Objective: The objective of the study was to report the socio demographic risk factors of gestational diabetes mellitus (GDM). Methods: This study was conducted in the Institute of Chemical Sciences, University of Peshawar. In this study 103 GDM and 97 healthy pregnant women (HPW) were registered in Khyber Teaching Hospital (KTH), Peshawar, Pakistan. Women with gestational diabetes were diagnosed with 75mg Oral Glucose Tolerance Test (OGTT). Data was collected through questionnaire which had information about sociodemographic risk factors. Results: Maternal age, BMI and parity of GDM were significantly higher at P<0.05 as compared to HPW. Previous history of gestational diabetes and family history of diabetes of GDM women were also significantly higher at P<0.001 as compared the control group. Socioecnomic status, education level and occupations of GDM and HPW were not significantly different. Conclusion: Maternal age, BMI, parity, previous history of gestational diabetes and family history of diabetes are the high risk factors of GDM. Socioecnomic status does not affect the prevalence of GDM.

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Introduction:The purpose of this study was to separate MAC lung disease from colonization and to define indications for treatment.Materials and Methodology:Over 4 years, we evaluated patients who had positive MAC cultures, MAC infection and coinfection with MTB. In the first study, 42 immunocompetent patients with sputum or BAL culture positive only for MAC during a single year (2004) were reviewed. On clinical and radiographic review, they were classified as disease related to MAC, likely related to MAC or unrelated to MAC. In the second study, we reviewed all immunocompetent patients, during two years (2004-2005), whose respiratory secretions cultured both MTB and nontuberculous mycobacteria (NTM). In the last study, we evaluated pulmonary function (PF) in patients with MAC infection before and after therapy (2006- 2007). PF was evaluated in patients following ATS guidelines.Results:Lung disease was related/likely related to MAC in 21 patients (50%) and not related in 21 (50%). In patients with MAC-related lung disease, the primary physician did not consider the diagnosis except when that physician was a pulmonologist. Half of those with MAC-related lung disease were smokers, white and US-born. There were 12 immunocompetent patients with MTB and NTM cultures. Eleven were non-white and all were foreign-born. Presentation and clinical course were consistent with MTB. All 8 patients with abnormal PF improved.Conclusions:The prevalence of MAC lung infection in two inner city hospitals was four times higher than that of TB. The indication for treatment of MAC infection should also rely heavily on clinical and radiological evidence when there is only one positive sputum culture. The diagnosis was considered only when the admitting physician was a pulmonologist. Most patients with combined infection were clinically consistent with MTB and responded to anti MTB treatment alone. Treatment with anti-MAC therapy improved PF in those patients whose PF was abnormal to begin with.

The Pab Formation of Zamzama block, lying in the Lower Indus Basin of Pakistan, is a prominent gas-producing sand reservoir. The optimized production is limited by water encroachment in producing wells, thus it is required to distinguish the gas-sand facies from the remainder of the wet sands and shales for additional drilling zones. An approach is adopted based on a relation between petrophysical and elastic properties to characterize the prospect locations. Petro-elastic models for the identified facies are generated to discriminate lithologies in their elastic ranges. Several elastic properties, including p-impedance (11,600-12,100 m/s*g/cc), s-impedance (7,000-7,330 m/s*g/cc), and Vp/Vs ratio (1.57-1.62), are calculated from the simultaneous prestack seismic inversion, allowing the identification of gas sands in the field. Furthermore, inverted elastic attributes and well-based lithologies are incorporated into the Bayesian framework to evaluate the probability of gas sands. To better determine reservoir quality, bulk volumes of PHIE and clay are estimated using elastic volumes trained on well logs employing Probabilistic Neural Networking (PNN), which effectively handles heterogeneity effects. The results showed that the channelized gas-sands passing through existing well locations exhibited reduced clay content and maximum effective porosities of 9%, confirming the reservoir's good quality. Such approaches can be widely implemented in producing fields to completely assess litho-facies and achieve maximum production with minimal risk.

INTRODUCTION: COVID-19 disease usually presents as a respiratory infection which can progress to pneumonia, acute respiratory distress syndrome (ARDS) and multi organ dysfunction. The more severe cases occur in older adults, with chronic conditions such as cardiovascular and cerebrovascular diseases and diabetes[1,2]. We present a case of COVID-19 infection complicated by central diabetes insipidus (DI).