Association between Ureaplasma urealyticum colonization and bronchopulmonary dysplasia in preterm infants: a systematic review and meta-analysis.

Background: Bronchopulmonary dysplasia (BPD) is the most prevalent chronic lung disease in preterm infants. Studies have shown that Ureaplasma urealyticum (UU) infection is linked to its pathogenesis. However, it remains controversial whether UU colonization in preterm infants increases the risk of developing BPD. Objective: This study aimed to conduct a systematic review and meta-analysis to summarize the correlation between UU and BPD. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, Wanfang Database, Chinese National Knowledge Infrastructure Database, Chinese Science and Technique Journal Database, and the China Biology Medicine disc from their inception to March 15, 2024. We included cohort and case-control studies investigating the association between UU infections and BPD in preterm infants, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Newcastle-Ottawa Scale was used for quality assessment. The outcome was defined as the continued need for oxygen or respiratory support at 28 days after birth (BPD28) or at 36 weeks postmenstrual age (BPD36). Considering the potential publication bias in observational studies, we used a random-effects meta-analysis model, assessed heterogeneity (I2), performed subgroup analyses, evaluated publication bias, and graded the quality of evidence. Results: The meta-analysis included 36 cohort studies encompassing 5,991 participants. Among these, 20 reported on BPD28, 13 on BPD36, and 3 on both. The results indicated a significant association between UU colonization and BPD28 (odds ratio (OR): 2.26, 95% confidence interval (CI): 1.78-2.85, P < 0.00001, 23 studies, very low certainty of evidence) and BPD36 (OR: 2.13, 95% CI: 1.47-3.07, P < 0.0001, 16 studies, very low certainty of evidence). Conclusion: There is a correlation between UU colonization and the development of BPD in preterm infants. Future research should prioritize well-designed, large-scale, high-quality randomized controlled trials (RCTs) to comprehensively assess the risk of BPD in neonates following UU infection and to provide stronger evidence for clinical screening and prevention strategies to improve the prognosis of affected newborns. Systematic Review Registration: https://www.crd.york.ac.uk/, identifier (CRD42024524846).

Machine learning-causal inference based on multi-omics data reveals the association of altered gut bacteria and bile acid metabolism with neonatal jaundice.

Early identification of neonatal jaundice (NJ) appears to be essential to avoid bilirubin encephalopathy and neurological sequelae. The interaction between gut microbiota and metabolites plays an important role in early life. It is unclear whether the composition of the gut microbiota and metabolites can be used as an early indicator of NJ or to aid clinical decision-making. This study involved a total of 196 neonates and conducted two rounds of "discovery-validation" research on the gut microbiome-metabolome. It utilized methods of machine learning, causal inference, and clinical prediction model evaluation to assess the significance of gut microbiota and metabolites in classifying neonatal jaundice (NJ), as well as the potential causal relationships between corresponding clinical variables and NJ. In the discovery stage, NJ-associated gut microbiota, network modules, and metabolite composition were identified by gut microbiome-metabolome association analysis. The NJ-associated gut microbiota was closely related to bile acid metabolites. By Lasso machine learning assessment, we found that the gut bacteria were associated with abnormal bile acid metabolism. The machine learning-causal inference approach revealed that gut bacteria affected serum total bilirubin and NJ by influencing bile acid metabolism. NJ-associated gut bile acids are potential biomarkers of NJ, and clinical prediction models constructed based on these biomarkers have some clinical effects and the model may be used for disease risk prediction. In the validation stage, it was found that intestinal metabolites can predict NJ, and the machine learning-causal inference approach revealed that bile acid metabolites affected NJ itself by affecting the total bilirubin content. Intestinal bile acid metabolites are potential biomarkers of NJ. By applying machine learning-causal inference methods to gut microbiome-metabolome association studies, we found NJ-associated intestinal bacteria and their network modules and bile acid metabolite composition. The important role of intestinal bacteria and bile acid metabolites in NJ was determined, which can predict the risk of NJ.

Association analysis of the intestinal microbiome-metabolome found that neonatal jaundice (NJ)-related intestinal microbiota, network modules and metabolite composition, and the intestinal microbiota are closely related to bile acid metabolites.Gut bacteria were found to affect serum total bilirubin (TBIL) and NJ by influencing bile acid metabolism through a machine learning-causal inference approach, and bile acid metabolites affected NJ itself by affecting the TBIL content.NJ-associated gut bacteria and bile acids are potential biomarkers of NJ, and clinical decision-making models based on these biomarkers have some clinical effects for disease risk prediction.

