Dataset Information

Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation.

ABSTRACT: Atrial fibrillation (AF) is a significant risk factor for ischemic strokes, and making a robust risk stratification scheme would be important. Few studies have examined whether nonlinear dynamics of the heart rate could predict ischemic strokes in AF. We examined whether a novel complexity measurement of the heart rate variability called multiscale entropy (MSE) was a useful risk stratification measure of ischemic strokes in patients with permanent AF.We examined 173 consecutive patients (age 69 ± 11 years) with permanent AF who underwent 24-hour Holter electrocardiography from April 2005 to December 2006. We assessed several frequency ranges of the MSE and CHA2DS2-VASc score (1 point for congestive heart failure, hypertension, diabetes, vascular disease, an age 65 to 74 years, and a female sex and 2 points for an age ? 75 years and a stroke or transient ischemic attack). We found 22 (13%) incident ischemic strokes during a mean follow up of 3.8-years. The average value of the MSE in the very-low frequency subrange (90-300 s, MeanEnVLF2) was significantly higher in patients who developed ischemic strokes than in those who did not (0.68 ± 0.15 vs. 0.60±0.14, P<0.01). There was no significant difference in the C-statistic between the CHA2DS2-VASc score and MeanEnVLF2 (0.56; 95% confidence interval, 0.43-0.69 vs. 0.66; 95% confidence interval, 0.53-0.79). After an adjustment for the age, CHA2DS2-VASc score, and antithrombotic agent, a Cox hazard regression model revealed that the MeanEnVLF2 was an independent predictor of an ischemic stroke (hazard ratio per 1-SD increment, 1.80; 95% confidence interval, 1.17-2.07, P<0.01).The MeanEnVLF2 in 24-hour Holter electrocardiography is a useful risk stratification measure of ischemic strokes during the long-term follow-up in patients with permanent AF.

SUBMITTER: Watanabe E

PROVIDER: S-EPMC4556684 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Publications

Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation.

Watanabe Eiichi E Kiyono Ken K Hayano Junichiro J Yamamoto Yoshiharu Y Inamasu Joji J Yamamoto Mayumi M Ichikawa Tomohide T Sobue Yoshihiro Y Harada Masehide M Ozaki Yukio Y

PloS one 20150901 9

<h4>Background</h4>Atrial fibrillation (AF) is a significant risk factor for ischemic strokes, and making a robust risk stratification scheme would be important. Few studies have examined whether nonlinear dynamics of the heart rate could predict ischemic strokes in AF. We examined whether a novel complexity measurement of the heart rate variability called multiscale entropy (MSE) was a useful risk stratification measure of ischemic strokes in patients with permanent AF.<h4>Methods and results</ ...[more]

PMID: 26325058

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Project description:BackgroundThere is currently no validated risk prediction model for recurrent events among patients with acute ischemic stroke (AIS) and atrial fibrillation (AF). Considering that the application of conventional risk scores has contextual limitations, new strategies are needed to develop such a model. Here, we set out to develop and validate a comprehensive risk prediction model for stroke recurrence in AIS patients with AF.MethodsAIS patients with AF were collected from multicenter registries in South Korea and Japan. A developmental dataset was constructed with 5648 registered cases from both countries for the period 2011‒2014. An external validation dataset was also created, consisting of Korean AIS subjects with AF registered between 2015 and 2018. Event outcomes were collected during 1 year after the index stroke. A multivariable prediction model was developed using the Fine-Gray subdistribution hazard model with non-stroke mortality as a competing risk. The model incorporated 21 clinical variables and was further validated, calibrated, and revised using the external validation dataset.ResultsThe developmental dataset consisted of 4483 Korean and 1165 Japanese patients (mean age, 74.3 ± 10.2 years; male 53%); 338 patients (6%) had recurrent stroke and 903 (16%) died. The clinical profiles of the external validation set (n = 3668) were comparable to those of the developmental dataset. The c-statistics of the final model was 0.68 (95% confidence interval, 0.66 ‒0.71). The developed prediction model did not show better discriminative ability for predicting stroke recurrence than the conventional risk prediction tools (CHADS2, CHA2DS2-VASc, and ATRIA).ConclusionsNeither conventional risk stratification tools nor our newly developed comprehensive prediction model using available clinical factors seemed to be suitable for identifying patients at high risk of recurrent ischemic stroke among AIS patients with AF in this modern direct oral anticoagulant era. Detailed individual information, including imaging, may be warranted to build a more robust and precise risk prediction model for stroke survivors with AF.

Dataset Information

Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation.

Publications

Multiscale Entropy of the Heart Rate Variability for the Prediction of an Ischemic Stroke in Patients with Permanent Atrial Fibrillation.

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