Skip main navigation

Brain Natriuretic Peptide and Discovery of Atrial Fibrillation After Stroke

A Subanalysis of the Find-AFRANDOMISED Trial
Originally published 2020;51:395–401


Background and Purpose—

Diagnosing paroxysmal atrial fibrillation (pAF) can be challenging after acute ischemic stroke. Enhanced and prolonged Holter-ECG monitoring (EPM) improves the detection rate but is not feasible for all patients. We hypothesized that brain natriuretic peptide (BNP) may help to identify patients with stroke at high risk for pAF to select patients for EPM more effectively.


Patients with acute cerebral ischemia ≥60 years presenting in sinus rhythm and without history of AF were included into a prospective, randomized multicenter study to receive either EPM (3× 10-day Holter-ECG) or usual stroke care diagnostic work-up. BNP plasma levels were measured on randomization and 3 months thereafter. Levels were compared between patients with and without pAF detected by means of EPM or usual care. Furthermore, the number needed to screen for EPM depending on BNP cut offs was calculated.


A total of 398 patients were analyzed. In 373 patients (93.7%), BNP was measured at baseline and in 275 patients (69.1%) after 3 months. pAF was found in 27 patients by means of EPM and in 9 patients by means of usual care (P=0.002). Median BNP was higher in patients with pAF as compared to patients without AF in both study arms at baseline (57.8 versus 28.3 pg/mL in the EPM arm, P=0.0003; 46.2 versus 27.7 pg/mL, P=0.28 in the control arm) and after 3 months (74.9 versus 31.3 pg/mL, P=0.012 in the EPM arm, 99.3 versus 26.3 pg/mL, P=0.02 in the control arm). Applying a cut off of 100 pg/mL, the number needed to screen was reduced from 18 by usual care to 3 by EPM.


BNP measured early after ischemic stroke identifies a subgroup of patients with stroke at increased risk for AF, in whom EPM is particularly efficacious.


URL: Unique identifier: NCT01855035.


Atrial fibrillation (AF) is the most frequent cardiac arrhythmia with a prevalence up to 3% which may rise further in increasingly aging societies.1 AF is one of the most important stroke risk factors and up to 20% of ischemic strokes are attributed to AF.2 Furthermore, AF-related strokes are more severe and associated with increased mortality and recurrence rates.3 There is an ongoing discussion on whether the exact rate of thromboembolic events in paroxysmal AF (pAF) is similar4,5 or lower compared with permanent AF.6,7 Nevertheless, the detection of both pAF and permanent AF is of vital importance for patients with acute ischemic stroke, since recurrent events can be prevented effectively by changing the secondary preventive approach from thrombocyte inhibitors to oral anticoagulation.3

Yet, especially the diagnosis of brief and asymptomatic paroxysmal episodes of pAF can be challenging.8 Although it is well-documented that enhanced and prolonged Holter-ECG monitoring (EPM) significantly improves the detection rate of pAF compared with usual care,9,10 EPM is often assumed to be uncomfortable for the patient and data analysis is very time-consuming. Furthermore, the cost-effectiveness of EPM in patients with stroke has been questioned,11 and health system’s resources are limited. Thus not every patient can receive EPM in a real-life-scenario.

Hence, there is a need to identify patients at a high risk for pAF to reduce the number of patients requiring prolonged monitoring. Various scores have been developed to determine the AF risk comprising either cardiovascular risk factors, pathological echocardiographic findings, racial and geographic backgrounds, or biomarkers.12,13 Nevertheless, their application in everyday clinical routine is limited.

Brain natriuretic peptide (BNP) is a neurohormone that is synthesized and released either by the ventricular and atrial myocardium under conditions of myocardial stretch or by the brain after ischemic stroke.14,15 It has been found that natriuretic peptides may be elevated in patients with pAF or persistent AF in many different clinical settings as well as in the general population.16–19 One promising approach in clinical stroke work-up could be the simple analysis of natriuretic peptides which have proven to be elevated in patients with AF.12,20–22

Therefore, we hypothesized that BNP may provide useful information to identify ischemic stroke patients at high risk for pAF to efficaciously select patients for EPM.


The basic data for the findings of this study are available from the corresponding author upon reasonable request. Find-AFRANDOMISED was registered. The current subanalysis was not prespecified.

Study Design and Patient Population

Find-AFRANDOMISED was an investigator-initiated prospective, randomized, controlled, open-label multicenter study, which included acute ischemic stroke patients ≥60 years of age irrespective of the suspected stroke cause, with sinus rhythm on admission ECG. Results of the study and protocol details have been published recently.9

Consecutive patients were included at 4 study sites in Germany between May 2013 and August 2014. Patients were randomized 1:1 to either EPM by means of repeated 10-day Holter-ECG monitoring (at randomization, after 3 and after 6 months) or the respective in-house standard-of-care procedures of diagnostic stroke cause work-up. The primary outcome parameter was AF, which was defined as at least one episode of ≥30 seconds duration, judged by an end point committee that was blinded to all clinical data including BNP plasma levels.

