Effect of Individualized vs Standard Blood Pressure Management Strategies on Postoperative Organ Dysfunction Among High-Risk Patients Undergoing Major Surgery

Objective: To determine the effect of individualized blood pressure management targeted upon the physiology of individual patient could help in decreasing the risk postoperative organ dysfunction.  Methodology It was a randomized trial carried out in department of general medicine from March 2016 to March 2017. An approval from Ethics committee was taken. An informed consent in the form of a written document was taken from every patient. Data was analyzed by using SPSS version 24. Student t-test and χ2 test that was unadjusted was performed for the analysis of primary outcome. P value ≤ 0.05 was considered as significant. Results: in the Individualized group, Primary composite outcome was noted as (36.7%) n=55. Acute kidney injury according to RIFLE criteria; Risk, injury and failure was observed as (17.3%) n=26, (9.3%) n=14 and (6%) n=9 respectively. Use of renal replacement therapy was noted as (8%) n=12. Acute heart failure occurred in (6%) n=9. respectively. For Standard treatment group, Primary composite outcome was noted as (48.7%) n=73. Use of renal replacement therapy was noted as (6.7%) n=10. Acute heart failure occurred in (1.3%) n=2. Need for noninvasive or invasive ventilation and sepsis was noted as (30.7%) n=46 and (18%) n=27 respectively. Conclusion: High Postoperative risk patients having major abdominal surgery, the mode of management directed towards the individual blood pressure as compared to standard mode of management proves to be fruitful in decreasing the risk for postoperative organ dysfunction. Keywords: Blood Pressure, Organ Dysfunction, Postoperative complications, Sepsis

Fatalism, Climate Resiliency Training and Farmers’ Adaptation Responses: Implications for Sustainable Rainfed-Wheat Production in Pakistan

Climate change is a severe threat to the agricultural sector in general and to rainfed farming in particular. The aim of this study was to investigate the factors that can potentially affect the adaptation process against climate change. This study focused on wheat farmers and farming systems in the rainfed agroecological zone of Pakistan. Farmers’ data related to climate change fatalism, the availability of climate-specific extension services, socioeconomic and institutional variables, and farm characteristics were collected. A logit model to assess farmers’ decisions to adopt an adaptation measure and a multinomial logit model to assess their choice of various adaptation measures were used. The results showed that fatalistic farmers were unlikely to implement climate change adaptation measures. The variables related to the climate-specific extension services, including farmers’ participation in training on climate-resilient crop farming and the availability of mobile communication-based advisory services, had highly significant and positive impacts on farmers’ decisions and their choice of adaptation measures. Input market access and tractor ownership also had positive and significant impacts on farmers’ decisions to adapt and their choice of adaptation measures. This study highlights the need to improve rainfed-wheat farmers’ education levels to change their fatalistic attitudes towards climate change. Furthermore, government action is needed to provide climate-specific extension services to ensure sustainable production levels that will ultimately lead to food and livelihood security under a changing climate.Fritz Thyssen StiftungStiftung fiat panisPeer Reviewe

Identifying obstacles encountered at different stages of the disaster management cycle (DMC) and its implications for rural flooding in Pakistan

The world has seen a number of natural hazards, but among them, floods are perhaps the most frequent devastating natural hazard, resulting in more human causalities and financial losses. Rural inundation has become an issue of concern in various parts of the world, including Pakistan. Over the past few decades, it has been hard for local institutions and rural populations to recover from the trauma inflicted by these events. The disaster risk management cycle is a well-known tool for coping with disasters and their consequences. Yet, the DRM cycle efficacy has been questioned in various rural settings. Thus, this paper applied a programmatic strategy to understand the challenges disaster management authorities and communities face in managing flood risks through the conventional disaster management cycle in Khyber Pakhtunkhwa province, Pakistan. The study objective was accomplished by using both qualitative and exploratory research designs. Four communities (namely, Peshawar, Charsadda, Nowshera, and Dera Ismail Khan) with a historical record of flooding were chosen for focus group discussion (32 in total) using a purposive sampling method. Additionally, 31 key informant interviews were undertaken from pertinent local disaster risk management institutions. We employed a thematic analysis to classify responses and obstacles into the various stages of the disaster management cycle. The findings of this study from interviews and focus groups provided some new insight into the conventional DRM cycle. The issues and challenges encountered by institutions and the community members were divided into four stages: 1-mitigation, 2-preparedness, 3-rescue and relief (R&R), and 4-rehabilitation and recovery (R&R). Based on the findings, it seems that local disaster management institutions still rely on reactive strategies and deal with flood hazards on an ad hoc basis. Poor governance and a lack of responses for present development trajectories were also highlighted as reasons why flood risk management is still challenging. There is an urgent need to perform susceptibility and risk assessments for multiple hazards and develop specialized plans that follow disaster risk reduction principles and adaptation to climate change. This study recommends incorporating resilience and adaptation to climate change into the current disaster management cycle to prevent or reduce future hazards and risks in rural areas

A systematic review on COVID-19 vaccine strategies, their effectiveness, and issues

