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利用心率变异性预测早产儿的神经学结局:一项范围综述

Using heart rate variability to predict neurological outcomes in preterm infants: a scoping review.

作者信息

Smolkova Magdalena, Sekar Shivani, Kim Seh Hyun, Sunwoo John, El-Dib Mohamed

机构信息

School of Clinical Medicine, University of Cambridge, Cambridge, UK.

Division of Newborn Medicine, Department of Pediatrics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

Pediatr Res. 2024 Oct 5. doi: 10.1038/s41390-024-03606-5.

DOI:10.1038/s41390-024-03606-5
PMID:39369103
Abstract

Infants born preterm are at higher risk of neurological complications, including intraventricular haemorrhage and white matter injury. After discharge, these infants may experience adverse neurodevelopmental outcomes and exhibit lower educational attainment. Early detection of brain injury and accurate prediction of neurodevelopmental impairment would allow early intervention and support. Heart rate variability (HRV) describes the variation of time intervals between each subsequent heartbeat. HRV is controlled by the autonomic nervous system, which may be affected by hypoxia and compromised blood flow. While HRV has primarily been investigated in neonatal sepsis, the association between HRV, brain injury and neurodevelopmental outcomes in preterm infants is less established. The present scoping review examines the utility of HRV monitoring for predicting short-term and long-term neurological outcomes in preterm infants. Following systematic search of Medline, Embase, Web of Science and the Cochrane Library, 15 studies were included. Nine studies examined the relationship between HRV and brain injury, with all but two showed an association. Eight studies examined the relationship between HRV and long-term outcomes and all eight found an association. This scoping review suggests that decreased HRV in the neonatal period is associated with short- and long-term neurodevelopmental outcomes in preterm infants. IMPACT: Changes in heart rate variability correlate with the occurrence of intraventricular haemorrhage in preterm infants. A decrease in heart rate variability may precede the development of intraventricular haemorrhage. Alterations in heart rate variability correlate with long-term neurodevelopmental outcomes. Significant variability exists in metrics used in assessing heart rate variability.

摘要

早产出生的婴儿出现神经并发症的风险更高,包括脑室内出血和白质损伤。出院后,这些婴儿可能会出现不良的神经发育结果,并表现出较低的教育成就。早期发现脑损伤并准确预测神经发育障碍将有助于早期干预和支持。心率变异性(HRV)描述了连续心跳之间时间间隔的变化。HRV受自主神经系统控制,自主神经系统可能受到缺氧和血流受损的影响。虽然HRV主要在新生儿败血症中进行了研究,但HRV与早产儿脑损伤和神经发育结果之间的关联尚不太明确。本综述探讨了HRV监测对预测早产儿短期和长期神经学结果的效用。在对Medline、Embase、科学网和考克兰图书馆进行系统检索后,纳入了15项研究。9项研究探讨了HRV与脑损伤之间的关系,除两项研究外,所有研究均显示存在关联。8项研究探讨了HRV与长期结果之间的关系,所有8项研究均发现存在关联。本综述表明,新生儿期HRV降低与早产儿短期和长期神经发育结果相关。影响:心率变异性的变化与早产儿脑室内出血的发生相关。心率变异性降低可能在脑室内出血发生之前出现。心率变异性的改变与长期神经发育结果相关。在评估心率变异性时使用的指标存在显著差异。

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Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity.使用具有局部连通性的多模态结构脑磁共振成像预测早产儿的2年神经发育结局。
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Long-term association of ultra-short heart rate variability with cardiovascular events.超短心率变异性与心血管事件的长期关联。
Sci Rep. 2023 Nov 3;13(1):18966. doi: 10.1038/s41598-023-45988-2.
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Defining the Neurologic Consequences of Preterm Birth.
生物噪声及其应用之间的关系:理解系统故障并基于受限无序原理提出一种增强功能的方法。
Biology (Basel). 2025 Mar 27;14(4):349. doi: 10.3390/biology14040349.
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N Engl J Med. 2023 Aug 3;389(5):441-453. doi: 10.1056/NEJMra2303347.
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Neurodevelopmental Correlates of Brain Magnetic Resonance Imaging Abnormalities in Extremely Low-birth-weight Infants.极低出生体重儿脑磁共振成像异常的神经发育相关性研究。
J Pediatr. 2023 Nov;262:113646. doi: 10.1016/j.jpeds.2023.113646. Epub 2023 Jul 28.
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A simple scoring system for prediction of IVH in very-low-birth-weight infants.一个用于预测极低出生体重儿 IVH 的简单评分系统。
Pediatr Res. 2023 Dec;94(6):2033-2039. doi: 10.1038/s41390-023-02744-6. Epub 2023 Jul 21.
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Why, when and how to assess autonomic nervous system maturation in neonatal care units: A practical overview.新生儿重症监护病房中自主神经系统成熟度评估的时机、原因及方法:实用概述
Neurophysiol Clin. 2023 Apr;53(2):102855. doi: 10.1016/j.neucli.2023.102855. Epub 2023 Mar 23.
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Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information.使用包含脑功能信息的多模态预后模型预测极早产儿的神经发育结局。
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