For the present analysis, patients underwent BNP sampling at randomization and 3 months thereafter. The time point of the second BNP analysis was chosen to exclude higher BNP levels due to an increased release by the brain after a recent cerebral infarction. Plasma levels of BNP were measured by means of a sandwich chemiluminescence immunoassay on the ADVIA Centaur (Bayer Diagnostics, Munich, Germany). Personnel responsible for the determination of BNP levels were blinded to clinical patient data including all Holter-ECG monitoring results. Although a specific cut off for BNP was not predetermined, we chose a cut off of BNP ≥100 pg/mL for investigating the yield of prolonged monitoring according to current literature.23,24 Furthermore, different cut offs were calculated to justify the chosen BNP cut off.

The study complies with the Declaration of Helsinki. The protocol was approved by the local ethics committee of each study site, and all patients gave written informed consent for study procedures, including Holter-ECG monitoring, BNP testing, and data collection for all data reported here.


The statistical analyses were performed with SPSS version 24.0 (SPSS, Inc). Continuous values are given as mean ± SD, nominal variables as count and percentages. Non-normally distributed variables are expressed as median values with the corresponding interquartile range (IQR). Normally distributed data were compared by Student t test, not normally distributed data by Mann-Whitney U test. A 2-sided P≤0.05 was considered to indicate a statistically significant difference. The predictive ability of BNP for AF was checked by receiver operating characteristic curves. The area under the curve (AUC) was calculated and tested. The number needed to screen was calculated as 1/(AF rate(EPM arm)−AFrate(usual care arm)). To assess how meaningful the National Institutes of Health Stroke Scale (NIHSS) and BNP are for the prediction of AF, we computed C statistics for the Cox regression model predicting AF from NIHSS, BNP, and both. The 95 CI for the C statistics and their pairwise differences as well as the P values for the null hypotheses that a C statistic equals 0.5 or a difference of 2 C statistics equals zero was computed by the jackknife method.


A total of 402 patients were enrolled and randomized. Four patients were randomized erroneously and in 25 patients no BNP sample was available. Thus the data of 373 patients were finally analyzed. In 275 patients (73.7%) BNP was measured at baseline (immediately after randomization) and additionally at the 3 months visit (median duration between symptom onset and baseline 3 days [IQR, 2–5 days] and for the 3 months visit 95 days [IQR, 90–102 days], respectively).

Of the 373 patients with a BNP sample at baseline, 186 patients were randomized to EPM and 187 patients to usual care. pAF was detected in 34 patients (26 patients by means of EPM and 8 patients by means of usual care, 76.5% versus 23.5%, P=0.001). Details of pAF detection by EPM have been published previously. Sixty-seven percent of pAF cases were detected within the first 10-day Holter ECG, 22% in the second and 4% in the third Holter ECG. The mean time from randomization to detection of AF was 35 days in the EPM group (SD 51 days) and 37 days in the usual care group (SD 60 days, P=0.92).

Baseline characteristics of all patients divided into groups according to the availability of BNP measurements are summarized in Table 1. No statistically significant differences were detected between patients with and without BNP determination.

Table 1. Baseline Characteristics of the Study Population

BNP Measured at Baseline, n=373 (93.7%)BNP Not Measured at Baseline, n=25 (6.3%)P Value
Mean age, y72.7 (SD 7.6)71.8 (SD 5.0)0.38
Female sex149 (39.9%)11 (44.0%)0.69
Medical history
 Arterial hypertension298 (79.9%)18 (72.0%)0.35
 Diabetes mellitus105 (28.2%)3 (12.0%)0.10
 Hyperlipidemia155 (41.6%)9 (36.0%)0.59
 Smoking status
  Current smoker68 (18.2%)2 (8.0%)0.28
  Previous smoker113 (30.3%)3 (12.0%)0.07
 Body mass index ≥25267 (74.6%)13 (59.1%)0.11
 Previous ischemic stroke75 (20.1%)2 (8.0%)0.19
 Previous TIA31 (8.4%)0 (0.0%)0.24
 Myocardial infarction35 (9.4%)3 (12.0%)0.72
 Coronary artery disease57 (15.3%)4 (16.0%)1.00
 Heart failure19 (5.1%)1 (4.0%)1.00
 Dilated cardiomyopathy3 (0.8%)0 (0.0%)1.00
 Peripheral artery disease23 (6.2%)0 (0.0%)0.38
Echocardiographic parameters
 Mean left ventricular enddiastolic diameter, mm46.5 (SD 8.6)47.6 (SD 7.4)0.63
 Mean left ventricular endsystolic diameter, mm34.3 (SD 10.1)30.8 (SD 2.3)0.33
 Mean left atrial diameter, mm40.9 (SD 10.8)43.3 (SD 7.3)0.39
 Mean left ventricular ejection fraction, %59.7 (SD 9.2)60.9 (SD 14.1)0.58
TOAST classification
 Large artery sclerosis5 (1.3%)2 (8.0%)0.07
 Cardioembolism75 (20.1%)0 (0.0%)0.07
 Small vessel occlusion110 (29.5%)8 (32.0%)0.79
 Stroke or other identified cause1 (0.3%)0 (0.0%)1.00
 Stroke of unknown cause182 (48.8%)15 (60.0%)0.28
Score on NIHSS
 Median NIHSS (IQR)3 (1–5)2 (1–4)0.50
AF detected within the study34 (9.1%)2 (8.0%)1.00

AF indicates atrial fibrillation; BNP, brain natriuretic peptide; IQR, interquartile range; NIHSS, National Institutes of Health Stroke Scale; TIA, transient ischemic attack; and TOAST, Trial of ORG 10172 in Acute Stroke Treatment.