The Association of Neonatal Gut Microbiota Community State Types with Birth Weight.

BACKGROUND: while most gut microbiota research has focused on term infants, the health outcomes of preterm infants are equally important. Very-low-birth-weight (VLBW) or extremely-low-birth-weight (ELBW) preterm infants have a unique gut microbiota structure, and probiotics have been reported to somewhat accelerate the maturation of the gut microbiota and reduce intestinal inflammation in very-low preterm infants, thereby improving their long-term outcomes. The aim of this study was to investigate the structure of gut microbiota in ELBW neonates to facilitate the early identification of different types of low-birth-weight (LBW) preterm infants. METHODS: a total of 98 fecal samples from 39 low-birth-weight preterm infants were included in this study. Three groups were categorized according to different birth weights: ELBW (n = 39), VLBW (n = 39), and LBW (n = 20). The gut microbiota structure of neonates was obtained by 16S rRNA gene sequencing, and microbiome analysis was conducted. The community state type (CST) of the microbiota was predicted, and correlation analysis was conducted with clinical indicators. Differences in the gut microbiota composition among ELBW, VLBW, and LBW were compared. The value of gut microbiota composition in the diagnosis of extremely low birth weight was assessed via a random forest-machine learning approach. RESULTS: we briefly analyzed the structure of the gut microbiota of preterm infants with low birth weight and found that the ELBW, VLBW, and LBW groups exhibited gut microbiota with heterogeneous compositions. Low-birth-weight preterm infants showed five CSTs dominated by Enterococcus, Staphylococcus, Klebsiella, Streptococcus, Pseudescherichia, and Acinetobacter. The birth weight and clinical indicators related to prematurity were associated with the CST. We found the composition of the gut microbiota was specific to the different types of low-birth-weight premature infants, namely, ELBW, VLBW, and LBW. The ELBW group exhibited significantly more of the potentially harmful intestinal bacteria Acinetobacter relative to the VLBW and LBW groups, as well as a significantly lower abundance of the intestinal probiotic Bifidobacterium. Based on the gut microbiota's composition and its correlation with low weight, we constructed random forest model classifiers to distinguish ELBW and VLBW/LBW infants. The area under the curve of the classifiers constructed with Enterococcus, Klebsiella, and Acinetobacter was found to reach 0.836 by machine learning evaluation, suggesting that gut microbiota composition may be a potential biomarker for ELBW preterm infants. CONCLUSIONS: the gut bacteria of preterm infants showed a CST with Enterococcus, Klebsiella, and Acinetobacter as the dominant genera. ELBW preterm infants exhibit an increase in the abundance of potentially harmful bacteria in the gut and a decrease in beneficial bacteria. These potentially harmful bacteria may be potential biomarkers for ELBW preterm infants.

[A multicenter study of neonatal stroke in Shenzhen, China]. / 深圳市新生儿脑卒中多中心现况调查.

OBJECTIVES: To investigate the incidence rate, clinical characteristics, and prognosis of neonatal stroke in Shenzhen, China. METHODS: Led by Shenzhen Children's Hospital, the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022. The incidence, clinical characteristics, treatment, and prognosis of neonatal stroke in Shenzhen were analyzed. RESULTS: The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137, 1/6 060, and 1/7 704, respectively. Ischemic stroke accounted for 75% (27/36); boys accounted for 64% (23/36). Among the 36 neonates, 31 (86%) had disease onset within 3 days after birth, and 19 (53%) had convulsion as the initial presentation. Cerebral MRI showed that 22 neonates (61%) had left cerebral infarction and 13 (36%) had basal ganglia infarction. Magnetic resonance angiography was performed for 12 neonates, among whom 9 (75%) had involvement of the middle cerebral artery. Electroencephalography was performed for 29 neonates, with sharp waves in 21 neonates (72%) and seizures in 10 neonates (34%). Symptomatic/supportive treatment varied across different hospitals. Neonatal Behavioral Neurological Assessment was performed for 12 neonates (33%, 12/36), with a mean score of (32±4) points. The prognosis of 27 neonates was followed up to around 12 months of age, with 44% (12/27) of the neonates having a good prognosis. CONCLUSIONS: Ischemic stroke is the main type of neonatal stroke, often with convulsions as the initial presentation, involvement of the middle cerebral artery, sharp waves on electroencephalography, and a relatively low neurodevelopment score. Symptomatic/supportive treatment is the main treatment method, and some neonates tend to have a poor prognosis.

