International Journal of Cardiology 176 (2014) 206–210

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Heart rate on admission independently predicts in-hospital mortality in acute ischemic stroke patients☆ Hebun Erdur a,⁎, Jan F. Scheitz a,b,e, Ulrike Grittner b,c, Ulrich Laufs d, Matthias Endres a,b,e, Christian H. Nolte a,b a

Department of Neurology, Charité — Universitätsmedizin Berlin, Germany Center for Stroke Research, Charité — Universitätsmedizin Berlin, Germany Department for Biostatistics and Clinical Epidemiology, Charité — Universitätsmedizin Berlin, Germany d Department of Cardiology, Universitätskliniken des Saarlandes, Homburg/Saar, Germany e NeuroCure, Cluster of Excellence, Charité — Universitätsmedizin Berlin, Germany b c

a r t i c l e

i n f o

Article history: Received 5 November 2013 Received in revised form 16 April 2014 Accepted 5 July 2014 Available online 11 July 2014 Keywords: Heart rate Stroke Mortality Sympathetic nervous system Outcome

a b s t r a c t Background: Higher heart rate (HR) is associated with worse outcomes – in particular death – in long term followup of patients with vascular diseases. We investigated the association between HR measured on admission and early in-hospital mortality in acute ischemic stroke patients. Methods: Over a period of 30 months all patients admitted to our hospital with acute ischemic stroke but without atrial fibrillation were prospectively enrolled. Univariate and multiple logistic regression analyses were conducted to estimate the impact of HR on in-hospital mortality. HR was analyzed as continuous and categorical variable (tertiles). Results: A total of 1335 patients (median age 73 (IQR 65–81), median National Institutes of Health Stroke Scale score 4 (IQR 2–8), median length of stay 5 days (IQR 4–7), female sex 46%) were studied. In-hospital mortality was 2.6%. When analyzed as categorical variable, HR ≥ 83 bpm was independently associated with in-hospital mortality after adjustment for predictors of poor outcome compared to the reference tertile (HR ≤ 69 bpm) (adjusted odds ratio 4.42, 95% CI 1.36–14.42, p = 0.01). When HR was modeled as continuous variable, relative risk for in-hospital death was elevated by 40% for every additional 10-bpm (p = 0.003). These results were not changed by including beta-blockers as covariate into the multiple regression model. Conclusions: HR on admission is independently associated with in-hospital mortality in acute ischemic stroke patients suggesting early negative effects of autonomic imbalance. HR may represent a therapeutic target to improve outcome after ischemic stroke. © 2014 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Retrospective analyses suggest that higher heart rate (HR) at rest is independently associated with total mortality in followup (≥3 months) of patients with ischemic stroke of non-cardioembolic origin [1,2]. A higher HR at rest is associated with increased mortality in long-term follow-up in the general population and in patients with arterial hypertension, coronary artery disease, and heart failure [3–6]. Furthermore, in patients with myocardial infarction and acute heart failure, higher HR on admission was independently associated with higher in-hospital mortality [7,8]. Studies investigating the relation of HR on

☆ All authors state that they take responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation. ⁎ Corresponding author at: Department of Neurology, Campus Benjamin Franklin, Charité – Universitätsmedizin Berlin, Hindenburgdamm 30, 12200 Berlin, Germany. Tel.: + 49 30 84454285; fax: + 49 30 84454264. E-mail address: [email protected] (H. Erdur).

http://dx.doi.org/10.1016/j.ijcard.2014.07.001 0167-5273/© 2014 Elsevier Ireland Ltd. All rights reserved.

admission with very early outcome of patients with ischemic stroke are lacking. To date, studies investigating the effects of HR on outcome of patients with ischemic stroke have mainly assessed (i) HR at rest and/or (ii) long-term outcome of at least three months after the index event. We investigated whether HR on admission was independently associated with early in-hospital mortality in patients with acute ischemic stroke and without atrial fibrillation. We additionally examined whether HR on admission was independently associated with poor outcome (Modified Rankin Scale (mRS) ≥ 5), as in-hospital mortality as an outcome parameter is subject to restrictions due to the possibility of withdrawal of care following patient and family preferences on life-sustaining measures [9]. 2. Methods 2.1. Study population and data acquisition This study is a retrospective analysis of prospectively collected data of all consecutive patients with acute ischemic stroke (n = 1766) admitted to our tertiary care hospital