The analysis of BNP values in patients with paired BNP samples (n=275), showed concentrations that ranged from <10 to 1042.0 pg/mL (median, 24.8 pg/mL, IQR, 11.2–55.5 pg/mL) at baseline and from <10 to 498.6 pg/mL (median, 31.9 pg/mL, IQR, 16.4–66.3 pg/mL) 3 months thereafter (P=0.006).

BNP values at baseline and after 3 months were significantly higher in patients with pAF compared to those without pAF. At baseline the median BNP value was 53.5 pg/mL (IQR, 29.9–175.4 pg/mL) in patients with pAF and 27.9 pg/mL (IQR, 12.0–62.0 pg/mL) in patient without AF (P=0.0002). After 3 months, it was 81.2 pg/mL (IQR, 34.3–143.5 pg/mL) in patients with pAF and 30.1 pg/mL (IQR, 16.0–59.9) in patients without AF (P=0.001).

A more detailed analysis considering pAF duration in the EPM group showed similar BNP values in patients with various durations of pAF episodes (median BNP [IQR] was 53.5 pg/mL [29.0–158.8 pg/mL] for pAF >30 seconds to <6 minutes [n=8]; 35.0 pg/mL [22.0–139.0 pg/mL] for pAF >6 minutes to <6 hours [n=5]; 51.0 pg/mL [47.5–139.5 pg/mL] for pAF >6 hours to <24 hours [n=3] and 97.0 pg/mL [52.8–198.0 pg/mL] for pAF >24 hours [n=8]).

Patients with pAF detected by EPM showed similar BNP values as compared to pAF detected by usual care (Figure 1 and Table 2).

Table 2. BNP Levels in Patients With and Without AF in Dependency of the Randomization Group

Usual CareEPMP Value*
 AFn=8; 46.2 (19.6–91.8)n=26; 57.8 (33.6–198.2)0.39
 No AFn=179; 27.7 (11.3–65.0)n=160; 28.3 (12.9–60.2)0.97
P value0.280.0003
3 mo
 AFn=6; 99.3 (45.3–203.3)n=19; 74.9 (29.0–110.7)0.48
 No AFn=133; 26.3 (13.0-60.9)n=117; 31.3 (19.5–59.4)0.26
P value0.020.012

AF indicates atrial fibrillation; BNP, brain natriuretic peptide; EPM, enhanced and prolonged Holter-ECG monitoring; and IQR, interquartile range.

*P level comparing usual care and EPM.

†Median BNP value (IQR), pg/mL.

P level comparing patients with and without AF.

Figure 1.

Figure 1. Brain natriuretic peptide (BNP) in patients with and without arial fibrillation (AF) depending on the randomization group at baseline and 3 months thereafter. EPM indicates enhanced and prolonged Holter-ECG monitoring.

The diagnostic accuracy of BNP in detecting pAF for the whole cohort was tested by means of a receiver operating characteristic analysis. The AUC was 0.68 (95% CI, 0.58–0.79, P=0.03) regarding BNP at baseline and 0.71 (95% CI, 0.60–0.82, P=0.01) regarding BNP measured after 3 months. We also calculated the AUC for EPM and usual care with respect of heart failure, which varied between 0.72 (EPM group) and 0.61 (usual care group) among patients with heart failure (Figure 2A through 2C and in the online-only Data Supplement).

Figure 2.

Figure 2. Receiver operating curve of brain natriuretic peptide (BNP) plasma levels at baseline and 3 mo thereafter for the detection of paroxysmal atrial fibrillation (AF). A, Receiver operating characteristics for BNP at baseline and 3 mo for the detection of AF. The area under the curve (AUC) using BNP to predict paroxysmal AF was 0.68 (95% CI, 0.58–0.79, P=0.03) and 0.71 (95% CI, 0.60–0.82, P=0.01) at baseline and 3 months thereafter, respectively. B, Receiver operating characteristics for BNP at baseline for the enhanced and prolonged Holter-ECG monitoring (EPM) group. The AUC using BNP to predict paroxysmal atrial fibrillation (pAF) was 0.72 (95% CI, 0.62–0.83). C, Receiver operating characteristics for BNP at baseline for the usual care group. The AUC using BNP to predict pAF was 0.61 (95% CI, 0.42–0.81).

