Chronic pelvic pain in women: comparative study between ultrasonography and laparoscopy as diagnostic tool

Background: Chronic pelvic pain is a major cause of morbidity among the reproductive age group women. The study on patients of chronic pelvic pain aimed to compare the diagnostic accuracy of ultrasonography and laparoscopy in these patientsMethods: The study was conducted on 100 patients of chronic pelvic pain attending the gynaecology outdoor and were subjected to thorough clinical examination followed by ultrasonography and laparoscopic examination.Results: Maximum number of cases of chronic pelvic pain belonged to 25-30 years, were parous with mean duration of pain of 15.2 months. The most common complaint was vaginal discharge (70%) followed by menstrual irregularity. On clinical examination, pelvic tenderness was observed in majority (60%) of cases. USG examination showed chronic pelvic inflammatory disease in 43% cases followed by myoma (8%), ovarian cyst (5%), endometriosis (6%), pelvic congestion (5%) and no abnormal pathology in 25% cases. On laparoscopic examination, chronic pelvic inflammatory disease was present in 47% cases followed by endometriosis (11%), pelvic congestion (8%), myoma (8%), adhesions (7%) while 13% cases showed normal findings.Conclusions: Laparoscopy is more effective than ultrasonography as a diagnostic tool in patients of chronic pelvic pain.

Dyslipidaemia & Framingham risk score: Tools for prediction of cardiovascular diseases as public health problem

Background: According to WHO, CVD is the number one cause of death globally and an estimated 17.5 million people died from CVDs in 2012, representing 31% of all global deaths. Dyslipidaemia with other cardio-metabolic risk factors are one of the major risk factors for cardiovascular diseases. This study was under taken to assess the prevalence of cardiovascular risk factors among the urban population aged 18 to 40 years. Methodology: This cross-sectional study was done at UHTC (Multan Nagar) in Meerut district from May 2014 to June 2015. 150 study participants aged 18 to 40 years of both sexes were recruited using simple random sampling. Data was collected using WHO’s STEPS criteria and modified close ended questionnaire. Data was analysed using Statistical Package for Social Sciences (SPSS v19).  Results: Overall prevalence of dyslipidaemia was, low HDL-c 58.7%, hypertriglyceridemia 36%, high TC:HDL-c ratio 24%, hypercholesterolemia 14.7% and high LDL cholesterol 8.0% & Framingham risk score of developing Coronary artery disease was 8.6% risk of 6% & above and 91.4% risk of 5% or less. Conclusion: The prevalence of two cardio-metabolic risk factors was quite high in both males and females and the association between Framingham risk score & dyslipidaemias were also statistically significant. Clearly indicating that those who were having dyslipidaemia in any form were at a higher risk of having coronary artery disease in the future

Prevalence of complications of Type 2 Diabetes Mellitus and its association with different risk factors in Urban Etawah, Uttar Pradesh

Background- India is experiencing a rapid health transition, with large and rising burdens of chronic diseases, which were estimated to account for 53% of all deaths in 2005. Earlier estimates projected that the number of deaths attributable to chronic diseases would rise from 3·78 million in 1990 (40·4% of all deaths) to 7·63 million in 2020 (66·7% of all deaths). Aims and Objectives- To find out the prevalence of Complications of Type 2 Diabetes Mellitus and its association with different risk factors in Urban Etawah (U.P.) including tobacco, alcohol, fatty meals and physical activity. Material and Methods- The present study is a community-based study performed among 400 participants using cluster sampling technique in the field practice area of Urban health training centre, Department of Community Medicine, UPUMS, Saifai, Etawah. The participants were interviewed using a pre-tested questionnaire using Diabetes Complication Index.  Results- Among the diabetics, the prevalence of coronary heart disease (CHD), peripheral vascular disease (PVD), cerebrovascular accidents (CVA), cataract, neuropathy and foot problems were 24%, 24%, 7%, 15.4%, 38%, 26% and 2% respectively. A statistically significant association was seen with fatty meals and complications. Conclusion - All the diabetic complications observed need to be addressed in prevention and control strategies in the study area. Heath screening camps will be organized for the people for awareness