H. Erdur et al. / International Journal of Cardiology 176 (2014) 206–210 (Department of Neurology at Campus Benjamin Franklin, Charité, Berlin) within 72 h after symptom onset between February 2011 and August 2013. Diagnosis of ischemic stroke was made by the attending neurologist according to the WHO-definition based on history, clinical data, and persistence of stroke symptoms for more than 24 h; neuroimaging (CT or MRI) showed proof of infarction in 91.1% of patients. Patients for whom admission electrocardiogram (ECG) and HR were not available (n = 8), patients with atrial fibrillation on admission ECG (n = 368), and patients with cardiac pacemakers (n = 55) were not included, leaving 1335 patients eligible for analysis (Fig. 1). Incorporating recommendations on obtaining and reporting HR [10], HR was obtained from a 12-lead ECG, which was conducted on admission to our emergency department by a nurse with the patient lying in supine position in a quiet room at a comfortable temperature. In line with our local standard operating procedure in acute stroke, there was no formal resting period before measurement. Duration of measurement was 30–60 s. We assessed history of following pre-existing diseases and cardiovascular risk factors: arterial hypertension (defined as systolic blood pressure of ≥140 mm Hg or diastolic blood pressure of ≥90 mm Hg more than 48 h after admission or history of treated hypertension), hyperlipidemia (fasting total plasma cholesterol level of ≥200 mg/dl, fasting low-density lipoprotein cholesterol level of ≥130 mg/dl, or history of treated hyperlipidemia), diabetes (fasting blood glucose level of 7.0 mmol/l or history of diabetes), current smoking, history of coronary artery disease, history of congestive heart failure, previous ischemic stroke, history of chronic obstructive lung disease (COLD), and history of renal insufficiency. Furthermore, we assessed pre-existing medication (use of beta-blockers, ACEinhibitors, AT1-receptor-blockers, and statins), stroke severity on admission evaluated by National Institutes of Health Stroke Scale (NIHSS), treatment with intravenous recombinant tissue plasminogen activator (iv rtPA), development of pneumonia during hospital stay, and length of stay in hospital. NIHSS on admission was categorized in three groups based on previous work [11]: [1] NIHSS 0–3, [2] NIHSS 4–15, and [3] NIHSS N 15. Primary endpoint was defined as all-cause in-hospital mortality. Secondary endpoint was poor outcome at hospital discharge, defined as a mRS score of ≥5 (bedbound with need of constant medical care or dead). 2.2. Ethics The study conforms to the ethical guidelines of the 1975 Declaration of Helsinki and the data protection laws of the Land of Berlin. The authors of this manuscript have certified that they comply with the Principles of Ethical Publishing in the International Journal of Cardiology. 2.3. Data analysis Because of skewed distributions univariate comparisons for continuous variables for analysis of baseline characteristics were assessed by Mann–Whitney-test. Spearman's rank correlation coefficient was used to investigate the association of HR with age. We conducted univariate and multiple logistic regression analyses in order to estimate the impact of HR on admission on in-hospital mortality. HR on admission was both analyzed as continuous and categorical variable (the latter by division into tertiles). Age and HR were rescaled by dividing the original variable by 10 to ease the interpretation of the regression coefficients. In a first step, several potential predictors of in-hospital mortality (all above-mentioned pre-existing diseases and cardiovascular risk factors) were

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separately assessed in logistic regression analyses adjusted for age. Then, we conducted a backward stepwise multiple logistic regression analysis adjusting for covariates with an association with in-hospital mortality (p ≤ 0.10) in the age-adjusted analyses. The same stepwise approach was conducted for the secondary endpoint ‘poor outcome’. Results are expressed as odds ratios with 95% confidence intervals (95% CI). All tests were two-sided, and a p-value of less than 0.05 was considered as statistical significant. In order to assess to what degree HR adds to the predictive value of known predictors of early mortality in stroke patients [12], the area under the curve (AUC) and the 95% confidence limits for different models are reported. Paired sample statistical techniques were used for comparison of the model without information of HR versus the regression model with additional information of HR. The method exploits the mathematical equivalence of the AUC to the Mann–Whitney U-statistic [13]. SPSS 19 (SPSS, Inc., 2010, Chicago, IL, USA) was used for data analysis. Comparison of ROC curves was done using SAS 9.2 (SAS Institute Inc., 2008, Cary, NC, USA).