Previous publications proposed a BNP cutoff of 100 pg/mL for preselecting patients for prolonged monitoring.23 In patients with BNP values ≥100 pg/mL at baseline, the pAF detection rate was 32.4% in the EPM arm (11/34 patients), versus 3.6% in the usual care arm (1/28 patients, absolute difference 28.8%). This resulted in a number needed to screen of 3. In patients with BNP values below the cut off of 100 pg/mL, pAF was found in 9.9% of the patients (15/137 patients) by means of EPM and in 4.4% of the patients with pAF (7/152 patients) by means of usual care (absolute difference 5.5%), resulting in a number needed to screen of 18 (Figures 3 and 4).

Figure 3.

Figure 3. Patients with atrial fibrillation (AF) detected and patients needing monitoring. Percentage of patients needing monitoring and percentage of patients with detected AF for specific brain natriuretic peptide (BNP) cut offs. If, for example, only patients with BNP ≥30 pg/mL would have undergone enhanced and prolonged Holter-ECG monitoring (EPM), only 50% of the population would need monitoring, but 83% of all AF cases would have been detected. The number needed to screen (NNS) would be 6 in this case.

Figure 4.

Figure 4. The diagnostic value of a cut off brain natriuretic peptide (BNP) value of ≥100 pg/mL. EPM indicates enhanced and prolonged Holter-ECG monitoring; and NNS, number needed to screen.

NIHSS at baseline was not significantly different between those patients with detection of pAF detected opposed to those without in either group (median NIHSS 6 [4;9] versus 2 [1;4], P=0.062 in the control group and 4 [2;4] versus 3 [1;5], P=0.533 in the intervention group). Cox models for the prediction of AF by NIHSS, BNP, and both and their C statistics are displayed in Table I in the online-only Data Supplement. Both variables were associated with incident AF. Data suggest that BNP might be the ultimate predictor while NIHSS does not add predictive information (even if the formal significance in the comparison of C statistics was not reached.


Major Findings

Within the current analysis of the Find-AFRANDOMISED study cohort, we evaluated whether increased BNP plasma levels are helpful to select patients, who benefit from EPM with respect to the detection of pAF. We observed significantly elevated BNP plasma levels in acute ischemic stroke patients ≥60 years of age with pAF detected within 6 months after the index stroke. Although pAF detection rates were significantly lower in the usual care group as has been published previously,9 there was no difference between BNP plasma levels between the 2 randomization groups. This finding leads to the conclusion that pAF, which was only detected by EPM, leads to the same release of BNP as easily detectable AF, found by usual care monitoring. Patients with elevated BNP ≥100 pg/mL benefitted more from EPM than patients with BNP <100 pg/mL (number needed to screen 3 versus 18, respectively), which indicates that patients with BNP ≥100 pg/mL measured 3 days after the index stroke should definitely undergo EPM.

Optimal Time Point for BNP Determination to Identify pAF After Stroke

Several studies have found elevated levels of natriuretic peptides in stroke patients with AF as compared to patients without AF.22,25–27 The median BNP in patients with AF in our cohort was 53.5 pg/mL (IQR, 29.9–175.4 pg/mL) at baseline and 81.2 pg/mL (IQR, 34.3–143.5 pg/mL) after 3 months which is lower than previously reported.22,25–27 Apart from differences in comorbidities and patients’ characteristics 2 further aspects may explain this difference: first, BNP rises early after stroke in patients with or without AF, presumably explained by BNP release from the brain.22 Previous studies mostly measured BNP within 24 hours after stroke,18,28 whereas BNP was measured 3 days after stroke in our study. BNP measured within 24 hours after stroke in patients with AF has been found to be nearly twice as high as 3 days later (173.2 versus 81.9 pg/mL).15 Given the short half-life of BNP (20 minutes),29 samples taken shortly after the stroke event contain BNP not only from heart but also from the damaged brain tissue. However, after 3 days, that is, after >200 half-lives, BNP is expected to be predominantly of cardiac origin. We conclude that BNP detected after 3 days is more likely to be associated with underlying AF compared to results from very early blood sampling. This hypothesis is further supported by the fact that BNP levels after 3 months were slightly higher than those determined 3 days after stroke. If a significant amount of BNP measured 3 days after stroke derived from the brain, we would expect to have measured lower rather than higher BNP levels after 3 months. The slightly more elevated BNP levels after 3 months may partly be explained by a higher and progressive cardiovascular morbidity after hospitalization and by immobility.30

A second explanation for similar levels of BNP in AF versus non-AF patients in our study could be the fact that patients with pAF identified in the EPM arm had AF at an earlier stage with shorter AF duration and were, therefore, associated with lower BNP values as compared to easier to detect AF in the control arm. However, there was no significant difference in BNP levels between AF patients in both trial arms. A similar finding was reported in previous studies20,31 and also shown in an earlier reported study cohort of our study group.22 We, therefore, conclude that EPM identifies AF patients with a similar activation of BNP release as patients identified by standard ECG monitoring.

