Correlation Analysis Between Brain Injury And Total Maturational Scores And Neurodevelopmental Outcome In Premature Infants

BackgroundPreterm infants because of their brain development is not yet mature,may affected by extrauterine adverse factors,prone to brain injury and the neurodevelopment impairment(NDI),result in neurological sequelae such as legacy of cerebral palsy shape[1-2].Early detection of NDI and neurological intervention can reduce the occurrence of complications,improve the quality of the survival of the premature infants[3-4].This project aims to study the total maturational scores(TMS)and brain injury of premature infants,and to explore the influence of TMS and brain injury on the neurodevelopment in premature infants.Methods2.1 Patient selectionA retrospective analysis,all premature infants admitted to our hospital from May 2013 to November 2017 were analyzed.They were grouped according to neurodevelopmental results.2.2 Clinical dataThe clinical data including gender,date of birth,gestational age(GA),birth weight(BW),postmenstrual age(PMA)at examination,the results of CDCC score,electroencephalogram,and visual/auditory evoked potentials at corrected 5～7 months.2.3 Magnetic resonance image(MRI)dates2.3.1 TMS score:random Numbers were given to all MRI datas,remove all information outside the image.TMS were scoring by two radiologists referred to Chlids mefthod[5],and the mean value of the two was taken.2.3.2 Classification of brain injury:Periventricular intraventricular hemorrhages(IVH),white matter injury(WMI),cystic-periventricular leukomalacia(c-PVL),secondary ventricular expansion of imaging diagnosis reference related literature at home and abroad[6-10].The occurrence of moderate-to-severe WMI or c-PVL,grade Ⅲ～Ⅳ of IVH and one or more cases of secondary ventricular dilatation were defined as moderate-to-severe brain injury[11].2.4 Statistical analysis SPSS 19.0 was used for statistical analysis,and P<0.05 was considered statistically significant.2.4.1 The chi-square test was used to analyze whether there were differences between in the general situation,brain injury,the TMS delay,and the neurodevelopment impairment2.4.2 T test was used to analyze whether the TMS of premature infants were different from their neurological development2.4.3 Clinical high risk factors of neurodevelopment impairment were analyzed using Logistics regression analysis.2.4.4 Linear discriminant analysis(LDA)was used to predict the presence of neurodevelopmental impairment in children without/mild brain injury,and to make a diagnostic evaluation.Result3.1 The incidence of NDI in premature infants with gestational age<32 weeks,birth weight<1.5kg and TMS delay was significantly increased.3.2 The incidence of various types of NDI in premature infants with moderate to severe brain injury,such as grade Ⅲ～Ⅳ of IVH,moderate to severe WMI or c-PVL,secondary ventricular dilatation,was significantly increased.But there was no significant difference in the incidence of NDI in premature infants with mild brain injury compare with premature infants without any brain injury in MRI.3.3 TMS delay(OR=4.858),gestational age<32 weeks(OR=2.971),brain injury(OR=3.118)were risk factors for NDI in premature infants;TMS scores were behind(OR=3.237),brain injury(OR=2.725)is a high-risk factor for mental retardation;brain injury is an independent risk factor for motor development retardation(OR=2.840)in premature infants;TMS delay is backward(OR=2.832)for epilepsy and visual/hearing impairment in premature infants Independent risk factors.3.4 The sensitivity of TMS-based LDA classification to predict the presence or absence of mild brain injury in premature infants with neurological development disorder is higher than that of mild brain injury(60.0%vs 34.0%),and the specificity difference is not significant.The sensitivity of LDA classification to predict the presence or absence of NDI is higher than that of brain injury(76.7%vs 67.6%).ConclusionModerate to severe brain injury and TMS delay may lead to NDI in premature infants.The combination of moderate to severe brain injury and TMS-based LDA classification can improve the sensitivity of early prediction of NDI.