Extremely preterm infants born outside a provincial tertiary perinatal center and transferred postnatally associated with poor outcomes: a real-world observational study

IntroductionExtremely preterm infants (EPIs) have high morbidity and mortality, and are recommended to be born in a tertiary perinatal center (inborn). However, many EPIs in central China are born in lower-level hospitals and transferred postnatally, the outcomes of which remain to be investigated.MethodsEPIs admitted to the Department of Neonatology, Maternal and Child Health Hospital of Hubei Province from January 2013 to December 2022 were retrospectively recruited and divided into the control (inborn) and transfer groups (born in other hospitals). The neonatal and maternal characteristics, neonatal outcomes, and the treatment of survival EPIs were analyzed.ResultsA total of 174 and 109 EPIs were recruited in the control and transfer groups, respectively. EPIs in the transfer group have a higher birth weight and a lower proportion of multiple pregnancies than the control group (all P < 0.05). The proportions of antenatal steroids, magnesium sulfate, cesarean delivery, premature rupture of membranes ≥18 h, gestational diabetes, and amniotic fluid abnormalities were lower in the transfer group (all P < 0.05). Survival rates (64.22% vs. 56.32%), proportions of severe periventricular-intraventricular hemorrhage (PIVH) (11.93% vs. 11.49%), severe bronchopulmonary dysplasia (sBPD) (21.05% vs. 20%), and severe retinopathy of prematurity (ROP) (24.77% vs. 20.11%) were similar in the transfer and control groups (all P > 0.05). However, the transfer group had higher proportions of severe birth asphyxia (34.86% vs. 13.22%, P < 0.001), PIVH (42.20% vs. 29.89%, P = 0.034), and extrauterine growth retardation (EUGR) (17.43% vs. 6.32%, P = 0.003). Less surfactant utilization was found in the transfer group among survival EPIs (70.00% vs. 93.88%, P < 0.001).ConclusionEPIs born outside a tertiary perinatal center and transferred postnatally did not have significantly higher mortality and rates of severe complications (severe PIVH, severe ROP, and sBPD), but there may be an increased risk of severe asphyxia, PIVH and EUGR. This may be due to differences in maternal and neonatal characteristics and management. Further follow-up is needed to compare neurodevelopmental outcomes, and it is recommended to transfer the EPIs in utero to reduce the risk of poor physical and neurological development

Anomaly Detection and Explanation Discovery on Event Streams

International audienceAs enterprise information systems are collecting event streams from various sources, the ability of a system to automatically detect anomalous events and further provide human readable explanations is of paramount importance. In this position paper, we argue for the need of a new type of data stream analytics that can address anomaly detection and explanation discovery in a single, integrated system, which not only offers increased business intelligence, but also opens up opportunities for improved solutions. In particular , we propose a two-pass approach to building such a system, highlight the challenges, and offer initial directions for solutions

Predictive factors influencing outcome of early cranioplasty after decompressive craniectomy: a outcome prediction model study

ObjectiveThe timing of cranioplasty (CP) has become a widely debated topic in research, there is currently no unified standard. To this end, we established a outcome prediction model to explore the factors influencing the outcome of early CP. Our aim is to provide theoretical and practical basis for whether patients with skull defects after decompressive craniectomy (DC) are suitable for early CP.MethodsA total of 90 patients with early CP after DC from January 2020 to December 2021 were retrospectively collected as the training group, and another 52 patients with early CP after DC from January 2022 to March 2023 were collected as the validation group. The Nomogram was established to explore the predictive factors that affect the outcome of early CP by Least absolute shrinkage analysis and selection operator (LASSO) regression and Logistic regression analysis. Receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the prediction model. Calibration curve was used to evaluate the accuracy of data fitting, and decision curve analysis (DCA) diagram was used to evaluate the benefit of using the model.ResultsAge, preoperative GCS, preoperative NIHSS, defect area, and interval time from DC to CP were the predictors of the risk prediction model of early CP in patients with skull defects. The area under ROC curve (AUC) of the training group was 0.924 (95%CI: 0.867–0.980), and the AUC of the validation group was 0.918 (95%CI, 0.842–0.993). Hosmer-Lemeshow fit test showed that the mean absolute error was small, and the fit degree was good. The probability threshold of decision risk curve was wide and had practical value.ConclusionThe prediction model that considers the age, preoperative GCS, preoperative NIHSS, defect area, and interval time from DC has good predictive ability

Risk factors and early markers for echovirus type 11 associated haemorrhage-hepatitis syndrome in neonates, a retrospective cohort study

BackgroundEchovirus type 11(E-11) can cause fatal haemorrhage-hepatitis syndrome in neonates. This study aims to investigate clinical risk factors and early markers of E-11 associated neonatal haemorrhage-hepatitis syndrome.MethodsThis is a multicentre retrospective cohort study of 105 neonates with E-11 infection in China. Patients with haemorrhage-hepatitis syndrome (the severe group) were compared with those with mild disease. Clinical risk factors and early markers of haemorrhage-hepatitis syndrome were analysed. In addition, cytokine analysis were performed in selective patients to explore the immune responses.ResultsIn addition to prematurity, low birth weight, premature rupture of fetal membrane, total parenteral nutrition (PN) (OR, 28.7; 95% CI, 2.8–295.1) and partial PN (OR, 12.9; 95% CI, 2.2–77.5) prior to the onset of disease were identified as risk factors of developing haemorrhage-hepatitis syndrome. Progressive decrease in haemoglobin levels (per 10 g/L; OR, 1.5; 95% CI, 1.1–2.0) and platelet (PLT) < 140 × 10⁹/L at early stage of illness (OR, 17.7; 95% CI, 1.4–221.5) were associated with the development of haemorrhage-hepatitis syndrome. Immunological workup revealed significantly increased interferon-inducible protein-10(IP-10) (P < 0.0005) but decreased IFN-α (P < 0.05) in peripheral blood in severe patients compared with the mild cases.ConclusionsPN may potentiate the development of E-11 associated haemorrhage-hepatitis syndrome. Early onset of thrombocytopenia and decreased haemoglobin could be helpful in early identification of neonates with the disease. The low level of IFN-α and elevated expression of IP-10 may promote the progression of haemorrhage-hepatitis syndrome

Fuzzy clustering ensemble based on mutual information

Abstract:-Clustering ensemble is a new topic in machine learning. It can find a combined clustering with better quality from multiple partitions. But how to find the combined clustering is a difficult problem. In this paper, we extend the object function proposed by Strehl & Ghosh which is based on mutual information and we present a new algorithm similar to information bottleneck to solve the object function. This algorithm can combine “soft” partitions and need not establish label correspondence between different partitions. We conducted experiments on four real-world data sets to compare our algorithm with other five ensemble algorithms, including CSPA, HGPA, MCLA, QMI. The results indicate that our algorithm provides solutions of improved quality. Key-Words:- Clustering Ensemble, Mutual Information, soft partitions