16 research outputs found
Nosocomial infection in an Iranian neonatal intensive care unit: Hospital epidemiology and risk factors
Background: Hospital-acquired infection is one of the main concerns in Neonatal Intensive Care Units (NICUs), leading to increased mortality, hospital stay, and costs. Objectives: This study aimed to investigate the risk factors of hospital-acquired infection in NICUs. Methods: A descriptive, cross-sectional, prospective study was conducted in the NICU of Ali Asghar Children Hospital for one year. All admitted newborns were sampled on a simple basis. The criteria for the diagnosis of hospital-acquired infection were based on the definitions of the CDC and the NNIS system. Risk factors such as days of fully catheters usage, nurse-to-patient ratio, history of surgery, prematurity, and mechanical ventilation were considered as variables. The data collection tools consisted of a patient information questionnaire, the monthly report of the hospital infection control committee based on the NNIS system, a daily schedule of all risk factors for each infant, and the monthly nurse-to-patient ratio in the NICU. The STATA software was used for data analysis. Results: In our study, 654 newborns were enrolled. The rate of hospital-acquired infections was 13.5. Moreover, 80.7 of the cases exhibited sepsis (72.7 diagnosed based on clinical findings and 8 based on positive blood culture). Statistical analysis showed 9 pneumonia cases, 8 surgical site infection cases, and 2.3 urinary tract infection cases. The average time to the occurrence of hospital-acquired infection was 13.5 days after admission. All risk factors were significantly higher in the infected group than in the control group (P = 0.0001). Furthermore, surgical interventions were significantly more in the infected group than in the non-infected group (34.1 vs. 6.7, respectively, P = 0.0001). The prevalence rates in different weight ranges (less than 1000 g, 1001 to 1500 g, 1501 to 2500, and above 2501 g) were 2.6, 6.9, 21.4, and 69.1, respectively, in the infected group, which were significantly different from those of the non-infected group (P = 0.0001). The most common etiologic microorganism was Acinetobacter baumannii. Conclusions: Factors such as surgery, the presence of a central venous catheter, and the increased length of hospital stay significantly increased the hospital-acquired infections. Reducing invasive procedures, maintenance of full catheters, and providing optimal nursing care can help control hospital-acquired infections. © 2020, Author(s)
MONET: a toolbox integrating top-performing methods for network modularization.
We define a disease module as a partition of a molecular network whose components are jointly associated with one or several diseases or risk factors thereof. Identification of such modules, across different types of networks, has great potential for elucidating disease mechanisms and establishing new powerful biomarkers. To this end, we launched the 'Disease Module Identification (DMI) DREAM Challenge', a community effort to build and evaluate unsupervised molecular network modularization algorithms. Here, we present MONET, a toolbox providing easy and unified access to the three top-performing methods from the DMI DREAM Challenge for the bioinformatics community.
MONET is a command line tool for Linux, based on Docker and Singularity containers; the core algorithms were written in R, Python, Ada and C++. It is freely available for download at https://github.com/BergmannLab/MONET.git.
Supplementary data are available at Bioinformatics online
Evaluation of cortisol level in premature neonates: Are there any correlations between prevalence of patent ductus arteriosus and prenatal administration of betamethasone?
Background: The results of previous studies suggested that there is an increased risk of patent ductus arteriosus (PDA) in the neonates with lower serum cortisol levels. This study aimed to assess the association between serum cortisol values and PDA and investigate if there is an association between PDA and the antenatal administration of betamethasone. Methods: The present study was carried out on the neonates with gestational age between 28 to 35 weeks. The prenatal administration of betamethasone to the mothers was extracted from the records. A pediatric cardiologist performed an echocardiographic assessment on the second day of life (DOL) and fifth DOL and the infants were evaluated for the presence of PDA. The blood samples were obtained on the second and fifth DOL and serum cortisol levels were measured. We evaluated the association between serum cortisol levels and PDA. Also, the correlation between PDA and the antenatal administration of betamethasone was assessed. Results: The mean scores of serum cortisol levels on the second DOL in the neonates with and without PDA were 4.99±2.69 (μg/dl) and 7.23±2.87 (μg/dl), respectively that were significantly lower in the first group, compared to those of the second group. However, the mean levels of serum cortisol in the neonates with and without the prenatal administration of betamethasone were not significant (P=0.522). Conclusion: We have concluded that lower serum cortisol level was associated with the increase in the risk of PDA and the prenatal administration of glucocorticoids may not reduce the occurrence of PDA. © 2019 Mashhad University of Medical Sciences. All rights reserved
Transplacental transmission of SARS-CoV-2 infection: A case report from Iran
We report a case of SARS-CoV-2 vertical transmission through the placenta in a neonate whose mother had non-M3 acute myeloid leukemia (AML) that was complicated with Covid-19 in the last trimester. Viral load in nasopharyngeal swabs from mother and neonate were high. Real-time PCR of the fetal side of the placenta was positive for SARS-CoV-2, which makes it possible to consider this case as a congenital case of SARS-CoV-2 infection that is transmitted through vertical transmission. © 2020, Author(s)
Identifying communities from multiplex biological networks by randomized optimization of modularity
Identifying communities from multiplex biological networks by randomized optimization of modularity
Joint role and community detection in networks via L<sub>2,1</sub> norm regularized nonnegative matrix tri-factorization
Role discovery and community detection in networks are two essential tasks in network analytics where the role denotes the global structural patterns of nodes in networks and the community represents the local connections of nodes in networks. Previous studies viewed these two tasks orthogonally and solved them independently while the relation between them has been totally neglected. However, it is intuitive that roles and communities in a network are correlated and complementary to each other. In this paper, we propose a novel model for simultaneous roles and communities detection (REACT) in networks. REACT uses non-negative matrix tri-factorization (NMTF) to detect roles and communities and utilizes L2,1 norm as the regularization to capture the diversity relation between roles and communities. The proposed model has several advantages comparing with other existing methods: (1) it incorporates the diversity relation between roles and communities to detect them simultaneously using a unified model, and (2) it provides extra information about the interaction patterns between roles and between communities using NMTF. To analyze the performance of REACT, we conduct experiments on several real-world SNs from different domains. By comparing with state-of-the-art community detection and role discovery methods, the obtained results demonstrate REACT performs best for both role and community detection tasks. Moreover, our model provides a better interpretation for the interaction patterns between communities and between roles.</p