Prevalence of chronic kidney disease in South Asia: a systematic review

Background: Chronic kidney disease (CKD) is becoming a major public health problem around the world. But the prevalence has not been reported in South Asian region as a whole. This study aimed to systematically review the existing data from population based studies in this region to bridge this gap. Methods Articles published and reported prevalence of CKD according to K/DOQI practice guideline in eight South Asian countries between December 1955 and April 2017 were searched, screened and evaluated from seven electronic databases using the PRISMA checklist. CKD was defined as creatinine clearance (CrCl) or GFR less than 60 ml/min/1.73 m2. Results Sixteen population-based studies were found from four South Asian countries (India, Bangladesh, Pakistan and Nepal) that used eGFR to measure CKD. No study was available from Sri Lanka, Maldives, Bhutan and Afghanistan. Number of participants ranged from 301 in Pakistan to 12,271 in India. Majority of the studies focused solely on urban population. Different studies used different equations for measuring eGFR. The prevalence of CKD ranged from 10.6% in Nepal to 23.3% in Pakistan using MDRD equation. This prevalence was higher among older age group people. Equal number of studies reported high prevalence among male and female each. Conclusions This systematic review reported high prevalence of CKD in South Asian countries. The findings of this study will help pertinent stakeholders to prepare suitable policy and effective public health intervention in order to reduce the burden of this deadly disease in the most densely populated share of the globe

QNAT: a graphical tool for the analysis of queueing networks

The Queueing Network Analysis Tool (QNAT) is a powerful package for analysing a wide variety of queueing networks. QNAT has a friendly GUI for a PC-Windows environment and uses MathematicaTM as its computing platform. QNAT can handle general configurations of open and closed networks of both finite and infinite capacity queues. Incorporation of fork-join nodes (with and without a synchronising queue), multiclass customers, mixed customer classes and blocking mechanisms of different types are some of the other features available in QNAT.© IEE

Clinical profile and outcome of perinatal asphyxia in a tertiary care centre

Abstract The aim was to study the clinical profile and outcome of term asphyxiated newborns admitted to our hospital. This was a retrospective observational study conducted from July 2013 to August 2014. Sixty newborn babies, who fulfilled the selection criteria, were included in the study. Out of 1167 admissions, 60 cases (5.1%) were diagnosed of birth asphyxia with APGAR score of </=6 at 5 minutes. Thirty four babies (56.66%) were inborn and 26 babies (43%) were outborn. Forty two babies (70%) were found to be males and 18 (30%) were females. Majority of the babies i.e. 80% (48cases) were appropriate for gestational age, 16% (10 babies) were IUGR babies and 3% (2 babies) were large for gestational age. Majority of them (70%) were delivered vaginally, 15 babies (25%) by caesarian section and 3 babies (5%) by instrumental delivery. Out of the total, it was found that 40% had meconium stained liquor, 13.3% mothers had PIH, 11.6% had PROM and 3 (5%) had cord prolapse. Of the total, hypoxic ischaemic encephalopathy (HIE) was diagnosed in 31.7%, with stage I in 52.6%, stage II in 31.5% babies and stage III in 15.7% babies. ABG analysis showed moderate acidemia in 65% and severe in 35%. The mortality was 8% (5 babies). All the three HIE stage III cases died and the remaining 2 cases died of MAS with early onset sepsis. Keywords: HIE (hypoxic ischaemic encephalopathy), ABG (arterial blood gases), MSAF (meconium stained amniotic fluid), PROM (premature rupture of membranes), PIH (pregnancy induced hypertension

Sharing knowledge in digital ecosystems using semantic multimedia big data

The use of formal representations has a basic importance in the era of big data. This need is more evident in the context of multimedia big data due to the intrinsic complexity of this type of data. Furthermore, the relationships between objects should be clearly expressed and formalized to give the right meaning to the correlation of data. For this reason the design of formal models to represent and manage information is a necessary task to implement intelligent information systems. Approaches based on the semantic web need to improve the data models that are the basis for implementing big data applications. Using these models, data and information visualization becomes an intrinsic and strategic task for the analysis and exploration of multimedia Big Data. In this article we propose the use of a semantic approach to formalize the structure of a multimedia Big Data model. Moreover, the identification of multimodal features to represent concepts and linguistic-semantic properties to relate them is an effective way to bridge the gap between target semantic classes and low-level multimedia descriptors. The proposed model has been implemented in a NoSQL graph database populated by different knowledge sources. We explore a visualization strategy of this large knowledge base and we present and discuss a case study for sharing information represented by our model according to a peer-to-peer(P2P) architecture. In this digital ecosystem, agents (e.g. machines, intelligent systems, robots,..) act like interconnected peers exchanging and delivering knowledge with each other