Author + information
- Received June 18, 2009
- Revision received January 20, 2010
- Accepted February 25, 2010
- Published online September 21, 2010.
- Mira Katan, MD⁎,†,⁎ ( )(, )
- Felix Fluri, MD†,
- Philipp Schuetz, MD⁎,
- Nils G. Morgenthaler, MD, PhD‡,
- Christian Zweifel, MD§,
- Roland Bingisser, MD∥,
- Ludwig Kappos, MD†,
- Andreas Steck, MD†,
- Stefan T. Engelter, MD†,
- Beat Müller, MD⁎,¶ and
- Mirjam Christ-Crain, MD⁎
- ↵⁎Reprint requests and correspondence:
Dr. Mira Katan, University Hospital Basel, Petersgraben, 4031 Basel, Switzerland
Objectives The purpose of this study was to examine the prognostic value of midregional pro-atrial natriuretic peptide (MR-proANP) in patients with acute ischemic stroke.
Background The rapid and reliable estimation of prognosis in acute ischemic stroke is pivotal to optimize clinical care. MR-proANP, a recently described, stable fragment of the ANP precursor hormone, may be useful in this setting.
Methods In a prospective observational study, we measured MR-proANP on admission in plasma of 362 consecutive patients presenting with acute ischemic stroke. The prognostic value of MR-proANP to predict mortality within 90 days and functional outcome (defined as a modified Rankin Scale of ≤2 or ≥3) was evaluated and compared with the National Institutes of Health Stroke Scale (NIHSS) score.
Results The discriminatory accuracy, calculated with the area under the curve (AUC) of the receiver operating characteristics curve, of MR-proANP to predict death was comparable to the NIHSS (AUC: 0.86 [95% confidence interval (CI): 0.82 to 0.90] and 0.85 [95% CI: 0.81 to 0.89; p = 0.7]). Combined, the accuracy significantly improved (0.92 [95% CI: 0.88 to 0.96; p < 0.01]). The AUC of MR-proANP to predict functional outcome was 0.70 (95% CI: 0.65 to 0.75), similar to the NIHSS (0.75 [95% CI: 0.70 to 0.80]; p = 0.16). The prognostic value of MR-proANP for both outcomes was independent of the NIHSS. Higher MR-proANP concentrations were found in stroke of cardioembolic etiology.
Conclusions MR-proANP is a prognostic marker in the acute phase of stroke, improving the discriminatory value of the NIHSS, independently predicting post-stroke mortality and functional outcome. (The “COSMOS”-Study [Copeptin in Osmoregulation and Stress Assessment]; NCT00390962)
Stroke is the third leading cause of death and the primary cause of long-term disability worldwide (1). The direct and indirect cost of stroke amounted to $65.5 billion in 2008 (2). Each year, over 5 million people die as a consequence of stroke, and at least 1 in 6 patients who survives a stroke will suffer another stroke within 5 years (3). An early risk assessment with estimate of the severity of disease and prognosis could facilitate optimized care and allocation of health care resources (4). Thus, there is the need to develop a credible evidence base of prognostic information for outcomes that are meaningful to patients, including mortality and level of independency. In this context, prognostic markers available during the initial phase after acute stroke would aid in the timely estimation of disease severity, functional outcome, and mortality.
A-type natriuretic peptide (ANP) is a family member of the natriuretic peptides. Its physiological role is mainly the regulation of blood pressure ascribed to its natriuretic, diuretic, and vasodilating action. ANP emerged as reliable prognostic marker for congestive heart failure and risk of cardiovascular events and death (5,6). In the acute phase of ischemic stroke, levels of ANP have been reported to be elevated (7) and to predict mortality (8). Immunohistochemical studies suggest that cerebral ischemia directly induces ANP secretion in brain tissue (9,10). Interestingly, individuals with a homozygous genotype for the ANP stop codon mutation have an increased risk of ischemic stroke (11). Thus, ANP is likely to play a role in the hemodynamic regulation during the acute phase of ischemic stroke.