Discriminatory BNP Value and Cutoffs

The discriminatory value of BNP for the detection of patients with pAF was only moderate in our collective of stroke patients ≥60 years of age (mean age 72.7±7.6 years) (AUC 0.68 at baseline and 0.71 at 3 months thereafter). We obtained a similar result for the BNP AUC in our previous observational study (best AUC 0.75). In the Find-AF trial, BNP samples were collected within 24 hours after admission and elevated plasma BNP levels predicted the detection of pAF within a 7-day Holter-ECG.22 Other studies described AUCs between 0.82 and 0.89 in patients with stroke or transient ischemic attack, in whom telemetry or Holter-ECG of up to 3 days were performed during hospitalization.25–27 However, AF detected during limited ECG monitoring probably represent more advanced stages of disease. In contrast, more prolonged ECG monitoring also reveals shorter episodes of pAF, which presumably represents earlier stages of disease that were in sinus rhythm at the time of blood sampling. EPM initiated after the measurement of elevated BNP levels of ≥100 pg/mL may reveal this hard to detect AF, which cannot be detected by usual care Holter-ECG monitoring or telemetry during hospitalization.

Analyzing the ECGs of patients divided into 2 groups with BNP values below or above the cut off of 100 pg/mL, 32.4% of all patients with AF were detected by means of EPM and only 3.6% by means of usual stroke diagnostic work-up (Figure 4). This leads to the conclusion that BNP values ≥100 pg/mL may help to identify stroke patients at special risk for pAF to select patients for EPM effectively. Currently, there is no established optimal cut off value for BNP32 and various publications recommended cut offs for BNP ranging from 65 to 144 pg/mL.22,25–27 Our cut off of 100 pg/mL lies in the middle of this range and in line with recent consensus recommendations.23 Yet, the choice of a cut off value for AF risk stratification regarding EPM is a compromise between screening costs for the discovery of patients with AF and risk of recurrent strokes in patients without prevention due to undiscovered AF.

Clinical Relevance of pAF Detected by Short-Term or Continuous Monitoring

Besides Find-AFRANDOMISED9 2 other randomized trials have compared prolonged monitoring with usual care ECG to detect pAF in stroke patients. The EMBRACE trial (30-Day Cardiac Event Monitor Belt for Recording Atrial Fibrillation After a Cerebral Ischemic Event) included 572 patients with cryptogenic strokes, who underwent additional ECG monitoring with either an externally applied 30-day event recorder or a conventional 24-hour Holter-ECG.33 The CRYSTAL-AF study (Cryptogenic Stroke and Underlying Atrial Fibrillation) randomized 441 patients with cryptogenic stroke to either an implantable cardiac monitor or usual care.9 Significantly more cases of pAF were found in the intervention arms of all 3 studies as compared to the usual care arms. The minimum duration of clinical relevant pAF episodes probably depends on the duration and type of monitoring. We suggest that even short AF episodes of >30 seconds during a 10-day Holter-ECG monitoring are precursors of clinically relevant AF. This is supported by the finding of no additional AF cases detected within 6 to 12 months after randomization in the EPM arm in comparison to 3 cases in the usual care arm in Find-AFRANOMISED. In CRYSTAL-AF, pAF episodes >2 minutes were detected in 30% of patients randomized to an implantable loop recorder within 3 years after randomization. However, the pAF detection rate in the control arm was only 3% after 3 years. Observation trials over 30 months in patients without prior stroke but with increased cardiovascular risk profile have established that continuous monitoring may find AF >2 minutes in up to 40% of patients. Only 10% of these episodes lasted >24 hours.34 The ASSERT study (Asymptomatic Atrial Fibrillation and Stroke Evaluation in Pacemaker Patients and the Atrial Fibrillation Reduction Atrial Pacing) showed only pAF episodes exceeding 24 hours increase the risk of stroke in stroke-naïve patients with implanted pacemakers or defibrillators.35 Hence, we propose a cut off of clinically relevant AF of 30 seconds in patients monitored for ≤10 days, while a cut off of 24 hours may be appropriate for stroke-naïve patients undergoing continuous monitoring.

Clinical Implications

Interestingly, BNP is currently only considered for the diagnosis of heart failure36 but not mentioned in AF guidelines.32,37 Our results indicate that prolonged AF monitoring may be useful in patients with elevated BNP levels as it may reflect undetected AF. In stroke patients, the clinical consequence of elevated BNP levels is currently unknown. BNP is a predictor of future stroke28 and our analysis shows that patients with elevated BNP >100 pg/mL represent a group of patients in whom EPM is very effective. Our calculated AUC in patients with or without heart failure does not differ significantly, so that BNP with a cut off value of ≥100 pg/mL can be used to preselect stroke patients for EPM irrespective of a heart failure diagnosis.

The potential of BNPs to predict AF is also supported by a retrospective subgroup of the WARSS trial (Warfarin-Aspirin Recurrent Stroke Study), which showed that (unlike the entire cohort) a subgroup of stroke patients with elevated natriuretic peptide levels benefit from anticoagulation as compared to aspirin. Hence, in this subgroup with increased biomarker levels, the number of patients with undetected AF might have been substantially higher.38

Strengths and Limitations

The strengths of the present analysis of Find-AFRANDOMISED include the randomized, controlled, and prospective multicenter trial design, a large sample size, the real-life-scenario of patients with acute ischemic stroke included irrespective of the suspected stroke cause, the very intensive cardiac monitoring by means of three 10-day Holter-ECGs, the 2 time points of BNP sampling, and the high rate of BNP samples drawn at baseline (93.7%). The lack of generalizability to populations not included in the study—particularly patients younger than 60years of age or of ethnic groups—is a limitation. Previous observational data have shown that the number needed to screen increases with younger age.39,40

In this study, we only analyzed BNP values, but not other natriuretic peptides, because BNP showed best diagnostic characteristics in a head-to-head comparison to NT-proBNP and NT-proANP.20,22 However, we cannot exclude that other parameters (eg, mid-regional pro-atrial natriuretic peptide) may yield different results.


