一种新的早产儿脑电发育成熟度评价方法的初步研究

doi:10.7499/j.issn.1008-8830.2303144

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摘要目的基于早产儿脑电活动特征建立一种新的早产儿脑电成熟度评价方法。方法前瞻性收集经后龄（postmenstrual age，PMA）25~36周符合纳入标准的早产儿生后7 d内视频脑电图和同步振幅整合脑电图（amplitude-integrated electroencephalography，aEEG）的监测资料。将aEEG与常规脑电图（conventional electroencephalography，cEEG）背景活动指标（aEEG+cEEG）按发育成熟规律赋分作为新的评价体系，并与单一aEEG评价方法比较，分析二者与胎龄（gestational age，GA）、PMA、头围的相关性。计算不同PMA早产儿aEEG+cEEG总分和aEEG总分的分值区间，比较组间差异。在不同评价者之间对新评分体系进行一致性分析。结果共纳入52例早产儿。aEEG+cEEG总分、aEEG总分分别与GA、PMA、头围呈显著正相关（均P<0.05），与PMA和GA的相关系数均>0.9。aEEG+cEEG评价方法和单一aEEG评价方法在不同PMA早产儿中正常分值区间分别为：<28周组为13.0（11.0，14.0）、6.0（4.0，7.0）分，28~29⁺⁶周组为16.0（14.5，17.0）、8.0（6.0，8.0）分，30~31⁺⁶周组为18.0（17.0，21.0）、9.0（8.0，10.0）分，32~33⁺⁶周组为22.0（20.0，24.5）、10.0（10.0，10.8）分，34~36周组为26.0（24.5，27.5）、11.0（10.0，12.0）分。不同PMA早产儿组间aEEG+cEEG总分和aEEG总分差异有统计学意义（P<0.05）。不同评价者之间应用该评分体系进行早产儿成熟度评价时一致性高（κ=0.86）。结论该研究所建立的脑电评分体系可以定量反映早产儿脑电发育的成熟度，不同PMA组间有很好的区分度，在不同评价者之间应用一致性高。

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	田艺丽
	方秀英
	王英杰
	毛健

关键词 ：脑发育成熟度, 常规脑电图, 振幅整合脑电图, 早产儿

Abstract：Objective To establish a new method for evaluating the brain maturation of preterm infants based on the features of electroencephalographic activity. Methods A prospective study was conducted on the video electroencephalography (vEEG) and amplitude-integrated electroencephalography (aEEG) recordings within 7 days after birth of preterm infants who had a postmenstrual age (PMA) of 25-36 weeks and met the inclusion criteria. The background activity of aEEG+conventional electroencephalography (cEEG) was scored according to the features of brain maturation as a new evaluation system and was compared with the aEEG evaluation system. The correlations of the evaluation results of the two methods with gestational age (GA), PMA, and head circumference were evaluated. The intervals of the total scores of aEEG+cEEG and aEEG were calculated for preterm infants with different PMAs and were compared between groups. The consistency of the new scoring system was evaluated among different raters. Results A total of 52 preterm infants were included. The total scores of aEEG+cEEG and aEEG were positively correlated with GA, PMA, and head circumference (P<0.05), and the correlation coefficient between the total scores of the two systems and PMA and GA was >0.9. The normal score intervals for aEEG+cEEG and aEEG scoring systems were determined in preterm infants with different PMAs as follows: infants with a PMA of less than 28 weeks had scores of 13.0 (11.0, 14.0) points for aEEG+cEEG and 6.0 (4.0, 7.0) points for aEEG; infants with a PMA between 28 and 29+6 weeks had scores of 16.0 (14.5, 17.0) points for aEEG+cEEG and 8.0 (6.0, 8.0) points for aEEG; infants with a PMA between 30 and 31+6 weeks had scores of 18.0 (17.0, 21.0) points for aEEG+cEEG and 9.0 (8.0, 10.0) points for aEEG; infants with between 32 and 33+6 weeks had scores of 22.0 (20.0, 24.5) points for aEEG+cEEG and 10.0 (10.0, 10.8) points for aEEG; infants with a PMA between 34 and 36 weeks had scores of 26.0 (24.5, 27.5) points for aEEG+cEEG and 11.0 (10.0, 12.0) points for aEEG. There were significant differences in the total scores of aEEG+cEEG and aEEG among the different PMA groups (P<0.05). There was a high consistency between different raters when using the scoring system to evaluate the brain maturation of preterm infants (κ=0.86). Conclusions The aEEG+cEEG scoring system established in this study can quantitatively reflect the brain maturation of preterm infants, with a good discriminatory ability between preterm infants with different PMAs and high consistency between different raters.