Correlation of DNA load, genotyping, and clinical phenotype of Mycoplasma pneumoniae infection in children.

Introduction: This study aimed to investigate the correlation between Mycoplasma pneumoniae (MP)-DNA load in the bronchoalveolar lavage fluid (BALF) of children with MP pneumonia (MPP) and its subtypes, relevant laboratory data, imaging, extrapulmonary complications in infected children, and its clinical significance in evaluating the disease. Methods: Children hospitalized with MPP at Tianjin Children's Hospital between December 2017 and December 2020 were selected for the study, excluding those with mixed viral, bacterial, and fungal infections. Children were divided into low- and high-load groups according to the MP DNA load in BALF using real-time quantitative fluorescence polymerase chain reaction (PCR). After a successful MP culture, positive specimens were subjected to PCR-Restriction fragment length polymorphism and Multiple-locus variable number tandem repeat analysis typing. Basic data, clinical information, laboratory data, and radiological results were collected from all children included in the study. Results: The PI-I type dominated the different load groups. Children in the low-load group had more wheezing and shortness of breath; however, children in the high-load group had a higher length of hospitalization, maximum fever temperature, higher chills/chilliness, incidence of abdominal pain, and higher C-reactive protein (CRP), procalcitonin (PCT) and aspartate aminotransferase (AST) levels. Children in the high-load group were more likely to have imaging changes such as pleural effusion, and the incidence of respiratory infections and extrapulmonary complications was higher than that of those in the low-load group. We applied Spearman's correlation analysis to clarify the relationship between MP DNA load and the clinical severity of MPP. We found that MP DNA load was positively correlated with length of hospitalization, maximum fever temperature, CRP, PCT, Interleukin-6 (IL-6), and AST levels, and negatively correlated with fever and cough durations, white blood cell count (WBC), and proportion of monocytes (MONO). The degree of correlation was as follows: length of hospitalization > IL-6 > cough duration > AST > fever duration > PCT > WBC > proportion of MONO > maximum fever temperature > CRP levels. Conclusions: MP DNA load was not correlated with MP typing but was significantly correlated with the children's clinical phenotype. Therefore, the MP DNA load helps in the early diagnosis of infection and can better predict disease regression.

Inductively coupled plasma mass spectrometry based urine metallome to construct clinical decision models for autism spectrum disorder.

BACKGROUND: The global prevalence of autism spectrum disorder (ASD) is on the rise, and high levels of exposure to toxic heavy metals may be associated with this increase. Urine analysis is a noninvasive method for investigating the accumulation and excretion of heavy metals. The aim of this study was to identify ASD-associated urinary metal markers. METHODS: Overall, 70 children with ASD and 71 children with typical development (TD) were enrolled in this retrospective case-control study. In this metallomics investigation, inductively coupled plasma mass spectrometry was performed to obtain the urine profile of 27 metals. RESULTS: Children with ASD could be distinguished from children with TD based on the urine metal profile, with ASD children showing an increased urine metal Shannon diversity. A metallome-wide association analysis was used to identify seven ASD-related metals in urine, with cobalt, aluminum, selenium, and lithium significantly higher, and manganese, mercury, and titanium significantly lower in the urine of children with ASD than in children with TD. The least absolute shrinkage and selection operator (LASSO) machine learning method was used to rank the seven urine metals in terms of their effect on ASD. On the basis of these seven urine metals, we constructed a LASSO regression model for ASD classification and found an area under the receiver operating characteristic curve of 0.913. We also constructed a clinical prediction model for ASD based on the seven metals that were different in the urine of children with ASD and found that the model would be useful for the clinical prediction of ASD risk. CONCLUSIONS: The study findings suggest that altered urine metal concentrations may be an important risk factor for ASD, and we recommend further exploration of the mechanisms and clinical treatment measures for such alterations.

Identifying Rare Genetic Variants of Immune Mediators as Risk Factors for Autism Spectrum Disorder.

Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2−12 years old) and 107 healthy controls without ASD (20−78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis.

Machine learning approach identifies meconium metabolites as potential biomarkers of neonatal hyperbilirubinemia.