In summary, acute ischemic stroke patients ≥60 years of age with newly detected AF showed significantly elevated BNP levels compared to patients without AF. The subgroup with BNP levels ≥100 pg/mL measured 3 days after stroke greatly benefitted from prolonged heart rhythm monitoring in terms of pAF detection.


*Drs Gröschel and Wachter contributed equally.

The online-only Data Supplement is available with this article at

Correspondence to Katrin Wasser, MD, Department of Neurology, University Medicine Göttingen, 37099 Göttingen, Germany. Email


  • 1. Friberg L, Bergfeldt L. Atrial fibrillation prevalence revisited.J Intern Med. 2013; 274:461–468. doi: 10.1111/joim.12114CrossrefMedlineGoogle Scholar
  • 2. Wolf PA, Abbott RD, Kannel WB. Atrial fibrillation as an independent risk factor for stroke: the Framingham Study.Stroke. 1991; 22:983–988. doi: 10.1161/01.str.22.8.983LinkGoogle Scholar
  • 3. Hart RG, Pearce LA, Aguilar MI. Meta-analysis: antithrombotic therapy to prevent stroke in patients who have nonvalvular atrial fibrillation.Ann Intern Med. 2007; 146:857–867. doi: 10.7326/0003-4819-146-12-200706190-00007CrossrefMedlineGoogle Scholar
  • 4. Hart RG, Pearce LA, Rothbart RM, McAnulty JH, Asinger RW, Halperin JL. Stroke with intermittent atrial fibrillation: incidence and predictors during aspirin therapy. Stroke prevention in atrial fibrillation investigators.J Am Coll Cardiol. 2000; 35:183–187. doi: 10.1016/s0735-1097(99)00489-1CrossrefMedlineGoogle Scholar
  • 5. Hohnloser SH, Pajitnev D, Pogue J, Healey JS, Pfeffer MA, Yusuf S, et al; ACTIVE W Investigators. Incidence of stroke in paroxysmal versus sustained atrial fibrillation in patients taking oral anticoagulation or combined antiplatelet therapy: an ACTIVE W Substudy.J Am Coll Cardiol. 2007; 50:2156–2161. doi: 10.1016/j.jacc.2007.07.076CrossrefMedlineGoogle Scholar
  • 6. Glotzer TV, Daoud EG, Wyse DG, Singer DE, Ezekowitz MD, Hilker C, et al. The relationship between daily atrial tachyarrhythmia burden from implantable device diagnostics and stroke risk: the TRENDS study.Circ Arrhythm Electrophysiol. 2009; 2:474–480. doi: 10.1161/CIRCEP.109.849638LinkGoogle Scholar
  • 7. Vanassche T, Lauw MN, Eikelboom JW, Healey JS, Hart RG, Alings M, et al. Risk of ischaemic stroke according to pattern of atrial fibrillation: analysis of 6563 aspirin-treated patients in ACTIVE-A and AVERROES.Eur Heart J. 2015; 36:281–27a. doi: 10.1093/eurheartj/ehu307CrossrefMedlineGoogle Scholar
  • 8. Rabinstein AA. Prolonged cardiac monitoring for detection of paroxysmal atrial fibrillation after cerebral ischemia.Stroke. 2014; 45:1208–1214. doi: 10.1161/STROKEAHA.113.003389LinkGoogle Scholar
  • 9. Wachter R, Gröschel K, Gelbrich G, Hamann GF, Kermer P, Liman J, et al; Find-AF(randomised) Investigators and Coordinators. Holter-electrocardiogram-monitoring in patients with acute ischaemic stroke (Find-AFRANDOMISED): an open-label randomised controlled trial.Lancet Neurol. 2017; 16:282–290. doi: 10.1016/S1474-4422(17)30002-9CrossrefMedlineGoogle Scholar
  • 10. Grond M, Jauss M, Hamann G, Stark E, Veltkamp R, Nabavi D, et al. Improved detection of silent atrial fibrillation using 72-hour Holter ECG in patients with ischemic stroke: a prospective multicenter cohort study.Stroke. 2013; 44:3357–3364. doi: 10.1161/STROKEAHA.113.001884LinkGoogle Scholar
  • 11. Kamel H, Hegde M, Johnson DR, Gage BF, Johnston SC. Cost-effectiveness of outpatient cardiac monitoring to detect atrial fibrillation after ischemic stroke.Stroke. 2010; 41:1514–1520. doi: 10.1161/STROKEAHA.110.582437LinkGoogle Scholar
  • 12. Schnabel RB, Wild PS, Wilde S, Ojeda FM, Schulz A, Zeller T, et al. Multiple biomarkers and atrial fibrillation in the general population.PLoS One. 2014; 9:e112486. doi: 10.1371/journal.pone.0112486CrossrefMedlineGoogle Scholar
