AbstractObjectiveTo determine the efficacy and the prognostic value of amplitude‐integrated electroencephalography (aEEG) in term and near‐term neonates with high risk of neurological sequelae.MethodsInfants of ≥35 weeks of gestation diagnosed with neonatal encephalopathy or with high risk of brain injury were included. All eligible infants underwent aEEG within 6 h after clinical assessment. The infants were followed up 12 months to evaluate neurological development.ResultsA total of 250 infants were eligible, of which 85 had normal aEEG, 81 had mildly abnormal aEEG, and 84 had severely abnormal aEEG. Of these infants, 168 were diagnosed with different neonatal encephalopathies, 27 with congenital or metabolic diseases, and 55 with high risk of brain injury. In all, 22 infants died, 19 were lost to follow‐up, and 209 completed the follow‐up at 12 months, of which 62 were diagnosed with a neurological disability. Statistical analysis showed that severely abnormal aEEG predicted adverse neurological outcome with a sensitivity of 70.2%, a specificity of 87.1%, a positive predictive value of 75.6%, and a negative predictive value of 83.7%.InterpretationaEEG can predict adverse outcomes in high‐risk neonates and is a useful method for monitoring neonates with high risk of adverse neurological outcomes.

Phenylketonuria (PKU) is a common genetic metabolic disorder that affects the infant's nerve development and manifests as abnormal behavior and developmental delay as the child grows. Currently, a triple-quadrupole mass spectrometer (TQ-MS) is a common high-accuracy clinical PKU screening method. However, there is high false-positive rate associated with this modality, and its reduction can provide a diagnostic and economic benefit to both pediatric patients and health providers. Machine learning methods have the advantage of utilizing high-dimensional and complex features, which can be obtained from the patient's metabolic patterns and interrogated for clinically relevant knowledge. In this study, using TQ-MS screening data of more than 600,000 patients collected at the Newborn Screening Center of Shanghai Children's Hospital, we derived a dataset containing 256 PKU-suspected cases. We then developed a machine learning logistic regression analysis model with the aim to minimize false-positive rates in the results of the initial PKU test. The model attained a 95-100% sensitivity, the specificity was improved 53.14%, and positive predictive value increased from 19.14 to 32.16%. Our study shows that machine learning models may be used as a pediatric diagnosis aid tool to reduce the number of suspected cases and to help eliminate patient recall. Our study can serve as a future reference for the selection and evaluation of computational screening methods.

Background: Globally, the proportion of child deaths that occur in the neonatal period remains a high level of 37–41%. Differences of cause in neonate death exist in different regions as well as in different economic development countries. The specific aim of this study was to investigate the causes, characteristics, and differences of death in neonates during hospitalization in the tertiary Neonatal Intensive Care Unit (NICU) of China. Methods: All the dead neonates admitted to 26 NICUs were included between January l, 2011, and December 31, 2011. All the data were collected retrospectively from clinical records by a designed questionnaire. Data collected from each NICU were delivered to the leading institution where the results were analyzed. Results: A total of 744 newborns died during the 1-year survey, accounting for 1.2% of all the neonates admitted to 26 NICUs and 37.6% of all the deaths in children under 5 years of age in these hospitals. Preterm neonate death accounted for 59.3% of all the death. The leading causes of death in preterm and term infants were pulmonary disease and infection, respectively. In early neonate period, pulmonary diseases (56.5%) occupied the largest proportion of preterm deaths while infection (27%) and neurologic diseases (22%) were the two main causes of term deaths. In late neonate period, infection was the leading cause of both preterm and term neonate deaths. About two-thirds of neonate death occurred after medical care withdrawal. Of the cases who might survive if receiving continuing treatment, parents' concern about the long-term outcomes was the main reason of medical care withdrawal. Conclusions: Neonate death still accounts for a high proportion of all the deaths in children under 5 years of age. Our study showed the majority of neonate death occurred in preterm infants. Cause of death varied with the age of death and gestational age. Accurate and prompt evaluation of the long-term outcomes should be carried out to guide the critical decision.

Background: Retinopathy of prematurity (ROP) is a gestational age (GA)-related illness that can lead to blindness in premature infants. Timely screening of premature infants could improve visual prognosis. Objective: To evaluate the WINROP algorithm as a method of predicting severe ROP in a Chinese population. Methods: 590 infants with a GA <32 weeks were entered into an online surveillance system (www.winrop.com) that included ROP evaluations and weekly weight measurements from birth to a corrected GA of 40 weeks. If the rate of weight gain decreased to a certain degree, the algorithm signaled an alarm that the infant was at risk for developing sight-threatening ROP. Each infant was categorized as having no, mild, or severe ROP. Results: Among the 590 infants with a GA <32 weeks, an alarm was triggered in 85 infants (14.4%), 50 of which developed severe ROP and were identified in this alarm group. Twenty-seven infants triggered the alarm signal in the first week after birth and 7 infants triggered the alarm at birth. Seven of the infants developed proliferative ROP and the median GA at birth for these infants was 31 weeks. Conclusions: The WINROP system had a sensitivity of 87.5% in a Chinese population for the early identification of infants that developed severe ROP. Postnatal weight gain may help predict ROP in lower birth weight infants.

OBJECTIVE:To carry out a nationwide epidemiologic survey on the neonates in urban hospitals with an attempt to understand the disease spectrum and treatment outcomes of hospitalized neonates in China.METHODS:The clinical data of 43,289 hospitalized neonates from 86 hospitals in 47 Chinese cities (22 provinces) between January 1, 2005 and December 31, 2005 were retrospectively analyzed.RESULTS:The male:female ratio was 1.73:1. Premature infants accounted for 26.2% of the hospitalized neonates, which was higher than that reported in 2002 (19.7%). The top three diseases during the neonatal period were jaundice, pneumonia, and hypoxic-ischemic encephalopathy. The incidences of pneumonia, meconium aspiration syndrome, and bilirubin encephalopathy in term infants were higher than those in premature infants, while the incidences of asphyxia, respiratory distress syndrome, and pulmonary hemorrhage in term infants were lower than those in premature infants. The incidences of asphyxia, small for gestational age infant, and wet lung were higher in neonates whose mother had pregnancy induced hypertension. The outcomes of these hospitalized neonates included: recovered, 63.9%; improved, 27.3%; discharged due to the family's own decisions, 7.6%, and died, 1.2%. Nearly half (46.4%) of the neonatal death occurred within 24 hrs after admission.CONCLUSION:The incidence of premature birth shows an increasing trend among hospitalized neonates. Since the neonatal deaths mainly occur within 24 hrs after admission, monitoring during this period should be enhanced.