3. Results 3.1. Baseline characteristics A total of 1335 patients were included in the study. Median age was 73 years (IQR 65–81), median NIHSS 4 (IQR 2–8), median length of stay in hospital 5 days (IQR 4–7), 46% of patients were females. Median HR on admission was 76 bpm (IQR 66–87). HR on admission was higher in females than in males (median 78 bpm (IQR 68–88) vs. 75 bpm (IQR 64–86), p b 0.001). There was a very weak negative correlation of HR with age (r = −0.081, p = 0.003). During hospitalization, 35 patients (2.6%) died. Median HR was significantly higher in deceased patients compared to survivors (85 bpm (IQR 74–100) vs. 76 bpm (IQR 65–87), p = 0.001). Poor outcome (mRS ≥ 5) was found in 146 patients (10.9%). Median HR was significantly higher in patients with poor outcome compared to patients with better outcome (mRS ≤ 4) (82 bpm (IQR 71–95) vs. 75 bpm (IQR 65–87), p b 0.001). 3.2. In-hospital mortality Higher HR on admission was associated with a higher risk for inhospital mortality in age-adjusted logistic regression analysis (Table 1). Especially patients with HR ≥ 83 bpm (highest tertile) showed a higher risk for in-hospital mortality compared to the reference tertile (≤69 bpm) (Table 2, Fig. 2). HR remained significantly associated with in-hospital mortality in a multiple logistic regression analysis adjusted for age, stroke severity, congestive heart failure, therapy with intravenous rtPA, and development of pneumonia (adjusted Odds ratio 1.40 per 10 bpm (95% CI 1.12–1.75), p = 0.003). Again, patients in the highest tertile (≥ 83 bpm) were at significantly higher risk compared to the reference tertile (≤69 bpm) (Table 2). Including beta-blockers into the multiple analysis did not change these results. 3.3. Poor outcome (mRS ≥ 5) Higher HR on admission was also associated with poor outcome at discharge in the age-adjusted logistic regression analysis (Table 1). Again, patients in the highest tertile had a higher risk of suffering a poor outcome compared to patients in the reference tertile (Table 2). After adjustment for age, sex, stroke severity, congestive heart failure, diabetes, and pneumonia, HR remained significantly associated with poor outcome (adjusted Odds ratio 1.28 per 10 bpm (95% CI 1.13–1.46, p b 0.001). Patients in the highest tertile were at a significant higher risk compared to patients in the reference tertile (Table 2). Results were not changed by including beta-blockers into the multiple analysis. 3.4. Predictive value of heart rate

Fig. 1. Title: Flow diagram depicting study population. Caption: Patients with atrial fibrillation on admission ECG and pacemakers were not included into analysis. ECG = electrocardiogram.

In order to assess whether HR adds to the predictive value of known predictors of early mortality in stroke, we compared AUC for age and stroke severity alone with AUC for age, stroke severity, and HR. AUC for age and stroke severity measured by NIHSS was 0.87 (95% CI

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Table 1 Odds ratios for in-hospital mortality and poor outcome at discharge (age-adjusted logistic regression analysis). Poor outcome (mRS ≥ 5) n = 146

In-hospital mortality n = 35 Odds ratio (95% CI) Age (per 10 years) Sex, female Admission heart rate (per 10 bpm) Stroke severity (NIHSS on admission in categories) NIHSS 0–3 NIHSS 4–15 NIHSS N15 Comorbidities Hypertension Hyperlipidemia Coronary artery disease Congestive heart failure Previous stroke Diabetes COLD Renal insufficiency Current smoking Therapy Beta-blockers ACE-inhibitors or AT1receptor-blockers Statins iv rtPA Complications Pneumonia

p

Odds ratio (95% CI)

p

1.57 (1.14–2.16) 0.006 1.72 (1.45–2.04) b0.001 1.39 (0.67–2.87) 0.38 1.58 (1.09–2.31) 0.02 1.46 (1.21–1.77) b0.001 1.30 (1.17–1.45) b0.001 b0.001

Reference 6.13 (1.37–27.38) 48.15 (11.00–210.83)

0.02

b0.001

Reference 5.19 (2.76–9.76) b0.001

b0.001 51.66 (26.29–101.50)

0.99 (0.34–2.91) 0.96 (0.49–1.88) 1.03 (0.44–2.38) 3.93 (1.72–8.98) 1.13 (0.55–2.35) 1.05 (0.48–2.27) 0.62 (0.15–2.63) 1.72 (0.82–3.59) 0.31 (0.07–1.37)