  • 13. Alonso A, Krijthe BP, Aspelund T, Stepas KA, Pencina MJ, Moser CB, et al. Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium.J Am Heart Assoc. 2013; 2:e000102. doi: 10.1161/JAHA.112.000102LinkGoogle Scholar
  • 14. Rodríguez-Yáñez M, Arias-Rivas S, Santamaría-Cadavid M, Sobrino T, Castillo J, Blanco M. High pro-BNP levels predict the occurrence of atrial fibrillation after cryptogenic stroke.Neurology. 2013; 81:444–447. doi: 10.1212/WNL.0b013e31829d8773CrossrefMedlineGoogle Scholar
  • 15. Nakagawa K, Yamaguchi T, Seida M, Yamada S, Imae S, Tanaka Y, et al. Plasma concentrations of brain natriuretic peptide in patients with acute ischemic stroke.Cerebrovasc Dis. 2005; 19:157–164. doi: 10.1159/000083249CrossrefMedlineGoogle Scholar
  • 16. Badran HM, Eid MA, Michael A. Doppler-derived indexes and B-type natriuretic peptide in prediction of paroxysmal atrial fibrillation in essential hypertension: a prospective study.Echocardiography. 2007; 24:911–922. doi: 10.1111/j.1540-8175.2007.00493.xGoogle Scholar
  • 17. Patton KK, Ellinor PT, Heckbert SR, Christenson RH, DeFilippi C, Gottdiener JS, et al. N-terminal pro-B-type natriuretic peptide is a major predictor of the development of atrial fibrillation: the Cardiovascular Health Study.Circulation. 2009; 120:1768–1774. doi: 10.1161/CIRCULATIONAHA.109.873265LinkGoogle Scholar
  • 18. Shibazaki K, Kimura K, Okada Y, Iguchi Y, Terasawa Y, Aoki J. Heart failure may be associated with the onset of ischemic stroke with atrial fibrillation: a brain natriuretic peptide study.J Neurol Sci. 2009; 281:55–57. doi: 10.1016/j.jns.2009.02.374CrossrefMedlineGoogle Scholar
  • 19. Kara K, Geisel MH, Möhlenkamp S, Lehmann N, Kälsch H, Bauer M, et al. B-type natriuretic peptide for incident atrial fibrillation-The Heinz Nixdorf Recall Study.J Cardiol. 2015; 65:453–458. doi: 10.1016/j.jjcc.2014.08.003CrossrefMedlineGoogle Scholar
  • 20. Seegers J, Zabel M, Grüter T, Ammermann A, Weber-Krüger M, Edelmann F, et al. Natriuretic peptides for the detection of paroxysmal atrial fibrillation.Open Heart. 2015; 2:e000182. doi: 10.1136/openhrt-2014-000182Google Scholar
  • 21. Sinner MF, Stepas KA, Moser CB, Krijthe BP, Aspelund T, Sotoodehnia N, et al. B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies.Europace. 2014; 16:1426–1433. doi: 10.1093/europace/euu175CrossrefMedlineGoogle Scholar
  • 22. Wachter R, Lahno R, Haase B, Weber-Krüger M, Seegers J, Edelmann F, et al. Natriuretic peptides for the detection of paroxysmal atrial fibrillation in patients with cerebral ischemia–the Find-AF study.PLoS One. 2012; 7:e34351. doi: 10.1371/journal.pone.0034351CrossrefMedlineGoogle Scholar
  • 23. Haeusler KG, Gröschel K, Köhrmann M, Anker SD, Brachmann J, Böhm M, et al. Expert opinion paper on atrial fibrillation detection after ischemic stroke.Clin Res Cardiol. 2018; 107:871–880. doi: 10.1007/s00392-018-1256-9CrossrefMedlineGoogle Scholar
  • 24. Morbach C, Buck T, Rost C, Peter S, Günther S, Störk S, et al; Handheld-BNP Research Network. Point-of-care B-type natriuretic peptide and portable echocardiography for assessment of patients with suspected heart failure in primary care: rationale and design of the three-part Handheld-BNP program and results of the training study.Clin Res Cardiol. 2018; 107:95–107. doi: 10.1007/s00392-017-1181-3Google Scholar
  • 25. Fujii S, Shibazaki K, Kimura K, Sakai K, Aoki J. A simple score for predicting paroxysmal atrial fibrillation in acute ischemic stroke.J Neurol Sci. 2013; 328:83–86. doi: 10.1016/j.jns.2013.02.025CrossrefMedlineGoogle Scholar
  • 26. Shibazaki K, Kimura K, Fujii S, Sakai K, Iguchi Y. Brain natriuretic peptide levels as a predictor for new atrial fibrillation during hospitalization in patients with acute ischemic stroke.Am J Cardiol. 2012; 109:1303–1307. doi: 10.1016/j.amjcard.2011.12.022CrossrefMedlineGoogle Scholar
  • 27. Okada Y, Shibazaki K, Kimura K, Iguchi Y, Miki T. Brain natriuretic peptide as a predictor of delayed atrial fibrillation after ischaemic stroke and transient ischaemic attack.Eur J Neurol. 2010; 17:326–331. doi: 10.1111/j.1468-1331.2009.02813.xGoogle Scholar