Background: The gut microbiota plays an important role in the early stages of human life. Our previous study showed that the abundance of intestinal flora involved in galactose metabolism was altered and correlated with increased serum bilirubin levels in children with jaundice. We conducted the present study to systematically evaluate alterations in the meconium metabolome of neonates with jaundice and search for metabolic markers associated with neonatal jaundice. Methods: We included 68 neonates with neonatal hyperbilirubinemia, also known as neonatal jaundice (NJ) and 68 matched healthy controls (HC), collected meconium samples from them at birth, and performed metabolomic analysis via liquid chromatography-mass spectrometry. Results: Gut metabolites enabled clearly distinguishing the neonatal jaundice (NJ) and healthy control (HC) groups. We also identified the compositions of the gut metabolites that differed significantly between the NJ and HC groups; these differentially significant metabolites were enriched in aminyl tRNA biosynthesis; pantothenic acid and coenzyme biosynthesis; and the valine, leucine and isoleucine biosynthesis pathways. Gut branched-chain amino acid (BCAA) levels were positively correlated with serum bilirubin levels, and the area under the receiver operating characteristic curve of the random forest classifier model based on BCAAs, proline, methionine, phenylalanine and total bilirubin reached 96.9%, showing good potential for diagnostic applications. Machine learning-based causal inference analysis revealed the causal effect of BCAAs on serum total bilirubin and NJ. Conclusions: Altered gut metabolites in neonates with jaundice showed that increased BCAAs and total serum bilirubin were positively correlated. BCAAs proline, methionine, phenylalanine are potential biomarkers of NJ.

Clinical Manifestations of Neonatal Hyperbilirubinemia Are Related to Alterations in the Gut Microbiota.

BACKGROUND AND PURPOSE: Neonatal hyperbilirubinemia, also known as neonatal jaundice, is a common and frequent clinical condition with a complex etiology that can lead to brain damage in severe cases. Early recognition of hyperbilirubinemia and timely intervention and treatment can help reduce the occurrence of sequelae. This study was conducted to identify whether the gut microbiota composition can distinguish neonates with hyperbilirubinemia. METHODS: Meconium samples were collected from 69 neonates with neonatal jaundice (NJ) and 69 age- and sex-matched neonates without clinically significant jaundice (healthy controls; HCs) for 16S rRNA gene sequencing and microbiome analysis. RESULTS: Compared with HCs, the Chao 1 richness index of the gut microbiota was significantly decreased in the NJ group. The relative abundance of the probiotic gut bacterium, Lactobacillus, was significantly lower in the NJ group than in the HC group, whereas the abundances of potentially harmful gut bacteria, such as Escherichia coli and Staphylococcus, were significantly higher in the NJ group than in HCs. Correlation of the gut microbiota and clinical indicators revealed a positive correlation between Escherichia coli/Staphylococcus and serum total bilirubin levels. Finally, the results of a random forest machine-learning method to evaluate the possibility of using NJ-associated gut microbiota compositions as potential NJ biomarkers revealed an area under the curve of 96.88%. CONCLUSIONS: The abundances of Escherichia coli and Staphylococcus were positively correlated with serum total bilirubin levels. Hence, the gut microbiota composition is a potential biomarker of NJ.

Effects of mind-body practice on arterial stiffness, central hemodynamic parameters and cardiac autonomic function of college students.

A substantial number of studies have shown the beneficial effects of mind-body practice on physical fitness among both the healthy middle-aged and elderly adults and patients with chronic diseases. However, its positive effects on college students remain poorly understood. This study aimed to systematically investigate the potential efficiency of the Baduanjin exercise on the maintenance of the homeostasis of body composition and the improvement of the cardiovascular function of the college students. The study revealed a promising efficacy of the Baduanjin exercise in the prevention of the loss of water, inorganic salts, protein, and muscle contents and the accumulation of body fat. Furthermore, the present study also demonstrated the positive efficacy of Baduanjin exercise in decreasing of peripheral and central arterial blood pressure and carotid and femoral artery pulse wave velocity (cfPWV) of the college students. Moreover, the heart rate variability (HRV) analysis was also performed using the assessment of time and frequency domain indices. The data showed that all of the time-domain indices and the high-frequency (HF) band of the HRV relatively increased, whereas the low-frequency (LF) band of the HRV relatively decreased after the long-term Baduanjin exercise. Collectively, the present study suggested that a 12-week Baduanjin exercise could maintain the body composition in a relatively healthy and stable range and improve blood pressure, central hemodynamics, and the arterial stiffness of the college students. The underlying mechanism might be due to the improvement of parasympathetic activity and the suppression of sympathetic activity of college students via Baduanjin exercise.