Midregional pro-ANP (MR-proANP) derives from the precursor hormone of ANP. MR-proANP is released in an equimolar ratio to ANP. The present assay for MR-proANP was designed to detect the midregion of the prohormone, which is more stable than the N- or C-terminal part of the precursor (12). Other proANP assays may underestimate the release of the precursor due to an early degradation of crucial epitopes at the extreme ends of the molecule. The midregional fragment of proANP is also more stable in blood ex vivo, which renders it generally more applicable in clinical practice (13). Fragments of natriuretic prohormones (i.e., MR-proANP and pro-brain natriuretic peptide [proBNP], respectively) predict poor outcomes in patients after acute myocardial infarction and in patients with heart failure (14–18). We hypothesize that MR-proANP, measured in the acute phase after an ischemic stroke, is a good prognostic marker for functional outcome and mortality within 90 days.
Study design and setting
We conducted a prospective cohort study at the University Hospital Basel, Basel, Switzerland. From November 2006 to November 2007, consecutive patients presenting with an acute ischemic cerebrovascular event were included. The primary end point of this study was to evaluate prognostic biomarkers, particularly the arginine vasopressin (AVP) precursor (copeptin) and the precursor hormone of ANP (MR-proANP) to predict outcome in ischemic stroke. A complete description of copeptin and stroke outcome has been reported previously (19). In brief, after approval from the Ethics Committee of the University Hospital Basel was received, written informed consent was obtained from study participants or, if not feasible, from next of kin. A total of 605 consecutive patients with a suspicion of stroke within 72 h before admission at the emergency department were examined.
For the purpose of this study, we evaluated all patients with the final diagnosis of ischemic stroke (n = 362), confirmed by computed tomography and/or magnetic resonance imaging on admission. The other 243 patients had either transient ischemic attack, intracerebral hemorrhage, or other final diagnoses and were excluded from the final analysis. Neurological deficits were assessed using the National Institutes of Health Stroke Scale (NIHSS) prospectively on admission in all patients. Blood samples were collected within 0 to 3 h (n = 78), 3 to 12 h (n = 189), 12 to 24 h (n = 55), and 24 to 72 h (n = 40) from symptom onset. The clinical stroke syndrome was determined by applying the criteria of the Oxfordshire Community Stroke Project; that is, total anterior circulation syndrome (TACS), partial anterior circulation syndrome (PACS), lacunar syndrome (LACS), and posterior circulation syndrome (POCS) (20). Stroke etiology was determined according to the criteria of the TOAST (Trial of Org 10172 in Acute Stroke Treatment) classification (21), which distinguishes large artery arteriosclerosis, cardioembolism, small artery occlusion, other etiology, and undetermined etiology. At discharge from the hospital, each patient received an etiologic diagnosis of stroke.
Follow-up and end points
All patients underwent a structured telephone interview after 90 days in order to identify occurrence and timing of mortality of any cause and functional outcome. Ninety-day outcome was measured by the modified Rankin Scale (mRS), and a favorable outcome was defined as a mRS score of 0 to 2.
Blood was obtained from a venous catheter. Results of the routine blood analyses were recorded. Plasma was frozen at −70°C. MR-proANP was detected in plasma from all patients with a new sandwich immunoassay (BRAHMS AG, Hennigsdorf/Berlin, Germany), as described in detail elsewhere (13). In brief, the lower detection limit of the assay is 6.0 pmol/l. The intra-assay coefficient of variation was 10% for samples containing 23 to 3,000 pmol/l MR-proANP and 20% for samples containing 18 to 22.8 pmol/l. The interassay coefficient of variation was 10% at the concentration of 65 pmol/l MR-proANP and 20% at a concentration of 18 pmol/l MR-proANP. In 325 healthy individuals, the range of MR-proANP concentrations was 9.6 to 313 pmol/l. The median was 45 pmol/l (95% confidence interval [CI]: 43.0 to 49.1 pmol/l) (13).
