Khan S.,University of Dammam |
Salahuddin N.,Shaheed Benazir Bhutto Women University |
Mehreen S.,North West Hospital
Macedonian Journal of Medical Sciences | Year: 2016
AIM: The basic aim of this study was to discover the association of End Stage Renal Disease (ESRD) with various risk factors. End Stage Renal Failure is the last stage of the chronic renal failure in which kidneys become completely fail to function. MATERIALS AND METHODS: The data were collected from the patients of renal diseases from three major hospitals in Peshawar, Pakistan. Odds ratio analysis was performed to examine the relationship of ESRD (a binary response variable) with various risk factors: Gender, Diabetic, Hypertension, Glomerulonephritis, Obstructive Nephropathy, Polycystic kidney disease, Myeloma, SLE Nephritis, Heredity, Hepatitis, Excess use of Drugs, heart problem and Anemia. RESULTS: Using odds ratio analysis, the authors found that the ESRD in diabetic patients was 11.04 times more than non-diabetic patients and the ESRD were 7.29 times less in non-hypertensive patients as compared to hypertensive patients. Similarly, glomerulonephritis patients had 3.115 times more risk of having ESRD than non-glomerulonephritis. Other risk factors may also, to some extent, were causes of ESRD but turned out insignificant due to stochastic sample. CONCLUSION: The authors concluded that there is a strong association between ESRD and three risk factors, namely diabetes, hypertension and glomerulonephritis. © 2016 Salahuddin Khan, Tariq Hussain, Najma Salahuddin, Salahuddin Mehreen.
PubMed | University of Dammam, Shaheed Benazir Bhutto Women University and Khyber Medical College
Type: Journal Article | Journal: Open access Macedonian journal of medical sciences | Year: 2016
End Stage Renal Failure (ESRD) is the last stage of the chronic renal failure in which kidneys become completely fail to function.The basic aim of this study was to discover the important risk factors of ESRD and to construct a model for prediction of the ESRD patients in various hospitals of Peshawar, Pakistan.The data were collected from the patients of renal diseases from three major hospitals of Peshawar. Brown method was used to obtain initial model, then backward elimination logistic regression analysis was performed to find the significant variables (risk factors). The response variable (ESRD) in this study is binary; therefore, logistic regression analysis is used to identify the significant variables. A Statistical Package GLIM and SPSS were used for fitting the model and for finding the significant variables.The backward elimination procedure selects predictor variables diabetic, hypertension, glomerulonephritis and heredity, for males. Thus, these variables are the main causes of ESRD. For females, the predictor variables selected are hypertension & (Diabetic*Hypertension), which means that hypertension and hypertensive diabetic are significant causes of ESRD.Our main conclusion from this analysis is that diabetic, hypertension and glomerulonephritis are the significant risk factors of ESRD.
PubMed | Shaheed Benazir Bhutto Women University, Johannes Gutenberg University Mainz, Ghent University, Beth Israel Deaconess Medical Center and Max Planck Institute for Polymer Research
Type: | Journal: Journal of controlled release : official journal of the Controlled Release Society | Year: 2016
Cationic nanohydrogel particles have become an attractive tool for systemic siRNA delivery, but improvement of their in vivo tolerance is desirable, especially to prevent potential long term side effects by tissue and cellular accumulation. Here we designed novel ketal cross-linked cationic nanohydrogel particles that were assessed for reduced tissue accumulation and robust siRNA delivery in vitro and in vivo. An oligo-amine cross-linker equipped with a ketal moiety in its core was synthesized and applied to nanohydrogel cross-linking of self-assembled reactive ester block copolymers in DMSO. The resulting acid-sensitive cationic nanoparticles spontaneously disassembled over time in acidic milieu, as investigated by dynamic light scattering. Fluorescent correlation spectroscopy showed effective complexation with siRNA as well as its release upon particle degradation at endosomal pH. These properties resulted in an enhanced in vitro gene knockdown for the acid-degradable cationic nanoparticles compared to their non-degradable spermine analogues. In a murine liver fibrosis model enhanced carrier and payload accumulation in the fibrotic tissue facilitated sequence-specific gene knockdown and prevented fibrosis progression. Long-term monitoring of the carrier in the body showed an enhanced clearance for the acid-degradable carrier, even after multiple dosing. Therefore, these acid-degradable cationic nanohydrogel particles can be considered as promising siRNA carriers for in vivo purposes towards therapeutic applications.
Rafiq L.,Shaheed Benazir Bhutto Women University |
Blaschke T.,University of Salzburg |
Tajbar S.,Shaheed Benazir Bhutto Women University
Advances in Space Research | Year: 2015
Advances in earth observation technology over the last two decades have resulted in improved forecasting of various hydrometeorological-related disasters. In this study the severe tropical cyclone Gonu (2-7 June, 2007) was investigated using multi-sensor satellite data sets (i.e. AIRS, METEOSAT, MODIS and QSCAT data) to monitor its overall structure, position, intensity, and motion. A high sea surface temperature and warm core anomalies (at 200. hPa and above) with respect to the pressure minima in the central core were found to have influenced the pattern of development of the tropical cyclone. High relative humidity in the middle troposphere was aligned with temperature minima at 850. hPa and 700. hPa; high winds (above 120 knots) and closed pressure contours were observed during the intensification stage. A contour analysis of outgoing longwave radiation (OLR) provided an explanation for the direction of movement of the cyclone. The translational movement and velocities (ground speed) of the tropical cyclone were calculated using the surface pressure of the cyclone's central core. Statistical analyses revealed a strong correlation between the maximum wind speeds within the cyclone and various atmospheric parameters. We conclude with a discussion of the significance of these findings with regard to cyclone forecasting within the framework of early warning and disaster management. © 2015 COSPAR.