Virulence factor-related gut microbiota genes and immunoglobulin A levels as novel markers for machine learning-based classification of autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental condition for which early identification and intervention is crucial for optimum prognosis. Our previous work showed gut Immunoglobulin A (IgA) to be significantly elevated in the gut lumen of children with ASD compared to typically developing (TD) children. Gut microbiota variations have been reported in ASD, yet not much is known about virulence factor-related gut microbiota (VFGM) genes. Upon determining the VFGM genes distinguishing ASD from TD, this study is the first to utilize VFGM genes and IgA levels for a machine learning-based classification of ASD. Sequence comparisons were performed of metagenome datasets from children with ASD (n = 43) and TD children (n = 31) against genes in the virulence factor database. VFGM gene composition was associated with ASD phenotype. VFGM gene diversity was higher in children with ASD and positively correlated with IgA content. As Group B streptococcus (GBS) genes account for the highest proportion of 24 different VFGMs between ASD and TD and positively correlate with gut IgA, GBS genes were used in combination with IgA and VFGMs diversity to distinguish ASD from TD. Given that VFGM diversity, increases in IgA, and ASD-enriched VFGM genes were independent of sex and gastrointestinal symptoms, a classification method utilizing them will not pertain only to a specific subgroup of ASD. By introducing the classification value of VFGM genes and considering that VFs can be isolated in pregnant women and newborns, these findings provide a novel machine learning-based early risk identification method for ASD.

Care Practices, Morbidity and Mortality of Preterm Neonates in China, 2013-2014: a Retrospective study.

This retrospective cohort study aimed to investigate the prevalence, morbidity, mortality and the maternal/neonatal care of preterm neonates and the perinatal risk factors for mortality. We included data on 13,701 preterm neonates born in 15 hospitals for the period 2013-2014 in China. Results showed a prevalence of preterm neonates of 9.9%. Most infants at 24-27 weeks who survived more than 12 hours were mechanically ventilated (56.1%). Few infants born before 28 weeks received CPAP without first receiving mechanical ventilation (8.1%). Few preterm neonates received antenatal steroid(35.8% at 24-27 weeks, 57.9% at 28-31 weeks, 57.0% at 32-33 weeks and 32.7% at 34-36 weeks). Overall mortality was 1.9%. Most of the deaths at 24-27 weeks of gestation occurred within 12 hours after birth, accounting for 68.1%(32/47), and within 12-72 hours after birth at 28-36 weeks of gestation, accounting for 47.4%(99/209). Rates of survival to discharge increased from 68.2% at 24-27 weeks, 93.3% at 28-31 weeks, 99.2% at 32-33 weeks to 99.4% at 34-36 weeks. The smaller of the GA, there was a greater risk of morbidities due to prematurity. Preterm birth weight (OR = 0.407, 95% CI 0.346-0.478), antenatal steroid (OR = 0.680, 95% CI 0.493-0.938), and neonatal asphyxia (OR = 3.215, 95% CI 2.180-4.741) proved to significantly influence the odds of preterm neonatal death. Overall, our results support that most of the preterm neonates at 28-36 weeks of gestation survived without major morbidity. Rate of survival of GAs less than 28 weeks was still low. Maternal and infant care practices need to be improved in the very preterm births.

Neonatal mortality and morbidity among infants between 24 to 31 complete weeks: a multicenter survey in China from 2013 to 2014.