0.97 0.90 0.95 0.001 0.74 0.91 0.52 0.15 0.12

b0.001

1.32 (0.72–2.42) 0.37 0.83 (0.59–1.18) 0.30 1.06 (0.69–1.64) 0.78 2.64 (1.58–4.41) b0.001 1.06 (0.72–1.56) 0.76 1.71 (1.18–2.49) 0.005 1.33 (0.75–2.36) 0.32 1.01 (0.66–1.55) 0.97 0.81 (0.47–1.40) 0.46

1.26 (0.63–2.50) 0.52 0.57 (0.28–1.17) 0.13

1.30 (0.90–1.89) 0.77 (0.53–1.11)

0.16 0.16

0.80 (0.36–1.76) 0.58 2.59 (1.31–5.11) 0.006

1.28 (0.77–2.13) 1.28 (0.87–1.89)

0.34 0.21

b0.001 11.46 (7.39–17.75)

23.02 (10.88–48.73)

b0.001

mRS = modified Rankin Scale; CI = confidence interval; bpm = beats per minute; NIHSS = National Institutes of Health Stroke Scale; COLD = chronic obstructive lung disease; and iv rtPA = intravenous recombinant tissue plasminogen activator.

0.81–0.92). After addition of HR to the model AUC amounted to 0.90 (95% CI 0.86–0.93), and the predictive value was significantly improved (p = 0.04).

Table 2 Heart rate as categorical variable (tertiles). Odds ratios for in-hospital mortality and poor outcome at discharge (logistic regression analysis). In-hospital mortality

Poor outcome (mRS ≥ 5)

Odds ratio (95% CI) p

Odds ratio (95% CI)

Univariate age-adjusted Heart rate in tertiles Tertile 1 (≤69 bpm) Reference Tertile 2 (70–82 bpm) 3.24 (1.04–10.15) Tertile 3 (≥83 bpm) 5.17 (1.74–15.35) Multiple analysisa Heart rate in tertiles Tertile 1 (≤69 bpm) Tertile 2 (70–82 bpm) Tertile 3 (≥83 bpm)

b0.001

0.01 0.04 0.003

1.40 (0.86–2.26) 2.58 (1.66–4.02)

0.048 Reference 3.22 (0.93–11.10) 4.42 (1.36–14.42)

0.06 0.01

p

0.18 b0.001 0.002

1.47 (0.82–2.64) 2.52 (1.47–4.33)

0.20 0.001

Abbreviations as in Table 1. a Model is adjusted for age, stroke severity, congestive heart failure, thrombolysis, and pneumonia for the endpoint in-hospital mortality, and for age, sex, stroke severity, congestive heart failure, diabetes, and pneumonia for the endpoint poor outcome, respectively.

Fig. 2. Title: Percentage of in-hospital mortality according to tertiles of heart rate on admission. Caption: In-hospital mortality amounted to 0.9% (4 of 448 patients) in the lowest tertile, 2.7% (12 of 439 patients) in the middle tertile, and 4.2% (19 of 448 patients) in the highest tertile. P for trend = 0.002. Bpm = beats per minute.

4. Discussion The main finding of our study is the association of higher HR on admission with in-hospital mortality in patients with acute ischemic stroke. Our results are in line with studies showing this association between higher admission HR and in-hospital mortality in patients with myocardial infarction and acute heart failure [7,8]. Moreover, our results are in line with previous investigations showing an association of higher HR at rest with higher probability of mortality in long term follow-up of patients with ischemic stroke [1,2]. The association between higher HR and mortality may even be more pronounced under the influence of an acute emergency setting as compared to sub-acute patients with HR recordings at rest. Both vagal and sympathetic nerve activity regulate HR; at rest, HR is mainly determined by vagal tone. Acute stroke can result in autonomic imbalance with activation of the sympathetic nervous system and decreased vagal tone [14]. Sympathetic overactivity results in higher HR, higher blood pressure, increased levels of catecholamines, and elevated cardiac troponin [15–18]. Sympathoexcitation may alter vascular tone, cellular metabolism, and facilitate cardiac arrhythmias that are independently associated with sudden death [19,20]. In contrast, it has been shown that vagal tone contributes to immunoregulatory functions limiting systemic inflammation and neuroinflammation [21]. Furthermore, vagus nerve stimulation with lowering of both blood pressure and HR reduced lesion size of induced stroke in rats [22]. Thus, the available evidence suggests that the negative effects of autonomic imbalance in patients with acute stroke are not only due to sympathetic overactivity but also due to reduction of vagal tone [23]. Taken together, autonomic imbalance may lead to unfavorable cardiovascular stress, systemic inflammation, and inflammatory processes in the brain worsening the clinical outcome of patients with acute stroke. Our results show that higher HR may indicate autonomic imbalance and might be used as an additional prognostic marker in acute stroke. We demonstrate that HR on admission significantly improved the predictive model for in-hospital mortality compared to previously identified predictors of worse outcome like age and stroke severity alone. Interestingly, stroke severity measured by NIHSS has been identified as a marker for autonomic imbalance as well [24]. It is unclear, whether higher HR implies also a causative role for vascular events and death. Considering pathophysiologic mechanisms contributing to the worse prognosis of patients with elevated HR, several effects of HR have been proposed [25]. These include

