Effects of Duties in Terminal Patients Wards on Nurses Well-Being

OBJECTIVES: This study was undertaken to explore the working conditions of nurses and well-being during performing their duties in terminally ill patients’ wards in B.V.H and find out the problems faced by them and to assess the impact of these problems on the social lives on nurses of Bahawal Victoria Hospital. METHODS: Survey method was used to collect data from respondents. A total of 214 nurses are working in terminally ill patients wards B.V.H from them sample size of 50% was selected randomly from all the wards of B.V.H with the response rate of 87%. Data was collected from 109 respondents using a self-administered questionnaire as a tool of data collection.RESULTS: The biggest problem faced by nurses in B.V.H is of excessive work load; nurses have to work a lot, B.V.H is facing grave scarcity of nursing staff. Due to intense nature of job, majority of nurses are victim of job stress. Job stressed has also proved to be cause of physical and psychological illnesses; like insomnia, dementia, hypertension and other disorders. What add to the injury is that apart from performing clinical duties, nurses also have to perform ward management as well. They have to maintain the records of medicine inventory in ward, maintain indent book and they are also responsible for the security of machinery or any equipment’s present in the ward. Most of the nurses are annoyed from patient’s attendants and consider them as the biggest hindrance in their job performance.CONCLUSION: Government must provide the accommodation facilities like staff colony for the nurses. The hospital administration should reduce the working hours of nurses to make some sort of relive Born their workload' There must be sufficient paid leaves in a year for the nurses. A proper service structure should be developed so the promotions and demotions should be done in accordance with some Preset rules and standards. The health department must also provide pick and drop services to the local nursing staff. Male nurses should be appointed especially for the night shift.  Quick and strict action should be taken against those who try to harass the nursing staff. Keywords: Nurses, Terminal Patients Wards, Hypertension, Insomnia, Dementia, Harassment. DOI: 10.7176/JHMN/80-07 Publication date:September 30th 2020

Hemodynamic Comparison between modified saddle block and subarachnoid block for Transurethral Resection of Prostate

BACKGROUND:   Spinal anesthesia is often the mode of anesthesia in transurethral resection of prostate (TURP) albeit with risk of hypotension. However, hemodynamic derangement is often less pronounced in saddle block. This study was conducted to compare the mean fall in Mean arterial Pressure (MAP) and Heart rate (HR) between modified saddle block and subarachnoid block for TURP.  OBJECTIVE:   To compare the mean fall in MAP and HR between modified saddle block and subarachnoid block for TURP.  METHODS:   In this randomized controlled trial 120 patients undergoing elective TURP were included and divided into two groups. Group A Patients received subarachnoid block and Group B received modified saddle block. Baseline hemodynamics were recorded before and then at 5 minutes after anesthesia. All the collected data was entered into SPSS version 22 and analyzed. Quantitative data like age, BMI, ASA-PS score, duration of surgery and baseline hemodynamics were presented as means and standard deviations. The fall of mean arterial pressure (MAP) & heart rate (HR) were compared among groups by independent t test and P value < 0.05 was considered as statistically significant.   RESULTS:  Mean fall in MAP was 8.98±1.28 mmHg and 3.13±0.68 mmHg (p<0.001) in group A and B, respectively. Mean fall in HR was 7.17±0.98 and 2.78±0.59 (p<0.001) in group A and group B, respectively.  CONCLUSION:   Modified saddle block resulted in significantly decreased fall in MAP and HR as compared with subarachnoid block for TURP.  KEY WORDS:   Modified Saddle Block; Subarachnoid Block; Mean Arterial Pressure &nbsp

Follow-up bibliometric analysis of neurosurgical publications from Pakistan and institutional comparison with other countries using h-index and i-10 Index

Aim: The aim of the study was to analyze the neurosurgical research output of Pakistan and compare it with that of developed countries.Methodology: We conducted a bibliometric analysis of publically available databases for all neurosurgical publications from Pakistan. All indexed peer-reviewed publications from January 2009 to December 2014 where at least one author was affiliated with any neurosurgical departments in Pakistan and research was conducted in Pakistan were selected. Manual and electronic search was done using MeSH terms to search for articles from Pakistan. Articles were then categorized according to design, subspecialty, region, and year.Results: Our search identified 121 articles during the defined study period (mean = 20.16 ± 5.2 papers/year). A relatively constant increase was noticed for the last 6 years, i.e., 2009-2014. From the total 121 references, 100 (82.4%) publications were from one city, and on subanalysis, 80 (66.1%) were from a single institution. Three primary authors cumulatively contributed to 76 (62.8%) of these publications. Almost two-thirds (n = 76, 62.8%) of these publications were published in either regional or international journals while only 37.2% (n = 45) were published in local nonneurosurgery-specific journals. Only one study in the 6-year study period was with Level I evidence (meta-analysis).Conclusion: Neurosurgery research in Pakistan has shown modest improvement in terms of quality and quantity. Collaboration between various centers and channelizing different resources to create national data registries along with basic science laboratories is much needed

Determining the Influences of the Employee’s Loyalty in the Organizational Setting