Discrete variables are expressed as counts (percentage), and continuous variables as medians and interquartile ranges (IQRs). Two-group comparison of not normally distributed data was performed using Mann-Whitney U test and a Kruskal-Wallis 1-way analysis of variance was used for multigroup comparisons. First, the relation of MR-proANP with outcomes (i.e., death and functional outcome in stroke patients) was assessed using logistic regression models. All baseline parameters were analyzed. Thereby, common logarithmic transformation (i.e., base 10) was performed to obtain normal distribution for skewed variables (i.e., MR-proANP concentrations) as the resulting model yielded a smaller Akaike Information Criterion, which was chosen to compare the results. We used crude models and only report odds ratios (ORs) of biological important or significant predictors in our tables. Multivariate models were adjusted for 3 biologically important outcome predictors for the end point mortality (n = 44) to avoid overfitting. For the end point functional outcome, we adjusted for all significant predictors, and then for the 4 main predictors. Note that the OR corresponds to an increase by 1 U in the explanatory variable. In terms of log-transformed MR-proANP values, the OR corresponds to a 10-fold increase.
Second, we compared the overall discriminatory ability of different predictors by calculating receiver-operating characteristic curve (ROC) analysis with the method by DeLong et al. (22). Thereby, the area under the ROC (AUC) is a summary measure over criteria and cut-point choices. The AUC summary equals the probability that the underlying classifier will score a randomly drawn positive sample higher than a randomly drawn negative sample. To test whether the MR-proANP level improves the performance of the NIHSS score, we compared ROCs of the logistic regression model combining the NIHSS score with MR-proANP with a ROC limited to the NIHSS. We also compared ROCs of MR-proANP and copeptin, which is a recently published prognostic biomarker in acute ischemic stroke.
Finally, to study the ability of MR-proANP to predict mortality, we calculated Kaplan-Meier survival curves and stratified patients by quartiles. All testing was 2-tailed, and p values <0.05 were considered to indicate statistical significance. All calculations were performed using STATA version 9.2 (Stata Corp, College Station, Texas).
Of the 362 consecutively enrolled patients with an ischemic stroke, 359 patients completed the 90-day follow-up and were analyzed; 2 patients were lost to follow-up, and 1 patient withdrew informed consent.
The median age of patients was 75 years (IQR 63 to 83 years), and 41% were women. Vital signs assessed on admission revealed a median systolic blood pressure of 160 mm Hg (IQR 140 to −180 mm Hg) and a body temperature of 37.0°C (IQR 36.5°C to 37.4°C). Regarding the neurological deficits on admission, the median NIHSS was 5 points (IQR 2 to 10 points). A total of 275 patients (77%) had a history of hypertension, 93 (26%) had hypercholesterolemia, 71 (20%) had a history of diabetes mellitus, 124 (35%) were smokers, 75 (21%) were diagnosed with atrial fibrillation (AF), 88 (25%) had a history of a previous vascular event, 91 (25%) had coronary heart disease, and 54 (15%) had a history of heart failure. According to the Oxfordshire Community Stroke Project classification, 162 (45%) had a PACS, 41 (11%) a TACS, 74 (21%) a LACS, and 83 (23%) a POCS. Baseline characteristics of the study population are provided in Table 1.
Outcome evaluation of the stroke population after 90 days showed a mortality rate of 12% (n = 44). The functional outcome assessment revealed a median mRS of 2 (IQR 1 to 4) in the whole stroke population, and 42% (n = 151) of patients had an unfavorable functional outcome defined as (mRS >2).
MR-proANP and severity of stroke on admission according to the NIHSS
MR-proANP concentrations increased with increasing severity of stroke as defined by the NIHSS (Fig. 1). MR-proANP levels in patients with a NIHSS of 0 to 6 points (n = 217) were 122.0 pmol/l (IQR 73.4 to 203.5 pmol/l), in patients with a NIHSS of 7 to 15 points (n = 90) 168.5 pmol/l (IQR 100.0 to 286.0 pmol/l), and in patients with a NIHSS >15 points (n = 55) 251.5 pmol/l (IQR 129.0 to 372.5 pmol/l) (p < 0.0001).
