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Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy
by
Hong, Daojun
, Huang, Jingwei
, Lin, Jing
, Lin, Yuyang
, Liao, Xuwei
, Fang, Pu
, Ouyang, Xiaoqing
, Su, Yingwen
, Yang, Shanglin
, Xiao, Zhihua
, Liu, Yi
, Zhou, Hongbin
, Huang, Qin
, Chen, Yunqing
, Xu, Zubing
in
Blood pressure
/ Care and treatment
/ Complications and side effects
/ Electrocardiography
/ Entropy
/ Fractals
/ Genetic transformation
/ Health aspects
/ Heart beat
/ Heart rate
/ Heart rate variability
/ Hemorrhage
/ Hemorrhagic transformation
/ Ischemia
/ Linear parameters
/ Measurement
/ Mechanical thrombectomy
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Medicine, Experimental
/ Mortality
/ Nervous system
/ Neurochemistry
/ Neurology
/ Neurosurgery
/ Neutrophils
/ Nonlinear parameters
/ Prevention
/ Risk factors
/ Stroke
/ Stroke (Disease)
/ Thrombocythemia
/ Thrombocytosis
/ Thrombolytic drugs
/ Time series
/ Tomography
2026
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Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy
by
Hong, Daojun
, Huang, Jingwei
, Lin, Jing
, Lin, Yuyang
, Liao, Xuwei
, Fang, Pu
, Ouyang, Xiaoqing
, Su, Yingwen
, Yang, Shanglin
, Xiao, Zhihua
, Liu, Yi
, Zhou, Hongbin
, Huang, Qin
, Chen, Yunqing
, Xu, Zubing
in
Blood pressure
/ Care and treatment
/ Complications and side effects
/ Electrocardiography
/ Entropy
/ Fractals
/ Genetic transformation
/ Health aspects
/ Heart beat
/ Heart rate
/ Heart rate variability
/ Hemorrhage
/ Hemorrhagic transformation
/ Ischemia
/ Linear parameters
/ Measurement
/ Mechanical thrombectomy
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Medicine, Experimental
/ Mortality
/ Nervous system
/ Neurochemistry
/ Neurology
/ Neurosurgery
/ Neutrophils
/ Nonlinear parameters
/ Prevention
/ Risk factors
/ Stroke
/ Stroke (Disease)
/ Thrombocythemia
/ Thrombocytosis
/ Thrombolytic drugs
/ Time series
/ Tomography
2026
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Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy
by
Hong, Daojun
, Huang, Jingwei
, Lin, Jing
, Lin, Yuyang
, Liao, Xuwei
, Fang, Pu
, Ouyang, Xiaoqing
, Su, Yingwen
, Yang, Shanglin
, Xiao, Zhihua
, Liu, Yi
, Zhou, Hongbin
, Huang, Qin
, Chen, Yunqing
, Xu, Zubing
in
Blood pressure
/ Care and treatment
/ Complications and side effects
/ Electrocardiography
/ Entropy
/ Fractals
/ Genetic transformation
/ Health aspects
/ Heart beat
/ Heart rate
/ Heart rate variability
/ Hemorrhage
/ Hemorrhagic transformation
/ Ischemia
/ Linear parameters
/ Measurement
/ Mechanical thrombectomy
/ Medical research
/ Medicine
/ Medicine & Public Health
/ Medicine, Experimental
/ Mortality
/ Nervous system
/ Neurochemistry
/ Neurology
/ Neurosurgery
/ Neutrophils
/ Nonlinear parameters
/ Prevention
/ Risk factors
/ Stroke
/ Stroke (Disease)
/ Thrombocythemia
/ Thrombocytosis
/ Thrombolytic drugs
/ Time series
/ Tomography
2026
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Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy
Journal Article
Multiparameters of heart rate variability predict symptomatic hemorrhagic transformation in patients following mechanical thrombectomy
2026
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Overview
Background
Hemorrhagic transformation (HT), especially symptomatic HT (sHT), seriously affects the functional prognosis in patients following mechanical thrombectomy (MT). The present study aimed to investigate the association of HT with heart rate variability (HRV) using multiple parameters in patients undergoing MT.
Methods
Between November 2019 and April 2024, we enrolled eligible patients according to the inclusion criteria and exclusion criteria. Linear parameters and nonlinear approaches reflecting HRV were calculated and analyzed.
Results
A total of 254 patients were included in the analysis, including 56 patients with HT and 198 patients without, and 24 patients with sHT and 230 patients without. Nonlinear approaches including SD1/SD2 ratio, Higuchi fractal dimension (HFD), large-scale multiscale entropy index (MSE
LS
), multiscale entropy area under the curve (MSE
AUC
), large-scale composite multiscale entropy index (CMSE
LS
), and composite multiscale entropy area under the curve (CMSE
AUC
) were showed to be independently associated with sHT (p < 0.05). Meanwhile, receiver operating characteristic curves suggested that CMSE
LS
was a better indicator to predict sHT than other HRV parameters, with the area under the curve of 0.708 (95%CI 0.581–0.835).
Conclusions
Nonlinear parameters of HRV including SD1/SD2 ratio, HFD, MSE
LS
, MSE
AUC
, CMSE
LS
, and CMSE
AUC
provide an independent indicator for predicting sHT in patients following MT.
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