Key words： Brain maturation Conventional electroencephalography Amplitude-integrated electroencephalography Preterm infant

收稿日期: 2023-03-29

通讯作者: 毛健，男，主任医师。Email：maoj@sj-hospital.org。 E-mail: maoj@sj-hospital.org

作者简介: 田艺丽，女，硕士，医师；

引用本文:

田艺丽,方秀英,王英杰等. 一种新的早产儿脑电发育成熟度评价方法的初步研究[J]. 中国当代儿科杂志, 2023, 25(8): 805-811.

TIAN Yi-Li,FANG Xiu-Ying,WANG Ying-Jie et al. A preliminary study on a new method for evaluating brain maturation in preterm infants[J]. CJCP, 2023, 25(8): 805-811.

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	Watanabe K, Hayakawa F, Okumura A. Neonatal EEG: a powerful tool in the assessment of brain damage in preterm infants[J]. Brain Dev, 1999, 21(6): 361-372. PMID: 10487468. DOI: 10.1016/s0387-7604(99)00034-0.
	Pavlidis E, Lloyd RO, Boylan GB. EEG: a valuable biomarker of brain injury in preterm infants[J]. Dev Neurosci, 2017, 39(1-4): 23-35. PMID: 28402972. DOI: 10.1159/000456659.
	Hayakawa F, Okumura A, Kato T, et al. Dysmature EEG pattern in EEGs of preterm infants with cognitive impairment: maturation arrest caused by prolonged mild CNS depression[J]. Brain Dev, 1997, 19(2): 122-125. PMID: 9105658. DOI: 10.1016/s0387-7604(96)00491-3.
	Lloyd RO, O'Toole JM, Livingstone V, et al. Can EEG accurately predict 2-year neurodevelopmental outcome for preterm infants?[J]. Arch Dis Child Fetal Neonatal Ed, 2021, 106(5): 535-541. PMID: 33875522. PMCID: PMC8394766. DOI: 10.1136/archdischild-2020-319825.
	Le Bihannic A, Beauvais K, Busnel A, et al. Prognostic value of EEG in very premature newborns[J]. Arch Dis Child Fetal Neonatal Ed, 2012, 97(2): F106-F109. PMID: 21659622. DOI: 10.1136/adc.2010.204735.
	Shellhaas RA, Chang T, Tsuchida T, et al. The American Clinical Neurophysiology Society's guideline on continuous electroencephalography monitoring in neonates[J]. J Clin Neurophysiol, 2011, 28(6): 611-617. PMID: 22146359. DOI: 10.1097/WNP.0b013e31823e96d7.
	Wallois F, Routier L, Heberlé C, et al. Back to basics: the neuronal substrates and mechanisms that underlie the electroencephalogram in premature neonates[J]. Neurophysiol Clin, 2021, 51(1): 5-33. PMID: 33162287. DOI: 10.1016/j.neucli.2020.10.006.
	Burdjalov VF, Baumgart S, Spitzer AR. Cerebral function monitoring: a new scoring system for the evaluation of brain maturation in neonates[J]. Pediatrics, 2003, 112(4): 855-861. PMID: 14523177. DOI: 10.1542/peds.112.4.855.
	Kato T, Okumura A, Hayakawa F, et al. Evaluation of brain maturation in pre-term infants using conventional and amplitude-integrated electroencephalograms[J]. Clin Neurophysiol, 2011, 122(10): 1967-1972. PMID: 21511528. DOI: 10.1016/j.clinph.2010.12.063.
	Massey SL, Shou H, Clancy R, et al. Interrater and intrarater agreement in neonatal electroencephalogram background scoring[J]. J Clin Neurophysiol, 2019, 36(1): 1-8. PMID: 30383719. PMCID: PMC6322680. DOI: 10.1097/WNP.0000000000000534.
	Stevenson NJ, Oberdorfer L, Koolen N, et al. Functional maturation in preterm infants measured by serial recording of cortical activity[J]. Sci Rep, 2017, 7(1): 12969. PMID: 29021546. PMCID: PMC5636845. DOI: 10.1038/s41598-017-13537-3.
	Stevenson NJ, Oberdorfer L, Tataranno ML, et al. Automated cot-side tracking of functional brain age in preterm infants[J]. Ann Clin Transl Neurol, 2020, 7(6): 891-902. PMID: 32368863. PMCID: PMC7318094. DOI: 10.1002/acn3.51043.
	Guyer C, Werner H, Wehrle F, et al. Brain maturation in the first 3 months of life, measured by electroencephalogram: a comparison between preterm and term-born infants[J]. Clin Neurophysiol, 2019, 130(10): 1859-1868. PMID: 31401493. DOI: 10.1016/j.clinph.2019.06.230.
	Tsuchida TN, Wusthoff CJ, Shellhaas RA, et al. American Clinical Neurophysiology Society standardized EEG terminology and categorization for the description of continuous EEG monitoring in neonates: report of the American Clinical Neurophysiology Society critical care monitoring committee[J]. J Clin Neurophysiol, 2013, 30(2): 161-173. PMID: 23545767. DOI: 10.1097/WNP.0b013e3182872b24.
	André M, Lamblin MD, d'Allest AM, et al. Electroencephalography in premature and full-term infants. Developmental features and glossary[J]. Neurophysiol Clin, 2010, 40(2): 59-124. PMID: 20510792. DOI: 10.1016/j.neucli.2010.02.002.
	Vesoulis ZA, Paul RA, Mitchell TJ, et al. Normative amplitude-integrated EEG measures in preterm infants[J]. J Perinatol, 2015, 35(6): 428-433. PMID: 25521561. PMCID: PMC4447544. DOI: 10.1038/jp.2014.225.
	Pavlidis E, Lloyd RO, Livingstone V, et al. A standardised assessment scheme for conventional EEG in preterm infants[J]. Clin Neurophysiol, 2020, 131(1): 199-204. PMID: 31812080. DOI: 10.1016/j.clinph.2019.09.028.
	Bourel-Ponchel E, Gueden S, Hasaerts D, et al. Normal EEG during the neonatal period: maturational aspects from premature to full-term newborns[J]. Neurophysiol Clin, 2021, 51(1): 61-88. PMID: 33239230. DOI: 10.1016/j.neucli.2020.10.004.
	Pavlidis E, Lloyd RO, Mathieson S, et al. A review of important electroencephalogram features for the assessment of brain maturation in premature infants[J]. Acta Paediatr, 2017, 106(9): 1394-1408. PMID: 28627083. DOI: 10.1111/apa.13956.
	Vecchierini MF, André M, d'Allest AM. Normal EEG of premature infants born between 24 and 30 weeks gestational age: terminology, definitions and maturation aspects[J]. Neurophysiol Clin, 2007, 37(5): 311-323. PMID: 18063233. DOI: 10.1016/j.neucli.2007.10.008.
	Whitehead K, Pressler R, Fabrizi L. Characteristics and clinical significance of delta brushes in the EEG of premature infants[J]. Clin Neurophysiol Pract, 2016, 2: 12-18. PMID: 30214965. PMCID: PMC6123866. DOI: 10.1016/j.cnp.2016.11.002.
	Maeda T, Kidokoro H, Tachibana T, et al. Trajectory of the incidence of brushes on preterm electroencephalogram and its association with neurodevelopment in extremely low birth weight infants[J]. Brain Dev, 2021, 43(10): 979-987. PMID: 34334244. DOI: 10.1016/j.braindev.2021.07.003.