MR-proANP and death within 90 days
MR-proANP levels on admission in the 44 patients who subsequently died were about 3-fold increased as compared with survivors (345.0 pmol/l [IQR 232.0 to 465.0 pmol/l] vs. 130.5 pmol/l [IQR 78.2 to 216.5 pmol/l]; p < 0.001) (Fig. 2A). Univariate analysis identified MR-proANP concentrations, age, presence of TACS and POCS, history of heart failure, coronary artery disease, renal insufficiency, small vessel disease, and the NIHSS as predictors for death (Table 2). Thereby, the unadjusted OR of log-transformed MR-proANP was 128.7 (95% CI: 29.7 to 557.1), and for MR-proANP quartiles, it was 4.7 (95% CI: 2.8 to 8.0). After combining MR-proANP in bivariate logistic regression analysis with each predictor alone, it remained an independent predictor. In addition, multivariate analysis restricted to the 4 main predictors, age, the NIHSS, and TACS, MR-proANP remained an independent predictor for mortality with an adjusted OR of 61.01 (95% CI: 9.87 to 377.93); similarly after adjustment for age, the NIHSS, and heart failure, the adjusted OR was 62.83 (95% CI: 9.60 to 411.28) (Table 3). ROCs demonstrated a discriminatory accuracy (AUC) to predict mortality for MR-proANP of 0.86 (95% CI: 0.82 to 0.86), which was in the range of the NIHSS (AUC: 0.85 [95% CI: 0.78 to 0.91]) and copeptin (AUC: 0.82 [95% CI: 0.76 to 0.89]). MR-proANP had a better predictive value as compared with CRP (AUC: 0.70 [95% CI: 0.60 to 0.70]; p < 0.05) and glucose (AUC: 0.57 [95% CI: 0.47 to 0.66]; p < 0.01). The combination of MR-proANP and the NIHSS in a combined logistic model had a significantly higher discriminatory accuracy (AUC: 0.92 [95% CI: 0.88 to 0.96]) than the AUC of the NIHSS or MR-proANP alone (p < 0.01 and p < 0.01, respectively) (Fig. 3). Also, the combination of the MR-proANP and copeptin improved the discriminatory accuracy of copeptin alone (AUC: 0.89 [95% CI: 0.84 to 0.93]; p = 0.04). Adding copeptin to the logistic model of MR-proANP and the NIHSS did not further improve the model's discriminatory ability and revealed an AUC of 0.92 (95% CI: 0.88 to 0.96).
The time to death in the 90-day follow-up was analyzed using Kaplan-Meier survival curves based on MR-proANP quartiles. As demonstrated in Figure 4, patients in higher MR-proANP quartiles had an increase in the risk of mortality.
MR-proANP and functional outcome of stroke patients within 90 days
MR-proANP levels in patients with an unfavorable outcome were about 2-fold higher compared with patients with a favorable outcome (213.0 pmol/l [IQR 119.0 to 333.0 pmol/l] vs. 119.0 pmol/l [IQR 72.8 to 187.0 pmol/l], p < 0.0001) (Fig. 2B). In univariate logistic regression analysis, we calculated the predictive value of MR-proANP as compared with the NIHSS and other risk factors (Table 2). With an unadjusted OR of 10.06 (95% CI: 4.71 to 21.52), for log-transformed MR-proANP levels and 1.9 (95% CI: 1.6 to 2.4) for MR-proANP quartiles, MR-proANP was a strong predictor of outcome. Comparing MR-proANP with each significant outcome predictors in a bivariate regression model, MR-proANP remained an independent predictor (adjustment for the NIHSS revealed an OR of 5.78 [95% CI: 2.60 to 12.97; p < 0.001], for age an OR of 4.88 [95% CI: 2.08 to 11.46; p < 0.001], for female sex an OR of 9.30 [95% CI: 4.33 to 19.97; p < 0.001], for heart failure an OR of 9.07 [95% CI: 4.10 to 20.05; p < 0.001], for AF an OR of 10.08 [95% CI: 4.45 to 22.87; p < 0.001], for renal insufficiency an OR of 7.73 [95% CI: 3.44 to 17.35; p < 0.001], for CRP an OR of 6.47 [95% CI: 2.82 to 14.83; p < 0.001], for the Charlson Index an OR of 8.41 [95% CI: 3.84 to 18.41], and for the presence of TACS an OR of 9.34 [95% CI: 4.28 to 20.34; p < 0.001]). When combining all significant predictors in a multivariate model, only age, the Charlson score, and the NIHSS remained independent predictors for functional outcome.