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development and progression of coronary atherosclerosis [26], disruption of atherosclerotic plaque [27], and progression of arterial stiffness [28]. Furthermore, HR directly influences myocardial oxygen demand and supply, thus contributing to disordered balances which can result in or aggravate pre-existing myocardial ischemia [29]. Finally, higher resting HR and an altered HR profile during exercise are associated with sudden death, probably due to cardiac arrhythmias [30]. Our finding of an association of higher HR with very early poor outcome raises the question whether therapeutic reduction of HR in the early phase after ischemic stroke is suitable. Animal studies linked selective reduction of HR by ivabradine with improved endothelial function and reduced vascular oxidative stress in mice [31,32]. Two large randomized controlled trials tested the effects of HR reduction by ivabradine and have shown an improvement of clinical outcomes in patients with stable coronary artery disease and patients with heart failure, respectively [33,34]. Studies investigating selective reduction of HR in acute stroke patients are missing. We confined our analysis to patients presenting with sinus rhythm. Approximately 25% of all ischemic strokes are of cardioembolic origin, mainly due to non-valvular atrial fibrillation [35]. The interpretation of HR in patients with atrial fibrillation is more complex due to the irregularity of HR in patients with atrial fibrillation, possible medical treatment in patients with very high HR (N120 bpm), and possible coexisting conduction disease resulting in a lower ventricular rate [6]. In patients with heart failure and atrial fibrillation, several studies could not find an association of higher HR with worse outcomes [6,8]. In contrast to patients with sinus rhythm, HR may not be a marker of autonomic imbalance in patients with atrial fibrillation [6]. Whether higher HR in patients with atrial fibrillation and stroke is associated with worse outcomes is uncertain and requires further research. Strengths of our study include the relatively large and well characterized cohort of patients with the assessment of numerous preexisting diseases and relevant risk factors. This allowed adjustment for possible confounding factors. Confirmation of previously identified predictors (i.e. older age and higher stroke severity) of early mortality [12] argues in favor of the robustness of our results. Limitations of our study include the monocentric design which might entail a referral bias and limit the extent to which our results could be generalized. Second, caution is advised given the retrospective analysis of our prospectively collected data. Third, in-hospital mortality as outcome parameter might be biased by the withdrawal of care due to patient and family preferences on life-sustaining measures [9]. We therefore extended our analysis to poor outcome, which was also independently associated with higher HR. 5. Conclusions Our results show that HR on admission is an important prognostic marker for in-hospital mortality in acute stroke patients. Higher HR might indicate unfavorable effects of autonomic imbalance in acute stroke. Targeting sympathetic system activation in general and HR in particular should therefore be prospectively investigated in stroke patients. Conflict of interest H. Erdur received a travel grant from Bayer, Boehringer Ingelheim (BI), and TEVA. Dr. Scheitz received a travel grant from BI and is a participant in the Charité Clinical Scientist Program funded by the Charité and the Berlin Institute of Health. Dr. Grittner reports no conflicts of interest. Dr. Laufs has received honoraria from Bayer, BI, Sanofi, and Servier. Dr. Endres has received grant support from AstraZeneca, Roche, and Sanofi, has participated in advisory board meetings of Bayer, BI, Bristol-Myers Squibb (BMS), MSD, Pfizer, Sanofi, and has received honoraria from Astra Zeneca, Bayer, Boston Scientific, Berlin Chemie, BI, BMS, Desitin, Edwards, Ever, Glaxo Smith Kline, MSD,

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