title: Complexity of Heart Rate Variability Can Predict Stroke-In-Evolution in Acute Ischemic Stroke Patients.
abstract: About one-third of acute stroke patients may experience stroke-in-evolution, which is often associated with a worse outcome. Recently, we showed that multiscale entropy (MSE), a non-linear method for analysis of heart rate variability (HRV), is an early outcome predictor in non-atrial fibrillation (non-AF) stroke patients. We aimed to further investigate MSE as a predictor of SIE. We included 90 non-AF ischemic stroke patients admitted to the intensive care unit (ICU). Nineteen (21.1%) patients met the criteria of SIE, which was defined as an increase in the National Institutes of Health Stroke Scale score of ≥2 points within 3 days of admission. The MSE of HRV was analyzed from 1-hour continuous ECG signals during the first 24 hours of admission. The complexity index was defined as the area under the MSE curve. Compared with patients without SIE, those with SIE had a significantly lower complexity index value (21.3 ± 8.5 vs 26.5 ± 7.7, P = 0.012). After adjustment for clinical variables, patients with higher complexity index values were significantly less likely to have SIE (odds ratio = 0.897, 95% confidence interval 0.818-0.983, P = 0.020). In summary, early assessment of HRV by MSE can be a potential predictor of SIE in ICU-admitted non-AF ischemic stroke patients.
authors.affiliation: Stroke Center and Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.|Division of Neurology, Department of Internal Medicine, Far-Eastern Memorial Hospital, New Taipei, Taiwan.|Graduate Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan.
authors.forename: Chih-Hao
authors.initials: CH
authors.lastname: Chen
authors.affiliation: Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan.|NTU-NTUH-MediaTek Innovative Medical Electronics Research Center, Taipei, Taiwan.
authors.forename: Pei-Wen
authors.initials: PW
authors.lastname: Huang
authors.affiliation: Stroke Center and Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.|NTU-NTUH-MediaTek Innovative Medical Electronics Research Center, Taipei, Taiwan.
authors.forename: Sung-Chun
authors.initials: SC
authors.lastname: Tang
authors.affiliation: Department of Mechanical Engineering and Innovation Center for Big Data and Digital Convergence, Yuan Ze University, Taoyuan, Taiwan.
authors.forename: Jiann-Shing
authors.initials: JS
authors.lastname: Shieh
authors.affiliation: NTU-NTUH-MediaTek Innovative Medical Electronics Research Center, Taipei, Taiwan.|Division of Neurosurgery, Department of Surgery, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Dar-Ming
authors.initials: DM
authors.lastname: Lai
authors.affiliation: Graduate Institute of Electronics Engineering, National Taiwan University, Taipei, Taiwan.|NTU-NTUH-MediaTek Innovative Medical Electronics Research Center, Taipei, Taiwan.
authors.forename: An-Yu
authors.initials: AY
authors.lastname: Wu
authors.affiliation: Stroke Center and Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
authors.forename: Jiann-Shing
authors.initials: JS
authors.lastname: Jeng
mesh_terms: D000208:Acute Disease; D000368:Aged; D000369:Aged, 80 and over; D002545:Brain Ischemia / Q000503:physiopathology*; D005260:Female; D006339:Heart Rate; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D020521:Stroke / Q000503:physiopathology*