With an AUC of 0.70 (95% CI: 0.65 to 0.75) to predict functional outcome, MR-proANP had a significantly higher prognostic discriminatory capacity as compared with TACS and sex, and was within the range of copeptin, the NIHSS, and age (Table 4). In addition, MR-proANP tended to improve the NIHSS with an AUC of the combined model of 0.79 (95% CI: 0.74 to 0.83; p = 0.05).
MR-proANP in different stroke etiologies
When dividing patients into 4 subgroups based on stroke etiology, 18% (n = 65) of patients were allocated to the large artery atherosclerosis group, 36% (n = 131) to the cardioembolism (CE) group, 15% (n = 55) to the small vessel occlusion group, 4% (n = 16) to the group of other etiologies (e.g., dissection), and 26% (n = 92) to the group with undetermined etiology. MR-proANP levels were highest in patients with CE etiology (206 pmol/l [IQR 119 to 326 pmol/l]), significantly higher as compared with other etiologies (124 pmol/l [IQR 73 to 207 pmol/l]; p < 0.0001). Logistic regression analysis revealed that MR-proANP was significantly associated with CE etiology (unadjusted OR of 7.1 [95% CI: 2.6 to 19.4]), independent of history of chronic heart failure (adjusted OR: 6.0 [95% CI: 2.3 to 13.9]) and atrial fibrillation (adjusted OR: 14.8 [95% CI: 1.2 to 6.1]) and hypertension (OR: 1.5 [95% CI: 0.80 to 2.91]). ROC analysis showed an AUC of 0.68 (95% CI: 0.62 to 0.74) for cardioembolic etiology. The optimal biomarker cutoff point for discriminating the presence or absence of a cardioembolic source was determined to be >180 pg/ml with a specificity of 60.3% (95% CI: 51.2 to 68.9), sensitivity of 71% (95% CI: 64.6 to 76.8), a positive likelihood ratio of 2.0, and a negative likelihood ratio of 0.6.
To estimate whether MR-proANP improved the diagnosis of CE etiology by already known clinical information, we calculated logistic models based on clinical information (age, known heart failure, and known AF on admission) and combined models based on clinical information plus MR-proANP concentrations. The model including MR-proANP (AUC: 0.81 [95% CI: 0.77 to 0.86]) was significantly better than the model based on clinical information alone (AUC: 0.76 [95% CI: 0.71 to 0.81]; p < 0.001).
MR-proANP levels in the subgroup of patients with heart failure or AF
In 54 (15%) patients with known chronic heart failure on admission, MR-proANP levels were higher as compared with patients without chronic heart failure (271 pmol/l [IQR 162.5 to 383.8] vs. 132.0 pmol/l (IQR 78.1 to 216.6]; p < 0.001). MR-proANP remained a significant predictor for both mortality and functional outcome after adjustment for heart failure with ORs of 148.83 (95% CI: 32.16 to 688.67) and 9.07 (95% CI: 4.10 to 20.05), respectively. In addition, ROC analysis showed a similar predictive value of MR-proANP for both outcomes in patients with and without heart failure (data not shown).