COVID-19 vaccines are indispensable, with the number of cases and mortality still rising, and currently no medicines are routinely available for reducing morbidity and mortality, apart from dexamethasone, although others are being trialed and launched. To date, only a limited number of vaccines have been given emergency use authorization by the US Food and Drug Administration and the European Medicines Agency. There is a need to systematically review the existing vaccine candidates and investigate their safety, efficacy, immunogenicity, unwanted events, and limitations. The review was undertaken by searching online databases, i.e., Google Scholar, PubMed, and ScienceDirect, with finally 59 studies selected. Our findings showed several types of vaccine candidates with different strategies against SARS-CoV-2, including inactivated, mRNA-based, recombinant, and nanoparticle-based vaccines, are being developed and launched. We have compared these vaccines in terms of their efficacy, side effects, and seroconversion based on data reported in the literature. We found mRNA vaccines appeared to have better efficacy, and inactivated ones had fewer side effects and similar seroconversion in all types of vaccines. Overall, global variant surveillance and systematic tweaking of vaccines, coupled with the evaluation and administering vaccines with the same or different technology in successive doses along with homologous and heterologous prime-booster strategy, have become essential to impede the pandemic. Their effectiveness appreciably outweighs any concerns with any adverse events

Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-Adjusted life-years for 29 cancer groups, 1990 to 2017 : A systematic analysis for the global burden of disease study

Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.Peer reviewe

Human Regular Activities Recognition Using Convolutional Neural Network

Capturing commonly occurring behaviors is a tough issue in computer vision. A few of them are recreation, touring, leisure pursuits, and religious practice. A comprehensive effort has already been dedicated to this aspect to deal with this issue. In this work, we recreated a dataset with five categories, including household activities, farming, exercise, sports, and occupation, to identify human daily actions. This collection has 4328 colored images in total, among them 630 are set aside for testing, and 3698 for training. Deep learning and standard image-based strategies are being explored to address the issues. In this paper, we have designed a deep learning paradigm to classify the regular activities of human beings. To characterize people's daily chores, we use the CNN model, one of the greatest tools for visual identification. We also have chosen two already-trained VGG16 and ResNet50 models. When we compare our model with the existing techniques, the investigation's findings demonstrate that the suggested network has a better recognition accuracy of 91%. Additionally, we have observed that accuracy varies throughout different epochs, and after 25 epochs we got better stable results from our model. The reader may find this article instructive in grasping CNN models for various recognizing applications

Determinants of Farmers’ Awareness and Adoption of Extension Recommended Wheat Varieties in the Rainfed Areas of Pakistan

Scientific evidence suggests that there is room for eradicating poverty and hunger by increasing food production through the adoption of modern agricultural practices by farmers. This study aimed, first, to explore the relationship between the farmers’ awareness and adoption of improved wheat varieties. Second, it aimed to find the key factors that govern the farmers’ awareness and adoption of extension-recommended innovations in the rainfed cropping system of the Khyber Pakhtunkhwa, Pakistan. Data were collected from 395 respondents. A binary logit model was used to analyze the effect of the farmers’ socioeconomic and farm-specific characteristics on their awareness and adoption of the extension-suggested wheat varieties. Moreover, qualitative data from 40 key informants were collected for in-depth analysis. The results show a strong association between the farmers’ awareness of a technology (improved wheat varieties) and its adoption. The results of the logit model show that their extension contacts, income from agriculture, and access to credit positively affected the farmers’ awareness, whereas their education and household sizes negatively affected their awareness. Moreover, the factors that positively influenced the farmers’ decision to adopt the technology included the extension contact, the confidence in the extension, the risk-bearing attitude, and the credit access, whereas the household size and education negatively affected it. The results of the key informant interviews reveal that the high incidence of poverty, the low soil fertility, the farmers’ inability to make effective decisions, the lack of accurate weather predictability in the rainfed farming system, the lack of government interest, and the asymmetric information in the inputs markets contributed to the farmers’ low levels of awareness and to their poor adoption of improved agricultural technologies. These results indicate that any intervention aimed at the awareness and adoption by farmers of improved technologies, such as new wheat varieties, should recognize the heterogeneity in the farmers’ socioeconomic and farm-specific characteristics

Why Do Households Depend on the Forest for Income? Analysis of Factors Influencing Households’ Decision-Making Behaviors

Using survey information of 150 randomly selected households across 21 villages of the forest-rich district of Swat, Pakistan, this study assessed households’ decision-making behaviors in depending on income from nearby forested land using socio-economic attributes. The evidence from the study may aid in making the existing policies be better targeted toward families that depend on the forest for income. Descriptive statistics and econometric techniques such as logit and tobit were used to analyze the data. Respondent households obtained the highest share of their income from off-farm activities (37%) and least from forest activities (16%). Fuelwood constitutes the biggest share (66%) of forest income, followed by medical plants (20%) and fodder (13%). We found that households with more physical assets, more family members working in off-farm jobs, and households earning more income from off-farm jobs were significantly and negatively associated with households’ decision to depend on forest income and total income obtained. We also found that households with less distance to the market and membership to joint forest management committees (JFMCs) were significantly and negatively associated with households’ total income obtained. However, household size was significantly and positively related to households’ decision of forest dependency. The study recommends the creation of off-farm opportunities and inclusion of local people in the management of forests through establishment of JFMCs, particularly for large and poor families