The aim of the following research is to provide a brief insight into employee loyalty towards their organization and its effects on working conditions, working environment, and bonus and incentives. As employees are considered to be key strategic assets of every organization so it is essential for the organization to study the factors which produce a profound effect on loyalty. Loyalty is said to be a unique composition of employee attributes depicting a higher quality which is difficult to find significantly affecting the prevailing organization succession. For the progression of the research findings, the precedent research followed a T-test, F-test, ANOVA, multiple regressions, Factor analysis, Durbin Watson, correlation as the methodology. The following methodology aid inevaluating the crucial elements of the organization significantly affecting the employee loyalty. Moreover, in the research working condition, working environment and bonus and incentives served as the dependent variable, while employee loyalty as the independent variable. The researcher has employed the calculation of the observation from self-design 100 questionnaires which were filled by Muslim commercial bank employees in all over Karachi, all result have significant impact at 5% alpha.  On the basis of data, it can be concluded that the determinants of the independent variable of the current dissertation have a significant impact on employee loyalty. Moreover, all of the three independent variables have been accepted. Therefore, it is feasible to suggest that the organization should focus on the prevailing variables for enhancing the performance of the organization and driving the optimal outcome for securing the leading position in the industry

Energy scan/dependence of kinetic freeze-out scenarios of multi-strange and other identified particles in central nucleus-nucleus collisions

The transverse momentum (mass) spectra of the multi-strange and non-multi-strange (i.e. other identified) particles in central gold-gold (Au-Au), lead-lead (Pb-Pb), argon-muriate (Ar-KCl) and nickel-nickel (Ni-Ni) collisions over a wide energy range have been studied in this work. The experimental data measured by various collaborations have been analyzed. The blast-wave fit with Tsallis statistics is used to extract the kinetic freeze-out temperature and transverse flow velocity from the experimental data of transverse momentum (mass) spectra. The extracted parameters increase with the increase of collision energy and appear with the trend of saturation at the Beam Energy Scan (BES) energies at the Relativistic Heavy Ion Collider (RHIC). This saturation implies that the onset energy of phase transition of partial deconfinement is 7.7 GeV and that of whole deconfinement is 39 GeV. Furthermore, the energy scan/dependence of kinetic freeze-out scenarios are observed for the multi-strange and other identified particles, though the multiple freeze-out scenarios are also observed for various particles.Comment: 12 pages, 2 figures. The European Physical Journal A, accepte

STOCK MARKET COINTEGRATION: EVIDENCE FROM DEVELOPED AND DEVELOPING EQUITY MARKETS

This study examined the relationship between KSE and stockmarkets of developed and developing countries for the period of 2000-2012. Cointegration approach showed that one cointegrationequation exists in KSE and developed countries equity markets andtwo cointegration equations exist in KSE and developing countriesequity markets case. Granger causality test showed a uni-directionalrelationship between KSE and developed and developing markets,and a bi-directional relationship with Taiwan’s equity market.Variance decomposition analysis showed that most of the changes inKSE are due to its own dynamics in both the developed and developingmarkets. Correlation matrix shows that there is a weak or nocorrelation between the KSE and developed and developing countriesso the benefit of diversification can be achieved by investing in KSE

Demand Side Management Techniques for Home Energy Management Systems for Smart Cities

In this paper, three distinct distributed energy resources (DERs) modules have been built based on demand side management (DSM), and their use in power management of dwelling in future smart cities has been investigated. The investigated modules for DERs system are: incorporation of load shedding, reduction of grid penetration with renewable energy systems (RES), and implementation of home energy management systems (HEMS). The suggested approaches offer new potential for improving demand side efficiency and helping to minimize energy demand during peak hours. The main aim of this work was to investigate and explore how a specific DSM strategy for DER may assist in reducing energy usage while increasing efficiency by utilizing new developing technology. The Electrical Power System Analysis (ETAP) software was used to model and assess the integration of distributed generation, such as RES, in order to use local power storage. An energy management system has been used to evaluate a PV system with an individual household load, which proved beneficial when evaluating its potential to generate about 20–25% of the total domestic load. In this study, we have investigated how smart home appliances’ energy consumption may be minimized and explained why a management system is required to optimally utilize a PV system. Furthermore, the effect of integration of wind turbines to power networks to reduce the load on the main power grid has also been studied. The study revealed that smart grids improve energy efficiency, security, and management whilst creating environmental awareness for consumers with regards to power usage

Improved Classification with Simultaneous Feature Selection of Speech Signals for Parkinson's Patients

Parkinson's disease (PD) is a brain disorder occurs due to a deficiency of dopamine hormone that regulates activities of the human body. Generally, the disease can be diagnosed by clinicians through clinical observation where they categorized PD patients on a PD assessment scale to understand disease severity in order to define a therapy/treatment plan. The clinicians have a view that this approach is not suitable for diagnosis at an early stage of the disease. Recent research outcome has shown that PD patients exhibit vocal impairment at the early stage of the disease, and this is now becoming a benchmark for early PD detection. Often researchers employ state-of-the-art speech analysis techniques that exploit various extracted features to meet the objective. An optimal set of features that best explains the problem often requires careful attention to the selection of extracted features in use. As a general practice, data analysts have a view that it is better to collect as many features as possible related to the problem but at the same time, it is also believed that the presence of some noisy features can also compromise classification ability. Our main objective in this work is to select/identify the optimal set of features to utilize for the machine learning classification models with an objective to have an improved early PD detection in patients. The selection of optimal features set will not only help clinicians to quickly diagnose PD but will also be useful to develop a better patient care strategy at an early stage of PD. In this study, various experiment are conducted to observe the most contributing speech feature to classify PD patients. The study have showed by using the Best-First feature selection approach the most optimal features from the PD dataset can be achieved. The efficacy of our approach with the optimal set of features has shown an improvement in classification with an accuracy of 92.19% that is better than the earliest reported accuracy of 86% [23] for an almost similar number of features