Similarly, in 75 (21%) patients with AF, MR proANP levels were higher (258.5 pmol/l [IQR 181.8 to 380.0 pmol/l]) as compared with patients without AF (123.5 pmol/l [IQR 74.2 to 213.0 pmol/l]; p < 0.001). Again, MR-proANP remained a significant predictor for both outcomes after adjustment for AF. ROC analysis showed a similar predictive value of MR-proANP for both outcomes in patients with and without AF (data not shown).
MR-proANP levels on admission were increased in stroke patients, with particularly prominently elevated levels in patients with cardioembolic strokes. MR-proANP proved to accurately predict 90-day mortality and functional outcome, independent of other comorbidities such as chronic heart failure and AF, age, and clinical scores. Importantly, MR-proANP improved the prognostic value of the NIHSS. To our knowledge, this is the first prospective study evaluating MR-proANP levels in a large cohort of stroke patients.
Elevated concentrations of natriuretic peptides, especially BNP, have been shown to be of prognostic value in patients with congestive heart failure and myocardial ischemia (assessed by electrocardiographic changes) (18,23,24). Recently, MR-proANP levels were also evaluated in patients with heart failure showing comparable prognostic capabilities to BNP values with respect to 1-year all-cause mortality (25). Hence, higher natriuretic peptide levels reflect a greater degree of hemodynamic dysfunction and explain the increased mortality in patients with acute cardiac disease. A role of natriuretic peptides in the hemodynamic regulation has also been shown during the acute phase of ischemic stroke (7,26–28). Clinical studies have revealed elevated levels of natriuretic peptides in the acute phase of ischemic stroke (8,28–30). One study (8) reported elevated levels of BNP and ANP in 51 ischemic stroke patients compared with healthy controls and higher levels of natriuretic peptides in patients who died as compared with those who survived. BNP and its N-terminal peptide (NT-proBNP) has been demonstrated to be excellent markers for vascular mortality and re-events in stroke (6) although NT-proBNP levels on admission were not significantly associated with functional outcome within 3 months (30) if adjusted for vascular risk factors in another study. Estrada et al. (7) investigated ANP concentrations in 37 patients with acute ischemic stroke. Compared with healthy controls, concentration of ANP increased immediately after stroke and remained elevated for 7 days. We found no published data on ANP or its precursor protein on the independent predictive value concerning mortality as well as functional outcome after an acute ischemic stroke.
The relation of natriuretic peptides and stroke prognosis seems not to be monocausal and is complex. First, it has been demonstrated that a higher level of NT-proBNP in stroke patients is associated with increased sympathetic activation. Sympathetic activation by itself is a prognostic determinant after an acute thromboembolic stroke (31,32). Second, previous studies have shown that heart failure is associated with dependency after stroke (27) and that it is an independent predictor for mortality after first cerebral infarction (33–35).
In our study, unadjusted and adjusted logistic regression analysis revealed that levels of MR-proANP were predictors for 90-day mortality and functional outcome, independently of the presence of heart failure or AF. The pathophysiological mechanism explaining this independent predictive value of MR-proANP observed in our study remains to be clarified. It may be hypothesized that high MR-proANP concentrations indicate the presence of a profound neurohormonal dysfunction, and thus a worse outcome. Furthermore, increased MR-proANP levels might mirror, not only manifest heart failure, but also a beginning cardiac pathology (e.g., subclinical heart failure) in which intracardial thrombus development might be more likely. This would explain the additional diagnostic value of MR-proANP levels to differentiate CE etiologies from others. It is essential to identify the CE etiology in stroke because recurrent stroke occurs within 2 weeks in up to 12% of patients who initially experience embolic stroke from cardiac sources (36). AF might be no longer present when patients are examined by 24-h electrocardiography monitoring. Thus, anticoagulant therapy might be delayed even when the neurologist suspects an embolic origin due to distinct patterns of lesions. Using biomarkers may be a reasonable strategy to improve the identification of cardioembolic stroke already in the acute phase, thus rapidly point to need of other diagnostic tests and accelerating the start of optimal secondary prevention (26).