BACKGROUND: The outcome of preterm infants has been varied in different hospitals and regions in developing countries. Regular clinical monitor are needed to know the effects of health care. This study aimed to describe the survival and morbidity rates of extreme to very preterm infants in 15 neonatal-intensive care hospitals in China. METHODS: Data were collected from January 1, 2013 to December 31, 2014 for preterm neonates with gestational age (GA) between 24 and 31 complete weeks born in hospitals from our collaborative study group. The primary outcomes were survival and major morbidities prior to hospital discharge. Major morbidities included bronchopulmonary dysplasia (BPD), intraventricular hemorrhage (IVH), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), patent ductus arteriosus (PDA) and sepsis. Mutivariate logistic regression was used to analyze the risk factor influencing on the outcomes. RESULTS: The preterm birth rate was 9.9 % (13 701/138 240). The proportion of extreme to very preterm infants was 1.1 % and 11.8 % respectively. The survival rate prior to discharge was increased with increasing GA (0, 24 weeks; 28 %, 25 weeks; 84.8 %, 26 weeks; 83.5 %, 27 weeks; 87.4 %, 28 weeks; 90.7 %, 29 weeks; 93.9 %, 30 weeks; 96 %, 31 weeks). Rate of survival and without severe morbidity according to GA were 0 at 24 weeks, 8 % at 25 weeks, 60.6 % at 26 weeks; 53.2 % at 27 weeks; 62.3 % at 28 weeks; 67.9 % at 29 weeks; 79.1 % at 30 weeks, 85.8 % at 31 weeks respectively. Rate of antenatal steroid use was 56 %. The antenatal steroid use was lower in GA < 28 weeks infants than that in GA between 28 and 32 weeks (28-44.3 % vs 49.7-60.1 %, P < 0.05). Infants at the lowest GAs had a highest incidence of morbidities. Overall, 58.5 % had respiratory distress syndrome, 12.5 % bronchopulmonary dysplasia, 3.9 % necrotizing enterocolitis, 15.4 % intraventricular hemorrhage, 5.4 % retinopathy of prematurity, 28.4 % patent ductus arteriosus, and 9.7 % sepsis. Mortality and morbidity were influenced by gestational age (OR = 0.891, 95 % CI: 0.796-0.999, p = 0.0047 and OR = 0.666, 95 % CI: 0.645-0.688, p = 0.000 respectively), birth weight (OR = 0.520, 95 % CI: 0.420-0.643, p = 0.000 and OR = 0.921, 95 % CI: 0.851-0.997, p = 0.041 respectively), SGA (OR = 1.861, 95 % CI: 1.148-3.017, p = 0.012 and OR = 1.511, 95 % CI: 1.300-1.755, p = 0.000 respectively), Apgar score <7 at 5 min (OR = 1.947, 95 % CI: 1.269-2.987, p = 0.002 and OR = 2.262, 95 % CI: 1.950-2.624, p = 0.000 respectively). The survival rate was increased with more prenatal steroid use (OR = 1.615, 95 % CI: 1.233-1.901, p = 0.033). CONCLUSION: Although most of the preterm infants with GAs ≥26 weeks survived, a high complication in survivors still can be observed. Rate of survival of GAs less than 26 weeks was still low, and quality improvement methods should be used to look into increasing the use of antenatal steroids in the very preterm births.

[Impact of premature rupture of membranes on neonatal complications in preterm infants with gestational age <37 weeks].

OBJECTIVE: To investigate the effect of premature rupture of the membrane (PROM) on neonatal complications in premature infants. METHODS: The registration information of 7684 preterm infants with gestational age <37 weeks were collected from the cooperative units in the task group between January 1, 2014 to December 31, 2014. Specially trained personnel from each cooperative units filled in the unified form in a standardized format to record the gender, gestational age, birth weight, PROM, placental abruption, antenatal corticosteroid, Apgar score, amniotic fluid pollution, and complications of the infants. The data were analyzed comparatively between the cases with PROM and those without (control). RESULTS: The preterm mortality rate was significantly lower but the incidences of ICH, NEC, ROP and BPD were significantly higher in PROM group than in the control group (P<0.05). The 95% confidence interval of the OR value was <1 for mortality, and was >1 for ICH, NEC, ROP and BPD. After adjustment for gestational age, birth weight, gender, mode of delivery, placental abruption, placenta previa, prenatal hormones, gestational diabetes mellitus (GDM), gestational period hypertension and 5-min Apgar score <7, the incidences of NEC, ROP and BPD were significantly different between the two groups (P<0.05) with 95% confidence interval of OR value >1, but the mortality rate and incidence of ICH were not significantly different between the two groups (P>0.05). CONCLUSION: PROM is a risk factor for NEC, ROP and BPD in preterm infants, and adequate intervention of PROM can reduce the incidences of such complications as NEC, ROP and BPD in the infants.

Effect of inoculum/substrate ratio on methane yield and orthophosphate release from anaerobic digestion of Microcystis spp.

A batch anaerobic test was conducted to evaluate the effects of inoculum/substrate ratios (ISRs) on the methane yield and orthophosphate release from the anaerobic digestion of Microcystis spp. The results demonstrated an obvious influence on methane yield and orthophosphate release by ISR. The maximum methane yield decreased from 140.48 to 94.42 mL/gVS when the ISR decreased from 2.0 to 0.5. The highest maximum methane yield calculated from Ørskov equation was 153.66 mL/gVS at ISR value of 1.0. The values of pH, ammonia and volatile fatty acids (VFAs) corroborated the appropriate stability of this anaerobic process.