  • 28. Sakai K, Shibazaki K, Kimura K, Aoki J, Kobayashi K, Fujii S, et al. Brain natriuretic peptide as a predictor of cardioembolism in acute ischemic stroke patients: brain natriuretic peptide stroke prospective study.Eur Neurol. 2013; 69:246–251. doi: 10.1159/000342887CrossrefMedlineGoogle Scholar
  • 29. Holmes SJ, Espiner EA, Richards AM, Yandle TG, Frampton C. Renal, endocrine, and hemodynamic effects of human brain natriuretic peptide in normal man.J Clin Endocrinol Metab. 1993; 76:91–96. doi: 10.1210/jcem.76.1.8380606Google Scholar
  • 30. Seifi A, Carr K, Maltenfort M, Moussouttas M, Birnbaum L, Parra A, et al. The incidence and risk factors of associated acute myocardial infarction (AMI) in acute cerebral ischemic (ACI) events in the United States.PLoS One. 2014; 9:e105785. doi: 10.1371/journal.pone.0105785CrossrefMedlineGoogle Scholar
  • 31. Li J, Wang L. B-type natriuretic peptide levels in patients with paroxysmal lone atrial fibrillation.Heart Vessels. 2006; 21:137–140. doi: 10.1007/s00380-005-0884-yCrossrefMedlineGoogle Scholar
  • 32. Kirchhof P, Benussi S, Kotecha D, Ahlsson A, Atar D, Casadei B, et al; ESC Scientific Document Group. 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS.Eur Heart J. 2016; 37:2893–2962. doi: 10.1093/eurheartj/ehw210CrossrefMedlineGoogle Scholar
  • 33. Gladstone DJ, Spring M, Dorian P, Panzov V, Thorpe KE, Hall J, et al; EMBRACE Investigators and Coordinators. Atrial fibrillation in patients with cryptogenic stroke.N Engl J Med. 2014; 370:2467–2477. doi: 10.1056/NEJMoa1311376CrossrefMedlineGoogle Scholar
  • 34. Reiffel JA, Verma A, Kowey PR, Halperin JL, Gersh BJ, Wachter R, et al; REVEAL AF Investigators. Incidence of-previously undiagnosed atrial fibrillation using insertable cardiac monitors in a high-risk population: the REVEAL AF Study.JAMA Cardiol. 2017; 2:1120–1127. doi: 10.1001/jamacardio.2017.3180CrossrefMedlineGoogle Scholar
  • 35. Van Gelder IC, Healey JS, Crijns HJGM, Wang J, Hohnloser SH, Gold MR, et al. Duration of device-detected subclinical atrial fibrillation and occurrence of stroke in ASSERT.Eur Heart J. 2017; 38:1339–1344. doi: 10.1093/eurheartj/ehx042CrossrefMedlineGoogle Scholar
  • 36. Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JGF, Coats AJS, et al; ESC Scientific Document Group. 2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.Eur Heart J. 2016; 37:2129–2200. doi: 10.1093/eurheartj/ehw128CrossrefMedlineGoogle Scholar
  • 37. January CT, Wann LS, Calkins H, Chen LY, Cigarroa JE, Cleveland JC, et al. 2019 AHA/ACC/HRS focused update of the 2014 AHA/ACC/HRS guideline for the management of patients with atrial fibrillation: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines and the Heart Rhythm Society.J Am Coll Cardiol. 2019; 74:104–132. doi: 10.1016/j.jacc.2019.01.011CrossrefMedlineGoogle Scholar
  • 38. Longstreth WT, Kronmal RA, Thompson JL, Christenson RH, Levine SR, Gross R, et al. Amino terminal pro-B-type natriuretic peptide, secondary stroke prevention, and choice of antithrombotic therapy.Stroke. 2013; 44:714–719. doi: 10.1161/STROKEAHA.112.675942LinkGoogle Scholar
  • 39. Chugh SS, Havmoeller R, Narayanan K, Singh D, Rienstra M, Benjamin EJ, et al. Worldwide epidemiology of atrial fibrillation: a Global Burden of Disease 2010 Study.Circulation. 2014; 129:837–847. doi: 10.1161/CIRCULATIONAHA.113.005119LinkGoogle Scholar
  • 40. Wachter R, Weber-Krüger M, Seegers J, Edelmann F, Wohlfahrt J, Wasser K, et al. Age-dependent yield of screening for undetected atrial fibrillation in stroke patients: the Find-AF study.J Neurol. 2013; 260:2042–2045. doi: 10.1007/s00415-013-6935-xCrossrefMedlineGoogle Scholar


eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.

Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.