Other known mediators involved in the ischemic cascade are markers for neuronal cell death, such as protein S-100β (37), inflammation markers, such as interleukin-6 (38), or markers for oxidative stress and blood-brain barrier disruption, such as matrix metalloproteinase-9 (39,40). Although these biomarkers reliably mirror the initial stroke severity (NIHSS and lesion size) and some even bear an association with outcome, they were not able to independently predict functional outcome and death within 3 months as well as to improve the NIHSS. To our knowledge, only 1 circulation biomarker, copeptin, the c-terminal part of the AVP prohormone, was able to significantly improve prediction of clinical outcome after stroke for death and functional outcome (19). Copeptin is released in an equimolar ratio to AVP and is more stable in the circulation and easier to determine as AVP (41). Interestingly, MR-proANP seems to be a better predictor for mortality, whereas copeptin had a higher prognostic accuracy to predict functional outcome. One reason for the absence of a “unique” biomarker pre-eminently mirroring all aspects of prognosis might be that the complexity of brain ischemia and recovery capacities is less amenable to the use of a single biochemical marker. In the difficult task of outcome prediction, it seems, therefore, reasonable to rely on several parameters, each mirroring different pathophysiological aspects. The approach of using a multiple biomarker panel has already been well established in the clinical setting of patients with cardiovascular disease (6,42). A model combining biomarkers and clinical parameters might also be the most promising approach to predict outcome in stroke patients.
We are aware of the following limitations. First, our study is a single-center study and should be externally validated in a large cohort of patients. Second, we did not directly compare the prognostic value of MR-proANP with other natriuretic peptides, especially B-type natriuretic peptides. However, this study shows promising data for a further multicenter trial including MR-proANP in a prognostic biomarker panel.
The present study shows that MR-proANP is a new, valuable marker for the prognosis in patients with ischemic stroke. It also seems to act as a diagnostic marker by differentiating patients with a CE etiology of stroke from other etiologies, especially when combining it with clinical information. Early risk assessment in acute ischemic stroke may allow for better and earlier intervention and improved care strategies to effectively change the dismal natural history of stroke.
The authors are grateful to the nurses, ward physicians, and patients who participated in the study, the department of neurology, and the emergency department. They thank the staff of the central laboratory of the University Hospital Basel for their assistance and technical support.
The study was supported by in-house grants of the Department of Endocrinology, Diabetology, and Clinical Nutrition, research grants from the Swiss National FoundationPP00P3-123346 (to Dr. Christ-Crain) and in-house grants of the Department of Neurology of the University Hospital of Basel, Switzerland, as well as by a personal grant for young investigators to Dr. Katan from the University of Basel. Dr. Morgenthaler is an employee of BRAHMS, the manufacturer of the MR-proANP assay (BRAHMS MR-proANP LIA, BRAHMS AG, Hennigsdorf/Berlin, Germany). Drs. Müller and Schuetz have served as consultants and received payment from BRAHMS for meetings, speaking engagements, or research unrelated to this trial. Dr. Kappos has received payment from several companies regarding his research within the field of multiple sclerosis unrelated to this trial. All other authors have reported that they have no relationships to disclose. Drs. Müller and Christ-Crain are joint senior authors on this study.
- Abbreviations and Acronyms
- atrial fibrillation
- A-type natriuretic peptide
- area under the curve
- arginine vasopressin
- confidence interval
- interquartile range
- lacunar syndrome
- midregional pro-atrial natriuretic peptide
- modified Rankin Scale
- National Institutes of Health Stroke Scale
- odds ratio
- partial anterior circulation syndrome
- posterior circulation syndrome
- pro-brain natriuretic peptide
- receiver-operating characteristic curve
- total anterior circulation syndrome
- Received June 18, 2009.
- Revision received January 20, 2010.
- Accepted February 25, 2010.
- American College of Cardiology Foundation
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