Awareness, Practice and Level of Anxiety using Coronavirus Anxiety Scale among the Indian Population regarding COVID -19 Pandemic

Abstract: The most important aspect of Public Health Emergency Preparedness (PHEP) involves the circulation of trustworthy and accurate information in the public health interest domain. Strict stringency measures such as nationwide lockdown impacted people's mental health. Hence, this study was planned to assess the knowledge, practice, and anxiety among the Indian population about the ongoing pandemic in the initial phase. Methods: A web-based cross-sectional study was conducted between August 1, 2020, to October 5, 2020. Coronavirus Anxiety Scale was used to determine dysfunctional anxiety. Results: Among 553 participants, 73.6% had overall good knowledge of COVID-19 with mean correct score of 6.9±1.1. Majority of participants (97%) wore mask regularly, and 93% of respondents regularly washed their hands with soap and water. Only 14 participants scored ?9 on CAS, suggesting probable cases of dysfunctional anxiety associated with the COVID-19 crisis. Conclusion: The knowledge and practices of citizens in a nation reflect their preparedness and ability to deal with a pandemic of such proportion. Good knowledge translates to good practices and therefore reduces anxiety among the population. It is deemed necessary that people's knowledge and habits, including the mental impact, be accessed at periodic intervals to track their adaptation to pandemics over time

Prevalence of Diabetic Peripheral Neuropathy among Type 2 Diabetes Mellitus patients and its associated risk factors

Background: Diabetic peripheral neuropathy (DPN) is a common and one of the severe complications of diabetes mellitus. It affects almost half the diabetic population and worsens quality of life of the patient. The present study was aimed to determine the prevalence of peripheral neuropathy and associated risk factors. Aims and Objectives: To assess the Prevalence of Diabetic Peripheral Neuropathy (DPN) among Type 2 DM patients and its associated risk factors. Material and Methods: A community based survey was conducted over a period of one and a half year. Cluster sampling technique was used to collect the study sample in urban Etawah. Study participants aged ? 30 years residing in urban Etawah with known history of Type 2 Diabetes Mellitus of ? 5 years were included in the study. Diabetic Peripheral Neuropathy (DPN) was diagnosed using 10 g monofilament test. Results: A total of 400 DM patients were enrolled in the study. Out of which 28% (n = 112) patients were diagnosed with DPN using Semmes-Weinstein (SW) 10-g monofilament test. Statistically significant association was also noted with Family history of DM, BMI, Systolic and Diastolic blood pressure, Family history of HTN and History of Smoking. Conclusion: The current study found a high prevalence of DPN (28%) and it was found to be significantly associated with advancing age, duration of diabetes and history of smoking

A survey on graph partitioning approach to spectral clustering

Cluster analysis is an unsupervised technique of grouping  related objects without considering their label or class. The objects  belonging to the same cluster are relatively more  homogeneous in comparison with other clusters. The application of cluster analysis is in areas like gene expression analysis, galaxy formation, natural language processing and image segmentation etc. The clustering problem can be formulated as a graph cut problem where a suitable objective function has to be optimized. This study uses different graph cluster formulations based on graph cut and partitioning problems. A special class of graph clustering algorithm known as spectral clustering algorithms is used for the study. Two widely used spectral clustering algorithms are applied to explaining solution to these problems. These algorithms are generally based on the Eigen-decomposition of  Laplacian matrices of either weighted or non-weighted graphs.

Effect of vitamin D supplementation on bone health parameters of healthy young Indian women

Summary There is a huge prevalence of hypovitaminosis D in the Indian population. We studied the efficacy and safety of oral vitamin D supplementation in apparently healthy adult women. Monthly cholecalciferol given orally, 60,000 IU/month during summers and 120,000 IU/month during winters, safely increases 25-hydroxyvitamin D (25 (OH)D) levels to near normal levels. Introduction There is a huge burden of hypovitaminosis D in the Indian population. The current recommendation for vitamin D supplementation is not supported by sufficient evidence. Methods Study subjects included 100 healthy adult women of reproductive age group from hospital staff. They wer

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature