[Amplitude-integrated electroencephalography monitoring results of hospitalized neonates in plateau areas]. / æŒ¯å¹ æ•´åˆè„‘ç”µå›¾åœ¨é«˜åŽŸåœ°åŒºä½é™¢æ–°ç”Ÿå„¿ä¸­çš„ç›‘æµ‹ç»“æžœåˆ†æž.

OBJECTIVES: To investigate the amplitude-integrated electroencephalography (aEEG) monitoring results of hospitalized neonates in plateau areas. METHODS: A retrospective analysis was conducted on 5 945 neonates who were admitted to the Department of Neonatology, Kunming Children's Hospital, and received aEEG monitoring from January 2020 to December 2022. According to the aEEG monitoring results, they were divided into a normal aEEG group and an abnormal aEEG group. The incidence rate of aEEG abnormalities was analyzed in neonates with various systemic diseases, as well as the manifestations of aEEG abnormalities and the consistency between aEEG abnormalities and clinical abnormalities. RESULTS: Among the 5 945 neonates, the aEEG abnormality rate was 19.28% (1 146/5 945), with an abnormality rate of 29.58% (906/3 063) in critically ill neonates and 8.33% (240/2 882) in non-critically ill neonates (P<0.05). The children with inherited metabolic diseases showed the highest aEEG abnormality rate of 60.77% (79/130), followed by those with central nervous system disorders [42.22% (76/180)] and preterm infants [35.53% (108/304)]. Compared with the normal aEEG group, the abnormal aEEG group had significantly lower age and gestational age, as well as a significantly lower birth weight of preterm infants (P<0.05). Among the 1 146 neonates with aEEG abnormalities, the main types of aEEG abnormalities were sleep cycle disorders in 597 neonates (52.09%), background activity abnormalities in 294 neonates (25.65%), and epileptiform activity in 255 neonates (22.25%), and there were 902 neonates (78.71%) with abnormal clinical manifestations. The sensitivity and specificity of aEEG monitoring for brain function abnormalities were 33.51% and 92.50%, respectively. CONCLUSIONS: In plateau areas, there is a relatively high rate of aEEG abnormalities among hospitalized neonates, particularly in critically ill neonates and those with smaller gestational ages and younger ages, suggesting a high risk of brain injury. Therefore, routine aEEG monitoring for the hospitalized neonates can help with the early detection of brain function abnormalities, the decision-making in treatment, and the formulation of brain protection strategies.

[Cerebral oxygen metabolism and brain electrical activity of healthy full-term neonates in high-altitude areas: a multicenter clinical research protocol]. / é«˜æµ·æ‹”åœ°åŒºå¥åº·è¶³æœˆæ–°ç”Ÿå„¿è„‘æ°§ä»£è°¢åŠè„‘ç”µæ´»åŠ¨å·®å¼‚çš„å¤šä¸­å¿ƒä¸´åºŠç ”ç©¶æ–¹æ¡ˆ.

Further evidence is needed to explore the impact of high-altitude environments on the neurologic function of neonates. Non-invasive techniques such as cerebral near-infrared spectroscopy and amplitude-integrated electroencephalography can provide data on cerebral oxygenation and brain electrical activity. This study will conduct multiple cerebral near-infrared spectroscopy and amplitude-integrated electroencephalography monitoring sessions at various time points within the first 3 days postpartum for healthy full-term neonates at different altitudes. The obtained data on cerebral oxygenation and brain electrical activity will be compared between different altitudes, and corresponding reference ranges will be established. The study involves 6 participating centers in the Chinese High Altitude Neonatal Medicine Alliance, with altitude gradients divided into 4 categories: 800 m, 1 900 m, 2 400 m, and 3 500 m, with an anticipated sample size of 170 neonates per altitude gradient. This multicenter prospective cohort study aims to provide evidence supporting the impact of high-altitude environments on early brain function and metabolism in neonates.

Evaluation of the clinical effect of an artificial intelligence-assisted diagnosis and treatment system for neonatal seizures in the real world: a multicenter clinical study protocol. / æ–°ç”Ÿå„¿æƒŠåŽ¥æ™ºèƒ½è¯Šç–—ç³»ç»ŸçœŸå®žåœºæ™¯ä¸´åºŠå®žæ–½æ•ˆæžœç»¼åˆè¯„ä»·çš„å¤šä¸­å¿ƒä¸´åºŠç ”ç©¶æ–¹æ¡ˆ.

Neonatal seizures are the most common clinical manifestations of critically ill neonates and often suggest serious diseases and complicated etiologies. The precise diagnosis of this disease can optimize the use of anti-seizure medication, reduce hospital costs, and improve the long-term neurodevelopmental outcomes. Currently, a few artificial intelligence-assisted diagnosis and treatment systems have been developed for neonatal seizures, but there is still a lack of high-level evidence for the diagnosis and treatment value in the real world. Based on an artificial intelligence-assisted diagnosis and treatment systems that has been developed for neonatal seizures, this study plans to recruit 370 neonates at a high risk of seizures from 6 neonatal intensive care units (NICUs) in China, in order to evaluate the effect of the system on the diagnosis, treatment, and prognosis of neonatal seizures in neonates with different gestational ages in the NICU. In this study, a diagnostic study protocol is used to evaluate the diagnostic value of the system, and a randomized parallel-controlled trial is designed to evaluate the effect of the system on the treatment and prognosis of neonates at a high risk of seizures. This multicenter prospective study will provide high-level evidence for the clinical application of artificial intelligence-assisted diagnosis and treatment systems for neonatal seizures in the real world.

[Association between interleukin-8 rs4073 polymorphisms and susceptibility to neonatal sepsis].

OBJECTIVE: To study the association between interleukin-8 (IL-8) rs4073 polymorphisms and susceptibility to sepsis in full-term neonates through a prospective study. METHODS: A total of 50 neonates who were diagnosed with sepsis based on positive blood culture from January to December 2017 were enrolled as the sepsis group. Fifty neonates who had clinical symptoms and negative blood culture were enrolled as the clinical sepsis group. Fifty neonates without infection were enrolled as the control group. Sequencing was used to detect the polymorphisms of IL-8 rs4073. The three groups were compared in terms of the frequencies of genotypes and alleles. A multivariate logistic regression analysis was used to investigate the association of IL-8 rs4073 genotypes with sepsis in full-term neonates. RESULTS: There were significant differences in the frequencies of genotypes and alleles at IL-8 rs4073 among the three groups (P<0.05). The logistic regression analysis showed that a low gestational age and TT genotype at IL-8 rs4073 were risk factors for the pathogenesis of sepsis in neonates (P<0.05). CONCLUSIONS: The full-term neonates with TT genotype at IL-8 rs4073 may be susceptible to sepsis.