Malik F.R.,Riphah International University |
Malik B.B.,Shaheed Benazir Bhutto Women University |
Irfan M.,Riphah International University
Journal of Postgraduate Medical Institute | Year: 2015
Objective: To compare the frequency of postnatal depression in women following Normal Vaginal Delivery and Caesarian Section Methodology: A comparative study was conducted in Departments of Obstetrics and Gynecology of Lady Reading Hospital, Khyber Teaching Hospital and Hayatabad Medical Complex, Peshawar from November 2009 to January 2010. A total of 100 women; 50 cases of Normal Vaginal Delivery and 50 cases of Caesarian Sections were included in the study through purposive, non-probability sampling technique. A semi-structured demographic proforma and Edinburg Post-Natal Depression Scale (EPNDS) were used for data collection by interviewing the cases between 1st and 8th post partum weeks. All findings were recorded in SPSS and excel sheets. Chi square test was applied as the test of significance and P- value of less than 0.05 was considered significant. Results: The mean age of the sample was 29.68+ 6.8 years (Range 15-52 years). In women that underwent Caesarean Section (n=50), 29 (58%) were found as having depressive illness while in the group of women that gave birth through Normal Vaginal delivery (n=50), 12 (24%) were having depression (p- value < 0.001). Conclusion: The study concluded that postnatal depression is significantly more common in the females undergoing caesarian sections as compared to the normal vaginal deliveries. © 2015, J post med inst. All Rights Reserved.
Sheng Q.,Harbin Engineering University |
Khalid S.S.,Chinese Academy of Agricultural Sciences |
Xiong Z.,Chinese Academy of Agricultural Sciences |
Sahib G.,Shaheed Benazir Bhutto Women University |
Zhang L.,Harbin Engineering University
Journal of Marine Science and Application | Year: 2013
In this paper, hydrodynamic analysis of vertical axis tidal turbine (both fixed pitch & variable pitch) is numerically analyzed. Two-dimensional numerical modeling & simulation of the unsteady flow through the blades of the turbine is performed using ANSYS CFX, hereafter CFX, which is based on a Reynolds-Averaged Navier-Stokes (RANS) model. A transient simulation is done for fixed pitch and variable pitch vertical axis tidal turbine using a Shear Stress Transport turbulence (SST) scheme. Main hydrodynamic parameters like torque T, combined moment C M, coefficients of performance C P and coefficient of torque C T, etc. are investigated. The modeling and meshing of turbine rotor is performed in ICEM-CFD. Moreover, the difference in meshing schemes between fixed pitch and variable pitch is also mentioned. Mesh motion option is employed for variable pitch turbine. This article is one part of the ongoing research on turbine design and developments. The numerical simulation results are validated with well reputed analytical results performed by Edinburgh Design Ltd. The article concludes with a parametric study of turbine performance, comparison between fixed and variable pitch operation for a four-bladed turbine. It is found that for variable pitch we get maximum C P and peak power at smaller revolution per minute N and tip sped ratio λ. © 2013 Harbin Engineering University and Springer-Verlag Berlin Heidelberg.
Fida M.-R.,Shaheed Benazir Bhutto Women University |
Ali M.,Institute of Management Sciences
2013 IEEE 11th Malaysia International Conference on Communications, MICC 2013 | Year: 2013
Frequent change in the topology of a disrupted social network is a barrier in using traditional routing protocols. One way to deal with this problem is to collect mobility profiles of nodes and to utilize them for future routing decisions. The solution however lacks scalability since it is difficult for nodes to keep updated information of the whole network. The paper thus devises a scalable scheme that exploits the limited social circles of the mobile device owners; i.e. it breaks network into social communities and employs a fine-grained heuristic routing scheme for intra-community communication. Moreover the paper specifies a simple method for identification of bridging nodes to transfer message to destination lying outside the community. The idea paper is expected to bring a near to optimal routing solution for disrupted social networks. © 2013 IEEE.
Fida M.,Shaheed Benazir Bhutto Women University |
Fida M.,Institute of Management Sciences |
Ali M.,Institute of Management Sciences |
Adnan A.,Institute of Management Sciences
6th International Conference on Computing, Communications and Networking Technologies, ICCCNT 2015 | Year: 2015
Changing topology and missing infrastructure makes conventional routing schemes useless. To overcome the communication problem, routing protocols ranging from contact-oblivious to contact-based have been tried for intermittently connected networks. These schemes vary highly in complexity and performance however they share the issue of non-scalability. © 2015 IEEE.
Ali S.,University of Peshawar |
Ali A.,University of Peshawar |
Khan S.A.,Abdul Wali Khan University Mardan |
Hussain S.,Shaheed Benazir Bhutto Women University
Computational and Mathematical Methods in Medicine | Year: 2016
For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML) method is better than Penalized Quasilikelihood (PQL) method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method. © 2016 Sabz Ali et al.
PubMed | Shaheed Benazir Bhutto Women University, Abdul Wali Khan University Mardan and University of Peshawar
Type: | Journal: Computational and mathematical methods in medicine | Year: 2016
For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML) method is better than Penalized Quasilikelihood (PQL) method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.