment, and data regarding clinical presentation and prehospital delay.
A CT scan was performed without contrast on Shimadzu SCT-7000 tomograph with infratentorial sections of 3-mm thickness and 5-mm spacing, 10-mm thickness supratentorial spacing and 10-mm spacing for the acquisition of images through the supraorbitomeatal angulation of the apparatus. The examination was performed at admission and tomographic control at 48 to 72 hours after admission.
An ECG was performed at the time of admission with an eightchannel Eletrotouch EP-3 Philips Dixtal with 12 leads, a 50/60 Hz filter, N gain, and 25 mm/s velocity in automatic mode. It was evaluated by a cardiologist who had no clinical information about the patients.
The following predictive variables were analyzed: rhythm (sinus or atrial fibrillation [AF]), heart rate (in beat per minute), duration of QRS The degree of disability was measured by the modified Rankin scale (mRs) 13 dichotomized according to the prognostic definition adopted in studies on the thrombolytic treatment of stroke. 14 At 90 days, a poor prognosis is indicated by a Rankin score between 3 and 6. For patients who, on admission to the emergency room, are already in coma and on mechanical ventilation, the maximum score was taken on the NIHSS (National Institute of Health Stroke Scale). 15 Medical complications were considered to include acute coronary syndrome, sudden death, AF or flutter, other arrhythmias, hypertensive crisis, acute heart failure, acute pulmonary edema, pulmonary thromboembolism (cardiac complications), pneumonia, urinary tract infection, deep venous thrombosis, gastrointestinal hemorrhage, and acute renal failure. [16][17][18][19][20][21][22][23][24][25]

| Statistical analysis
Data are expressed as the mean ± SD, the median (including the lower and upper quartiles) or as percentages. Comparisons between two groups for continuous variables were performed using Student's t test or the Mann-Whitney test. Comparisons between two groups for categorical variables were performed using the chi-square test or Fisher's exact test. A simple logistic regression model was used to predict outcomes. Variables were adjusted with parameters that indicated a significant difference in the univariate analysis or for factors that influenced the outcomes analyzed. The only exceptions were variables with high collinearity. Data analysis was performed using the SigmaPlot software for Windows v12.0 (Systat Software Inc., San Jose, California). P values lower than .05 were considered statistically significant.

| RESULTS
A total of 145 patients were evaluated. Of these, 18 patients pres- In relation to the mRs, patients were divided into those with scores from 0 to 2 and those with scores equal to or greater than 3 at the end of the observation period. The demographic and clinical data are shown in the Table 1. Patients with higher mRs scores at 90 days presented higher NIHSS and mRs at admission, elevated biomarkers of myocardial necrosis, and abnormalities on the ECG in comparison with patients with lower mRs at 90 days.
Data showing which ECG abnormalities were associated with a poor prognosis after stroke are presented in Table 2. AF and a prolonged     There was no association between ECG abnormalities (

| DISCUSSION
The objective of our study was to analyze ECG abnormalities with a particular focus on ST-segment changes as predictors of mortality and neurologic disability 90 days after stroke. In addition, we assessed the association between ECG abnormalities with biomarkers of myocardial necrosis and clinical stroke syndromes. Our data show that both strain pattern and T-wave alterations were predictors of both mortality and a poor neurologic outcome 90 days after stroke. Importantly, there was no association between ECG abnormalities and biomarkers of myocardial necrosis and clinical stroke syndromes.
The role of ECG after stroke has been widely analyzed in recent years, indicating that ECG alterations are commonly seen after brain injury even without preexisting heart disease, ranging from 30% to 90% depending on the study population. 26,27 The incidence of these manifestations is higher in patients with subarachnoid hemorrhage than in those with ischemic stroke. 4 The commonly seen ECG changes include T-wave inversion, U-wave abnormalities, abnormalities of the ST segment, and prolongation of the QT interval. Therefore, the types of ECG alterations found in our study are in concordance with these data.
It is accepted that ECG changes after stroke may be associated with negative clinical implications. However, the role of ECG changes as predictors of neurologic outcome remains unknown. Importantly, the type of ST-segment abnormality associated with poststroke prognosis also remains to be determined.
The main finding of our study was that ECG abnormalities are associated with a poor neurologic outcome 90 days after stroke.
Specifically, both strain pattern and T-wave alterations were predictors of neurologic disability. Another important issue is that these alterations were also predictors of mortality. Interestingly, both alterations suggest cardiac hypertrophy/ischemia and are associated with poor outcome in other clinical scenarios, including acute myocardial infarction, sudden death, and mainly in patients with hypertension. 28 However, the role of strain pattern as predictor of poor neurologic outcome and mortality after stroke had not yet been demonstrated.
Therefore, our data add prognostic information regarding these ECG changes in patients with stroke. This phenomenon can be detected by higher levels of biomarkers of myocardial necrosis, mainly troponin. Indeed, some studies have shown more ECG abnormalities in patients with stroke and high levels of troponin than in those with normal levels of troponin. 4 However, importantly, we did not find an association between ECG abnormalities and biomarkers of myocardial necrosis and clinical stroke syndromes, suggesting that the pathophysiologic mechanisms involved in this scenario remain to be studied.
Finally, this study had some limitations. First, it included a relatively small sample of patients at a single hospital. In addition, we cannot know whether the ECG changes would have been seen prior to stroke or were acutely induced by neurologic injury. However, even in the case of ECG changes before stroke, they would not diminish the importance of the strain pattern and T-wave abnormalities as predictors of poor prognosis in stroke patients treated in the emergency room.
Therefore, despite these limitations, we strongly believe that our study adds important data about the role of ECG abnormalities as predictors of both mortality and poor neurologic outcome after stroke.

| CONCLUSION
In conclusion, strain pattern and T-wave alterations were predictors of both mortality and poor neurologic outcome 90 days after stroke.
In addition, there was no association between ECG abnormalities with biomarkers of myocardial necrosis and clinical stroke syndromes.

ACKNOWLEDGMENTS
This work was supported by Botucatu Medical School.